Tag: hydroponic

These studies include a wide range of process-based crop models as well as empirical papers, published between the late 1990s and 2012, and they vary substantially in the geographic regions examined as well as the extent to which they include on-farm adaptations. In this paper we focus on maize, rice, soy and wheat, four crops that make up a major part of the scientific literature on climate impacts on crops. These crops collectively account for approximately 20% of the value of global agricultural production, 65% of harvested crop area, and just under 50% of calories directly consumed . For these four crops, the database contains 1010 data-points . Of these, 451 are reported as including some form of onfarm, within-crop agronomic adaptation. The majority of these adaptations involve adjusting either planting date , cultivar or both . In total, 28 models are represented in the 56 studies used for the estimation, made up of 17 process-based model families and 11 statistical models. For this analysis we have complemented the existing database in two ways. Firstly, we coded each study based on whether a process-based or empirical approach was used. Secondly we added baseline growing-season temperatures to the database. To do this, each data point was assigned to a country. 86% of points come from studies located in a single country. For the remaining 14% coming from studies with an international scope the assigned country was the country with the highest production of the relevant crop. Average growing season temperatures were calculated using planting and harvest dates from Sacks et al and gridded monthly temperature from the Climate Research Unit . We treat the database of studies as a kind of ‘ensemble of opportunity’ . The benefits of this approach are that predictions from multi-model ensembles have been shown to consistently out-perform individual models in both climate modeling and, increasingly, in agricultural modeling .

Though not derived from a formal ensemble modeling project,growing raspberries in pots the universe of individual studies contained in the database can be thought of as draws from a set of possible models, each of which captures the response of crops to changing climate conditions with some error. The sampling of models is not systematic or random, but instead has emerged from scientific research and associated peer review of work on climate effects on crop yields over the last two decades. The approach described here takes advantage of an implicit weighting derived from representation of models within the scientific literature. To the extent that this representation reflects researchers’ judgements about the best model to use for particular crops in particular locations, it may be that this implicit weighting emerging from the scientific literature is preferred to simpler one-model one-vote aggregation schemes . We use multiple regression to aggregate the results from individual studies to an ensemble average response function. This approach allows us to estimate common response functions at an appropriate level of aggregation. For example, every study in the database examines the effect of change in temperatures on yields, allowing us to estimate separate yield response functions by crop and by baseline temperature, as well as by type of study. Fewer studies examine the effect of CO2 fertilization or adaptation, limiting our ability to model heterogeneity in response to changes in these variables.The effect of adaptation on crop yields is modelled with both an intercept term . This is prompted by the observation that in many studies that report including on-farm agronomic adaptations, adaptation is represented by changing management practices that would improve yields even in the current climate . Failing to include an adaptation intercept in this context will lead to an over-estimation of the potential of the adaptation actions included in these studies to reduce the negative impacts of a warming climate. We therefore include an adaptation intercept in the estimating equation but then subtract it out to produce a damage function that goes through the origin. The true effect of adaptation is captured by the interaction with temperature change, given by the b8 term in equation .

This term reflects the effect of management changes that are not beneficial today but that will be beneficial under a changed climate, the standard definition of adaptation. To estimate the impact of local warming for a prespecified increase in global mean temperature we use pattern-scaling between local and global temperature changes based on the CMIP5 multi-model mean for RCP8.5 . The multi-model mean was calculated using the Climate Explorer tool using methods documented in van Oldenborg et al . For each grid cell we take the change in temperature between a future and baseline period and divide by the mean global warming over this time period. Local warming is greater than global average warming over land areas and is larger at high latitudes and in continental interiors. Gridded local temperature changes are combined with the response functions estimated using equation and baseline growing season temperatures based on CRU and Sacks et al to give projected changes in yield with warming on a 0.5 degree grid. Global average yield changes are calculated by production-weighting the gridded data using production data for the relevant crop in the year 2000 . In presenting results, we focus on global temperature changes ranging from 1 to 3 °C and use 4 cases to examine the importance of different variables. The reference case is based on the temperature response curves for process-based models, including CO2 and adaptation. The ‘No CO2’ case is the same as the reference except without CO2 fertilization. ‘No Adaptation’ is the same as the reference except excluding adaptation. And finally, the ‘Statistical’ case is the same as the reference except the temperature response comes from statistical studies. In order to assess the economic implications of alternative studies of climate impacts on crop yields, we use the Global Trade Analysis Project model . GTAP is a global, computable general equilibrium model which seeks to predict changes in bilateral trade flows, production, consumption, intermediate use and welfare, owing to changes in technology, policies or other exogenous shocks. In this case, we treat the climate-induced yield changes as Hicks-neutral productivity changes. Thus, a 10% yield loss would mean that, if farmers did not alter their practices in the face of the changing climate, application of the same inputs to the same amount of land would result in 10% less output. The economic model does allow for changes in area planted, as well as input intensities, in response to changing relative prices, so actual yields will not change by 10%.

In this sense, all of the economic results reported here allow for economic adaptation . In order to implement the yield shocks under the different climate scenarios, we aggregate the gridded impacts for each of the four crops to the level of the 140 countries/regions in the version 9 GTAP data base . Since maize and soybeans are part of larger crop aggregates in the GTAP data base , the climate-induced yield shocks are diluted by multiplying them by the share of the country-commodity aggregate made up of maize and soybeans, respectively. Thus in a region which does not produce soybeans, the climate shock would be zero, whereas a country in which maize was the only coarse grain produced would experience precisely the productivity shock specified by the aggregated maize results for that geographic region. To be consistent with these incomplete agricultural yield shocks,plant pot with drainage when it comes to reporting the welfare losses, we report the losses as a share of that incomplete production value .Figure 2 shows the temperature response functions estimated from equation . Warming has a negative impact on yields that is worse for maize and wheat than for the more heat-tolerant rice. It is striking that we find very little evidence for any yield benefits from warming over most growing areas—our point estimates are negative even for warming less than 1 °C and even in the 25th percentile of growing season temperatures . This negative impact is generally statistically significant for process based model results at warming above 2 °C. Standard errors for results from statistical models are much larger and bracket zero in almost all cases. The interaction with baseline temperature is in the expected direction: warming is less damaging for crops in cooler locations. Figure S1 shows the gridded yield responses to 2 °C of global average warming for each crop. While many areas see negative impacts, there are some positive effects in the boreal zone and in cooler temperate areas. In figure S2 we show a comparison between our estimated response to a 1 °C warming and the mean of multiple process-based crop models calibrated to specific locations as part of the Agricultural Modeling Inter-comparison and Improvement Project for the three crops that are available: maize , wheat , and rice . The results from these two very different methods are close for both wheat and maize while the findings for rice show more variability. In all cases the AgMIP data are well within the 95% confidence interval produced in this study. Figure 3 shows how the type of study, inclusion of adaptation , and the CO2 fertilization effect affect the climate change response. Point estimates for b3 and b4 suggest that on average results from statistical studies are slightly more optimistic than results from process-based models for small amounts of warming and more pessimistic for higher levels of warming. Error bars for the statistical model are extremely large though, particularly for warming beyond 2 °C, which is perhaps unsurprising given the concentration of empirical results at 1° warming documented in figure 1. The point estimate for the effect of adaptation is in the opposite direction from what would be expected , but the error bars are large and the effect is not distinguishable from zero.

Studies that include adaptation do have more positive yield outcomes than studies that don’t, but those benefits are captured entirely in the adaptation intercept term . Therefore, these findings suggest that most within-crop agronomic adaptation measures represented in process based modeling studies would provide the same benefit under the current climate as they would under future climates. In other words, they are actions that shift the supply curve out to the right but do not change the marginal impacts of future warming, consistent with the ‘adaptation illusion’ identified by Lobell . Finally, the CO2 response functions show statistically-significant benefits of CO2 fertilization that a symptote at 17.3% for C3 crops and 10.6% for C4 crops. Given the functional form assumption, this translates to yield gains of 11.5% and 8.5% for a doubling of CO2 from pre-industrial levels. For C3 crops, this value is close to that obtained from FACE experiments which range between 12 and 14% yield gains for a doubling of CO2 . and therefore this may not be a fully independent validation of the meta-analysis results.Fewer FACE experiments have been performed for C4 crops but available experimental data, as well as theory, suggest C4 crops will benefit less from CO2 except under water-stressed conditions. Figure 4 shows global production-weighted yield losses for a global temperature change of 1 °C–3 °C for four cases. Except for soybeans, the reference case that includes CO2 fertilization and adaptation shows positive effects on yields at low levels of warming, becoming negative between 2 °C–3 °C of warming. Variation between the different cases reflects what might be expected given the response curves shown in figure 3. CO2 fertilization is most important– excluding the CO2 effect produces substantial losses for all crops ranging from 14% to 25% at 3 °C of warming. The effect of excluding adaptation is very small. The effect of statistical as opposed to process-based studies is small and slightly positive for 1 °C–2 °C, becoming slightly negative at 3 °C. At higher levels of temperature change we would expect this effect to become more negative . The 95% confidence intervals are large and mostly bracket zero, with the exception of the No CO2 case at 3 °C of global average warming. Uncertainties are particularly large for soybeans and for the statistical case at 3 °C of warming—both instances where the number of data points in the meta-analysis are limited.

With respect to this aim of separate the role of demand for and supply of labor as drivers of sectoral reallocation, our work is, in fact, mostly related to Lee and Wolpin . Lee and Wolpin devised and structurally estimated a rich model to study the process of labor reallocation from manufacturing to services in the United States. We see our work as complementary to it, to the extent that we are interested in a similar question, but we tackle it from a different perspective. Specifically, our approach aims to impose the minimal structure to interpret the data, closer in spirit to the accounting literature. Relative to the three papers above, we also depart in extending our empirical analysis to as many countries as we could gather data for, rather than focusing only on the United States. Using multiple countries allows us to provide additional ways to identify the size of the mobility frictions, which is an important component of our analysis. More broadly, our work is related to a rich literature that studied the contribution of human capital to growth and development. This literature showed that the level of human capital is significantly correlated with consequent growth , Barro , Mankiw et al.. However, the effects of changes in human capital stocks have been much more elusive and Pritchett. Pritchett in particular, in a famous article, asked: “Where has all the education gone?”. In this respect, our work provides some encouraging answers: we show that growth of human capital stocks matters for explaining reallocation out of agriculture. Methodologically, we are in debt to the approach developed by the growth and developing accounting literature , Barro , Hsieh and Klenow , and more recently Gennaioli et al.. Relative to this literature, we show that observable variation across birth-cohorts can be used in an accounting framework,gallon pot and we introduced a way to measure the role of human capital without having to rely on prices.

In terms of the purely empirical contribution of this paper – that is, documenting novel cross country patterns in reallocation out of agriculture by cohort – our work relates to Kim and Topel , Lee and Wolpin , and Perez , which document sectorial reallocation by cohort but limit their focus to, respectively, South Korea and United States and Argentina; and especially to Hobijn et al. , which, in ongoing work, is also using the IPUMS dataset to document patterns on reallocation across sectors by cohorts, and use them to motivate a model linking demographic forces to structural change. Our model combines elements and insights already presents in Matsuyama , Lucas , and Herrendorf and Schoellman . To the best of our knowledge, we are the first to provide a tractable framework to analytically characterize reallocation within and across-cohorts in a context with general mobility frictions. Hsieh et al. also exploits year and cohort effects to calibrate a model of allocation of talent. It uses them to discipline the relative role, for the aggregate efficiency of the allocation of talent, of changes in frictions that affect human capital investment and frictions that distort the labor market. Relative to this paper, we focus on a simpler framework that allows us to consider fixed-cost-type frictions, which turn out to be crucial to correctly identify the role of human capital. Finally, our work relates to a growing literature that uses longitudinal wage data to reconsider the agricultural productivity gaps and that shows that these gaps are more consistent with sorting across-sectors than with large mobility frictions; , Herrendorf and Schoellman , and Hicks et al.. We contribute to this literature in two ways: we provide a model that highlights when wage data can be informative on frictions; and we show, without relying on wage data, additional evidence corroborating the sorting explanation and casting doubts on the presence of large mobility frictions.We next describe how we use data to quantify the role of human capital in labor reallocation out of agriculture. This is motivated by the results in Proposition 2, which provide an accounting framework to link within- and across-cohorts labor reallocation to the relative contribution of human capital vs. prices/productivity in reallocation out of agriculture. In this Section, we start by documenting a number of novel cross-country facts about reallocation by cohort using micro level data for a large set of countries.

Most of the cross-country evidence available to date only covers aggregate rates of reallocation. Our paper is among the first to provide micro level evidence on the behavior of different cohorts of workers in the process of structural transformation. We present the patterns descriptively to convey information on what the data say in a transparent format, focusing on the novelty of the findings rather than on their role in our approach. In Section 4 we will instead interpret the observed patterns through the lens of theory. There, we make explicit how Proposition 2 can be brought to the data to make inference on whether human capital matters for the movement of workers out of agriculture. Below we introduce the data and measurement approach, and then discuss the novel crosscountry findings on reallocation by cohort.We use micro level data from the Integrated Public Use Microdata Series 8. The data are either censuses or large samples from labor force surveys that are representative of the entire population. We include in our analysis all IPUMS countries for which we have available at least two ten-years apart repeated cross-sections with available information on age, gender, and working industry. This gives us a sample of fifty two countries covering about two thirds of the world population. For fifty one countries, the IPUMS data also include geographical information at the sub-national level which we use in our analysis as a source of additional variation.9 For twenty three countries, we observe four or more cross-sections, for seventeen we observe three or more. On average, we observe countries over a period of 28 years. For some countries, such as United States and Brazil, our data cover a long time span of half a century or more of labor reallocation. Table A.1 in the Appendix lists the countries in our sample, the income level of each country, in 2010, relative to the one of United States, the years of coverage, the agricultural employment shares, and the number of observed cross-sections. The countries in the sample comprise a wide range of income levels, from the United States to Liberia and El Salvador. Eight countries are high-income countries, twenty five are middle-income countries and the remaining nineteen are low-income10. Our sample also spans a large geographical area, covering Asia and Oceania , Africa , Central and South America , and Europe and North America . We focus on males and restrict our attention to those aged 25 to 59. This is meant to capture working age and identify the period after education investment is completed, which allows to consider human capital as constant.

We exclude women from the current analysis given the large cross-country differences in female labor force participation.In the model, we assumed that each cohort has equal size and that size is constant over the life-cycle. In the data, however, we observe that cohorts have different sizes,gallon nursery pot and that the size of a given cohort changes over time due to mortality. We may be concerned that these demographic compositional effects are relevant in explaining the cross-country variation in cohort and year effects. We here perform a series of exercise to show that, reassuringly, demographic composition does not mechanically drive our estimates. First, we compute the year effect weighting each cohort by its share in the population at time t + k rather than at time t. In Figure 8a, we show that this change does not make any difference. Second, we compute the year effect with the raw data – i.e. without smoothing the demographic distribution, which we did in the benchmark exercise to adjust for age-heaping. As is well know, Indian data suffer from extreme age-heaping. Consistent with this, we see in Figure 8b that only in India the year effect estimated with the raw data is different from the benchmark one. Third, we recompute the rate of labor reallocation out of agriculture keeping constant the demographic structure at time t – i.e. we compute LA,t+k weighting each cohort according to !t . Figure 8c, shows that the estimated rate of labor reallocation are almost identical to the benchmark ones. Finally – in Figure 8d – we perform the same exercise, but keeping constant the demographic structure at time t + k. Again, we conclude the demographic changes do not have relevant mechanical effects. In Figure A.3 in the appendix, we recompute the same exercise using sub-national units. We find similar results.This section introduces our empirical approach and discusses how we make use of the data and patterns described above to quantify, in an accounting sense, the relative contribution of human capital and prices/productivity to labor reallocation out of agriculture. Our main starting point is Proposition 2, which tells us that we can do so by leveraging within- and across-cohorts reallocation. Proposition 2 provides a mapping between two observable objects, year and cohort effects, and our two main objects of interest, the contribution of human capital and of prices/productivity to labor reallocation. The mapping, however, is made challenging by the possibility that labor mobility frictions bind, and by general equilibrium. The spirit of our empirical exercise in this section is to exploit – through multiple approaches – observable variation in year and cohort effects both across- and within-countries to discipline the size of the frictions. We then use further micro level data to calibrate the strength of the general equilibrium. We provide a range of estimates depending on parameter values, but the overarching conclusion, which we reach in Section 4.1, is that human capital explains approximately one third of total reallocation out of agriculture. In Section 4.2, we show that, at the same time, human capital has at most a minor role in explaining why some countries have faster reallocation rates than others.Next, we provide estimates for the size of the friction through a series of different exercises. The results of our estimates are summarized in Table 2. Conceptually, we follow two main alternative methods, each tied to a source of variation that can be exploited to back out the size of the frictions. Our first method builds on Proposition 3, which relates the size of labor mobility frictions to the reallocation rates of individuals of different ages. The fixed cost traps in agriculture individuals that would otherwise move to non-agriculture in a frictionless environment. This effect, however, is not symmetric across ages, and is instead stronger for older individuals: they benefit from future increases in non-agriculture wages for fewer years and hence, for given fixed cost, face a stronger constraint. This means that the presence of frictions causes old individuals – the constrained – to reallocate at a slower rate than young individuals – the unconstrained. Fact 3 in Section 3 showed that old and young individuals reallocate at similar rates, thus providing evidence against a sizable role for mobility frictions. The following Lemma shows that this intuition can be used to provide a direct estimate for the size of the frictions.In this section, we provide a proof of concept that it is possible to trigger reallocation out of agriculture through policies that successfully increase the educational attainment of the population. To do so, we identify the causal effect of schooling on labor reallocation out of agriculture in the context of a school construction program in Indonesia. Following the seminal work of Du- flo , we use the INPRES school construction program, which built 61,000 primary schools between 1974 and 1978, to provide quasi-experimental variation in schooling. While the intensity of the program, captured by the number of new schools per pupil, was not random, only somecohorts, those younger than 6 at the time the program started, were fully exposed to the program. Therefore, we can run a fairly standard difference-in-difference exercise: we compare cohorts fully exposed to the treatment to those not exposed to it, in districts with higher or lower treatment intensity.

With respect to anionic retention, etherification of rice straw increased the maximum adsorption capacity of sulfate from 11.68 to 74.76mg g−1 by introducing amino groups . Generation of positively charge, −C-N+ moieties, was responsible for the removal of sulfate by electrostatic interactions. Furthermore, triethylamine-etherification significantly accelerated the adsorption rate of wheat straw for anionic constituents . Adsorption equilibrium was achieved in 35min for HCrO4 − and 15min for H2PO4 −, compared with 3hr for the unaltered biomass. Accordingly, the adsorption capacity of modified wheat straw for HCrO4 − and H2PO4 − were 0.98 and 1.15mmol g−1 , respectively. Electrostatic attraction, complexation and ion exchange mechanisms were the most prominent sorption mechanisms contributing to cationic and anionic retention by etherified adsorbents.Carbonization is a thermal decomposition process of organic materials resulting in the production of a carbonaceous residue with a concomitant removal of distillates. Conversion of agricultural wastes into bio-char is a common carbonization process that has been extensively studied . Biochar products have a larger specific surface area, greater porosity and more functional groups than the raw agricultural wastes from which they were formed . The alkaline nature and the existence of mineral constituents on bio-char surfaces also promote the formation of metal precipitates on the bio-char surface . The fixation ability of original bio-char for pollutants is relatively limited and many studies have explored altering pyrolysis conditions to generate activated bio-chars with altered functional groups and rougher surfaces to enhance sorption capacities for various pollutants. Carbonization temperature has an especially strong effect on the properties of bio-char generated from agricultural waste . In general, bio-char produced at lower temperatures contains a greater functional group content,black plastic plant pots whereas those produced at higher temperatures have a more porous surface and overall porosity .

For example, aldehyde and ketone functionalities formed at ~200°C and became dominant at 300~500°C, increasing the adsorption capacity for various pollutants . However, the drastic fusion of the ring structures in bio-char occurred from 550 to 650°C, which decreased the content of functional groups and weakened the chemical fixation for pollutants. The influence of feedstock source is also an important factor determining the efficiency of pollutant removal by agricultural waste-derived bio-chars. The type of functional groups and chemical components comprising various agricultural wastes are different, thereby significantly affecting the adsorption performance. The most important of these properties in relation to the adsorption capacity were the O/C ratio, the P content and the ash content . The capacity of the bio-char to retain Cu present in solution depended on the size of the inorganic fraction and varied in the following order: rice bio-char > chicken manure bio-char > olive mill waste bio-char > acacia bio-char > eucalyptus bio-char > corn cob bio-char. The addition of chemical amendments to the biomass feedstock has an appreciable effect on bio-char characteristics and the adsorption performance of the bio-char material. The selective introduction of functional groups, heteroatoms, metal atoms into bio-char can improve its specific properties. In-situ synthesis of bio-char refers to the preparation of modified bio-char in only one step by simultaneously pyrolyzing reagents and agriculture wastes. As a result, the modified bio-char has the optimized physicochemical structures and properties. Postoptimization of bio-char is useful to further enhance its potential value after pyrolysis, a special bio-char could be designed via the further surface modification and pore regulation. For example, H2SO4 addition during carbonization generated excellent sorption performance for methylene blue, brilliant green, crystal violet and orange G by formation of -SO3 groups on the bio-char surface that increased the chemical afinity for pollutants through covalent bonding . Similarly, HNO3 addition to the feedstock generated N-containing functional groups on bio-char, with the positive ≡N+ group interacting with the negative -O≡, N=C and heterocycle N-C groups on methylene blue to facilitate adsorption . In addition, the weakly acidic FeCl3 would be transformed to Fe2O3 during the preparation process of bio-char, increasing the Fe-O functional groups strongly on the surface of bio-char .

The peaks of Fe 2p1/2 and Fe 2p3/2 shifted after the stabilization of Cd, suggesting that the iron-bound functional groups participated in the Cd retention actively. The addition of alkaline reagents was shown to increase both surface area and functional group content of bio-chars. Activation of orange peel bio-char with CO2 and KOH strongly altered several physicochemical properties . During pyrolysis, CO2 reacted with K2CO3 to generate NH3 and create a more porous structure with increased N-containing groups, which correspondingly increased the retention of methylene blue. Addition of oxidizing agents is a common technique for generating higher concentrations of oxygenated functional groups on bio-char surfaces . Co-pyrolyzed peanut hulls with H2O2 resulted in an increase in the O content and surface carboxyl functional groups, improving chemical adsorption . As another example of oxidation effects, a KMnO4-treated hickory wood bio-char surface was covered with ultrafne MnOx particles exhibiting a surface enrichment of O-containing functional groups and a higher surface area . Metal retention by this engineered bio-char mainly resulted from surface adsorption mechanisms involving both the surface MnOx particles and O-containing functional groups. A myriad of studies have demonstrated the efficacy of carbonization as an effective method for improving the adsorption performance of agricultural wastes, especially for modified bio-char adsorbents . The total adsorption capacity for Cd2+ increased due to the introduction of C-S complexes on bio-char that facilitated the retention of Cd2+ through a strong bond with S . Wang et al. showed that maximum acid red 18 dye sorption capacities for NH4Cl/CH3COONH4-modified adsorbents were 1.41 and 1.18 times higher than for non-N-doped bio-char. The enhanced sorption affinity was mainly attributed to π-π EDA interactions between pyridine-N groups and acid red 18. The N functional groups enhanced the surface polarity, thereby increasing interactions with adsorbates, such as acid red 18. In addition, the amino functional group greatly improved the adsorption behavior of Cr6+ by polyethylenimine-treated rice husk bio-char . A pseudo-second-order kinetic model indicated a maximum Cr6+ adsorption capacity of 435.7mg g−1 compared to only 23.09mg g−1 for natural bio-char. Moreover, this new material exhibited excellent cyclic adsorption ability making it a low cost, ecofriendly adsorbent.

In summary, carbonized agricultural wastes are an economical and effective approach for pollutant removal from water owing to their intrinsic physicochemical characteristics. Abundant functional groups, high surface area and a porous structure allow bio-chars to rapidly interact with pollutants through a variety of adsorption mechanisms . Furthermore, introduction of chemical amendments to the carbonization process can generate specific chemical moieties that selectively target the removal of specific pollutants.Magnetization of modified agricultural wastes, such as bio-char, is a strategy to introduce transition metals or their oxides into the organic matrix to create a material that is easily separable with an external magnet. Importantly, magnetic adsorbents can be easily removed making them highly effective for the removal of pollutants from aqueous solutions. Moreover, the doping of metals or metal oxides onto the surface of agricultural wastes can target specific functionalities to enhance adsorption properties, such as the modification of lignocellulose by magnetic materials to improve sorption of chloramphenicol while simultaneously allowing easy recovery and reuse of the material during adsorption applications . Nanoscale-zero-valent, iron-coated wheat straw exhibited better adsorption performance for removal of Cu2+ than the raw adsorbent . A portion of the Cu2+ was directly adsorbed by the wheat straw, whereas another fraction of the Cu2+ was frst reduced to zero-valent Cu and Cu2O, which were subsequently attached to the surface of the material as part of the crystalline Fe-oxide structure. Further, doping agricultural wastes with Fe oxides was shown to promote the removal of anionic As5+ due to enhanced surface interactions associated with the Fe oxides . The Fe-oxide modified sugarcane bagasse rapidly removed H2AsO4 − oxyanions by electrostatic interactions, ligand exchange and chelation reactions between the positively charged surface ≡FeOH2+ group and the negatively charged H2AsO4 −. Loading Fe3O4 on the surface of organic materials is a common technique for magnetization that can be achieved by ferrofuids,black plastic pots for plants microwave assisted and mechanochemical techniques . Co-precipitation is also widely adopted to synthesize and load Fe3O4 on material surfaces, the changes for -OH and Fe-O groups in Fe3O4-modified straw resulting from the combination of O in the straw with the Fe of Fe3O4 . The modification further increased the BET surface area from 3.37 to 23.56 m2 g−1 . Pb2+ was retained on the Fe3O4-modified straw through diffusion adsorption and chemical fixation with O-containing functional groups. Similarly, Khandanlou et al. demonstrated an increase in the pore volume and BET surface area by 12 and 22 times after Fe3O4 modification, respectively. The enhanced porosity and functional group activation prominently promoted the adsorption of Cu2+ and Pb2+. Further, a Fe3O4−doped organic adsorbent exhibited excellent sorption capacity for Cd2+ and Pb2+, with Fe-OH groups playing an important role in the adsorption mechanism . The modified adsorbent also had a more robust regeneration efficacy than the raw bagasse as the Fe3O4 stabilized the surface properties. The effect of SnO2/Fe3O4 doping on the adsorption affinity of reactive blue 4 and crystal violet by treated rice bran was investigated by Ma et al. .

They found that pore size was increased by 2~4nm and the FTIR peaks for Sn-O and Fe-O strengthened upon doping with SnO2/Fe3O4. The numerous -OH groups associated with the SnO2/Fe3O4-adsorbent interacted with the reactive blue 4 and crystal violet to effectively remove these polluting dyes from solution. The removal efficiencies of magnetic biosorbents for pollutants are listed in Table 6. Magnetization of wheat straw increased the adsorption capacity for Pb2+ by 23%, with an optimal contact time of 30min facilitating rapid processing . Baldikova et al. found that magnetized barley straw increased adsorption of methylene blue and crystal violet by 16.7% and 54.9%, respectively, due to creation of a larger surface area. Further, the SnO2/Fe3O4-doped rice bran showed a high adsorption affinity for reactive blue 4 and crystal violet with sorption capacities of 218.8 and 159.2mg g−1 , respectively . Characterization of the SnO2/Fe3O4-absorbent indicated that the surface was covered with abundant -OH functional groups, which played an important role in increasing the adsorption capacity through strong electron attraction. Moreover, Fe oxide-modified sugarcane bagasse showed a superior potential for H2AsO4 − removal compared to several other modification methods . Positively charged ≡FeOH2 + and negatively charged H2AsO4 − rapidly interacted through electrostatic interactions and ligand exchange reactions. Overall, magnetic adsorbents have demonstrated the capacity to efficiently remove heavy metals, anionic constituents, antibiotics and various dyes from water. The most prominent feature of magnetic modification is that a product can be easily recovered and reused, with improved the utilization efficiency and reduces production/use costs.Surfactants are compounds that consist of hydrophilic heads and hydrophobic tails, which can reduce the surface tension between different media when used as detergents and dispersing agents . The charge characteristics of the hydrophilic head classify the surfactants as ionic and non-ionic surfactant groups . Various functional groups occur in the structure of ionic surfactants, favoring the selective adsorption of various pollutants in solutions. Thus, surfactant modifications improve the surface hydrophobic/hydrophilic properties and enrich the variety and quantity of functional groups comprising agricultural wastes. Linear alkyl benzene sulphonates, secondary alkane sulphonates, alkyl trimethyl ammonium halides and quaternary ammonium-based compounds are common surfactants with widespread applications . Cationic surfactant treated agricultural wastes demonstrate a good potential for removal of anionic pollutants. Cetyl trimethyl ammonium bromide modified wheat straw obtained higher N , C and H contents than that of the origin wheat straw due to the loading of the surfactant . FTIR spectra indicated that the -CH2 peak strengthened while the -NH2 and -OH bands broadened in wheat straw after modification. Changes in these characteristics indicated that modification increased the number of ammonia functional groups, which combined with Congo red dye through ionic interactions. Moreover, the adsorption results indicated that π-π dispersion interactions between the surfactant and dye played an important role in the removal of the Congo red dye. Furthermore, Tamilarasi et al. found that cetyl trimethyl ammonium bromide formed a surfactant bilayer containing anion exchange properties due to reaction with acidic functional groups on palm fruit husk surfaces. The surfactant loading on the surface of the palm fruit husk surface reached a maximum at a cetyl trimethyl ammonium bromide concentration of 1.0% in solution.

Solutions will also require the provision of quality education to rural populations, including on the use of digital technologies,so that the agricultural and rural workforce can maximally benefit from new technologies and off-farm employment opportunities. To mitigate problems that arise during the farm labor transition and help prevent a reversal to agricultural policy distortions, adequate social protection systems that mitigate calls for agricultural protectionism must be developed. The decoupling of social protection from employment holds promise in that regard , with the massive expansion of social protection provisions across the globe in response to COVID-19, especially through cash transfers, providing useful experiences and platforms to build upon. The remainder of this paper discusses the impact and evolution of these different forces and reflects on a policy agenda that can leverage the future global food system to generate decent employment, accelerate poverty reduction, and attain shared prosperity. Work in agriculture tends to be seasonal and dispersed across space, with labor productivity often low and unpredictable. High fertility among rural and agricultural populations, partly in response to low and variable agricultural earnings, often contributes to low labor productivity. As countries become more affluent, their demand for nonfood goods and services increases, and their work forces shift out of agriculture into more stable, high-paying, jobs in industry and services.The development of food manufacturing and services is particularly important in the process of narrowing cross-sectoral income differences. These nodes of the AFS tend to be more labor-intensive and less high tech than other industries and services, more likely to employ women and unskilled workers ,drainage planter pot and less spatially concentrated .This pattern of structural transformation is evident historically in high-income countries and is currently unfolding in low-income countries .

Against this broad and sweeping background of structural transformation, what role will the AFS play as a source of employment and shared prosperity in the future? First, on-farm work will continue to be a major source of employment in poor countries. In low-income countries, as in much of Sub-Saharan Africa, a decrease in the share of the workforce employed in agriculture is still accompanied by an increase in agricultural employment in absolute terms. Given high population growth, the agricultural workforce is projected to continue swelling in the foreseeable future before it starts to decline . Therefore, in low-income countries, where most of the global agricultural workforce is still concentrated, the transition out of agriculture in the short run does not necessarily imply a smaller agricultural workforce overall. In these settings, the primary challenge is to improve the quality of farmers’ jobs, while also facilitating the transition out of agriculture. In many middle income countries, on the other hand, as well as historically in high income ones, the absolute number of agricultural workers has decreased over time,farm populations have “grayed,”and farm labor shortages in specific commodities at specific points in time have become a feature of the agricultural landscape. Second, agricultural labor productivity will continue to rise.The existence of a persistent and large productivity gap between non-agricultural and agricultural activities is received wisdom in development economics. It is often seen as proof that agriculture is intrinsically less productive and as suggestive that the policy solution for agricultural labor in the developing world lies in removing barriers that prevent people from exiting agriculture . Recent research, however, suggests that agricultural labor productivity is understated .

Using micro household data instead of national macro accounts, controlling for skill differences, and expressing productivity in terms of value per hour of labor , labor productivity in agriculture is not lower than in other sectors . This finding suggests that agriculture is not intrinsically less productive but, rather, underemployment in the sector is high, at least in the earlier stages of development. Underemployment is likely linked to the seasonal nature of agricultural production and high fertility rates . If the productivity gap is much smaller than generally assumed, a disproportionate focus on policies to remove barriers to sectoral or spatial migration, however well-intentioned, may be misplaced. In fact, if agricultural labor is only in surplus during the agricultural slack season , such policies may prove ineffective, or they may even exacerbate agricultural labor shortages during planting and harvesting . Improving agricultural productivity would enable a productive move out of agriculture, leaving a more productive agricultural labor force behind. This could be accomplished through the development of complementary activities during the slack season, such as double cropping through irrigation and mixed farming systems .These types of developments would maximize poverty reduction , in contrast to a scenario in which people leave agriculture due to distress following under investment. The road out of agriculture runs importantly through a path that increases labor productivity in agriculture. This agricultural job paradox remains underappreciated. It will eventually leave far fewer people in farming, but they will have better employment conditions, and there will be greater quantities of relatively cheap food available for those in the rest of the economy. This process is still not underway in earnest in many African low-income countries . Third, the successful exit of labor out of agriculture is intimately tied to a successful agricultural transformation . Food expenditure shares decline as incomes increase.

Food consumption patterns also change from primary staples to more protein- and micro-nutrient-rich diets .Eventually, societies tend to demand more processed and prepared foods; they may even develop food consumption patterns that involve eating as an “experience.” Societies become more dependent upon the downstream AFS as a result. This, in turn, opens up new employment opportunities off the farm in food processing, marketing, logistics, food retail, and food services. A fair number of farm workers who leave the farm remain within the broader food supply chain. In many low-income countries, off-farm work in the AFS already makes up about 25 to 33 percent of overall off-farm work . Off-farm AFS work is still relatively small as a share of total employment ; however, it rises to 25 percent when expressed in full-time equivalent employment as opposed to the number of people employed .The importance of off-farm employment in the overall AFS rises with income, from 9 percent of total AFS employment in Eastern and Southern Africa to 52 percent in Brazil and 80 percent in the United States . The share of off-farm AFS employment in total employment first rises and then falls . Asia’s experience shows that more successful countries develop their off-farm AFS as they pass through the structural transformation, and this leads to a more rapid reduction in poverty . In China, India, and Vietnam, the “supermarket revolution” has been more intense and rapid than in other developing regions, driven in part by private vertical coordination that has generated economic growth through the introduction of contracts, the creation of new credit and input markets, and tighter linkages between farmers and buyers . As agri-food systems develop, processing, logistics, and wholesale operations become more consolidated, incorporating advanced technologies in order to reduce costs and ensure timely availability of quality goods . In China and Vietnam, there has been an emerging shift from small- to large-scale processing, logistics, and storage,plant pot with drainage driven by large foreign investments in fixed plants . India and the Philippines enacted laws that prevented foreign direct investment from entering the retail food sector, leading to slower growth . Domestically funded market hubs have emerged in India, and they are expanding rapidly, effectively bringing modern markets to farmers .14 Non-farm AFS jobs are often also more easily accessible for women and poor workers leaving the farm, given their proximity and low entry requirements in terms of capital and skills.A large part of employment opportunities within the AFS is happening in secondary cities and towns , increasing their potential for poverty reduction, as most of the poor live in the rural hinterlands of these intermediate centers . Several recent case studies support the beneficial effects of the AFS and related development of agri-food value chains on labor force participation, income, working conditions , and, in some cases, smallholder participation in modern markets. Examples from the Future of Work in Agriculture conference include Sauer et al. for domestic food systems in Tanzania, Edwards for post farm oil-processing farms in Indonesia,and Maertens and Fabry for horticulture exports from Senegal to European markets.

The latter shows how vertical integration of production to meet the quality and standards requirements for European markets increased not only labor force participation, employment, and income in the source areas but also educational attainment and a reduction in fertility rates—evidence that the development of agri-export supply chains contributes to the broader socio-demographic transformation, in addition to reducing poverty. COVID-19, by disproportionately affecting small and medium enterprises, may jeopardize the potential of these beneficial effects. The downstream AFS has expanded rapidly in developing countries across the globe as part of the transformation of food markets. Even in Africa and Asia, consumers now purchase 80 percent of all food consumed, implying that food value chains provide 80 percent of all food consumed . As a result, food value chains in the developing world have become longer, stretching from rural to urban areas. Fragmented into many labor-intensive, informal, small and medium enterprises,AFS nodes often operate in clusters such as dense sets of food processing SMEs, scores of meal vendors at truck stops, and dense masses of wholesalers and retailers in public wholesale and wet markets . This concentration of activity is vulnerable to lock downs and other restrictions. Since the COVID-19 outbreak, food supply chain disruptions have been widely observed across the developing world. Many of the system’s smaller actors are under capitalized, informal, and ineligible for government support. They stand to suffer the most without adequate SME support, paving the way for accelerated consolidation and lower labor intensity in the mid and downstream AFS nodes. Fourth, fears of a mass exodus of African youth out of agriculture, disproportionate with normal patterns of youth transition out of agriculture as countries develop, appear to be overblown. Given Africa’s youth bulge, youth employment is especially high on the continent’s policy agenda. There is a perception that African youth may no longer be interested in agriculture . Exit from agriculture is a normal part of the structural transformation, and rural youth, in general, are less involved in agriculture than their older cohorts. It is mostly through youth that the structural transformation occurs: young people on average are more agile, educated, and adaptive to changing labor market conditions. Rural youth typically have less access to land than their parents did at the same age because many parents are not ready to transfer the farm and land rental markets are underdeveloped. A recent study of sectoral employment transitions in six African countries shows that both adults and youth are leaving agriculture, but not disproportionately relative to these countries’ level of development . In their 13-country study, after controlling for location and agricultural potential, Dolislager et al. find that youth do not spend fewer hours in on-farm work than older adults in general, and only younger adults spend less time in own farming . Youth appear to access off-farm AFS employment more easily than non-AFS jobs, especially wage work in urban and peri-urban zones. For rural youth, gaining access to opportunities both inside and outside the AFS is important, but promoting employment opportunities within the AFS is more likely to bring employment opportunities within reach of the rural poor. Fifth, sociodemographic changes, including decreasing fertility rates, rising rural schooling levels, and increasing participation of women in the rural workforce, further stimulate labor to move from farm to the non-farm AFS as well as to non-AFS jobs. Liu et al. , for example, find that, in Vietnam, the potential for agriculture to address youth unemployment is limited. However, as wages converge between rural and urban sectors, the rural economy is diversifying into non-farm activities, and access to education has become the key driver of improvements in rural household well-being. Gender differentiated preferences may affect the farm-nonfarm labor transition, as well. A field experiment in Ghana uncovered evidence that traditional gender roles lead to a division of labor that causes women to prefer investments in non-agricultural activities . This finding highlights the need to recognize women’s preference to diversify into non-farm activities in regions where gender roles preclude women from engaging in agricultural production.

By 2014, raspberries represented 33% of the county’s total value of production for all berries. In contrast, Monterey County raspberry production accounted for only 6% of the county’s total berry value. Blackberries have not been consistently reported as a separate category in archived statistical analyses, but instead were often included under the terms “bush- or miscellaneous berries”. Therefore, similar data for blackberry acreage and value of production cannot be reported here. However, between 1990 and 2010, Santa Cruz County agricultural commissioner crop reports reported an upward trend for the broad category with respect to acreage planted and value of production . In 2010, blackberries were promoted to a position of prominence in the report and shown as a separate statistic; at the same time, the miscellaneous berry category was shown to be very small indeed. Between 2010 and 2014, however, blackberry acreage and value of production leveled off and have shown only modest gains . This may be because there has been less emphasis on production and market research and promotion for blackberries than for strawberries or raspberries. No comparable data are available for Monterey County. The two counties have contributed significantly to California’s total berry sector: in 2014, area strawberry acreage represented 35% of the statewide total, 37% of the total tons produced and 38% of the total value of production . Area raspberry acreage represented 43% of the statewide total, 42% of the total tons produced and 39% of the total value of production. Comparable statewide statistics are not available for blackberries. County agricultural commissioners’ reports show that the majority of all berries produced in the two counties — up to 98% — are sold as fresh market fruit . In years with adverse production conditions or low prices, a higher percentage of the crop may be diverted to the freezer or processed products market. Fresh market fruit is handled and sold primarily through local grower-shippers; a much smaller share is sold directly to consumers through farmers markets, community supported agriculture operations,10 liter drainage collection pot farmstands and other direct and intermediated market channels such as restaurants, independent grocers and schools.

Arguably the most momentous shift in cultural practices for strawberries was the introduction of preplant soil fumigants, beginning with chloropicrin in the 1950s and methyl bromide in the 1960s. Fumigation is a soil disinfestation practice that improves plant productivity and helps with the management of arthropods, nematodes, weeds, soilborne fungi and other plant pathogens. Some of the most difficult to control pathogens include Verticillium dahliae, Fusarium spp. and Macrophomina phaesolina. Without soil fumigation, these pathogens have the potential to completely destroy strawberry plantings. Early on, when CP and MB were mixed and applied together, the synergistic effects allowed strawberries to be produced as an annual rather than a biennial crop, and to be grown continuously on the same land without rotation to another crop, resulting in an increase in annual strawberry acreage. The use of fumigants also led to higher and more predictable yields and fruit quality, and further enabled the development of more stable markets for strawberries . Yields for strawberries statewide increased from a range of 2 to 4 tons per acre prior to the introduction of soil fumigants to 16 tons per acre by 1969 . Additional cultural improvements included the development of both UC and proprietary strawberry varieties uniquely adapted to coastal production conditions. Varieties were bred, for example, for disease resistance, yield and market potential. Notable UC-bred strawberry varieties include Tufts , Pajaro, Douglas, Chandler, and Selva , Camarosa and Seascape , and Aromas, Albion and Monterey . Irrigation practices also evolved, shifting from furrow irrigation in the 1960s to drip irrigation in the 1980s, which led to further improvements in plant disease management and greater water use efficiency. These and other enhancements meant that by 2012, yields could exceed 35 tons per acre . More recently, the strawberry industry has focused on “fine-tuning” fertility and water management for more efficient resource use, along with additional yield and fruit quality improvements . The Santa Cruz–Monterey area is also recognized for its early experience with conversion of conventional strawberry production to organic management .

Organic strawberry production was shown to result in lower yields, which, when offset bypremium prices could potentially offer higher net returns to growers. The importance of crop rotation for disease management was not addressed in the initial study by Gliessman et al. but has since been the focus of additional research, as have more complete analyses of the economics of organic strawberry production .Most notably, a long-term research commitment has been made to determine organically acceptable disease management practices such as anaerobic soil disinfestation , the use of commercially available soil-applied biological organisms and the incorporation of soil amendments such as mustard seed and its derivatives. The area is now seen as a global leader in organic strawberry research, and in 2012 the first organic strawberry production manual was published by UC Agriculture and Natural Resources . Statistics documenting expansion of the organic strawberry industry over time are not available on a county-by-county basis, but statistics for California show prodigious growth in acreage and value of production: from $9.7 million in 2000 to $93.6 million in 2012, a 621% increase in real dollars . Research points to several factors that have spurred consumer demand for all berries. Berries contain bioactive compounds, including essential vitamins, minerals, fiber and antioxidants that contribute to healthy diets, and that help to reduce the risks associated with some chronic diseases and cancers . This information has been widely shared with consumers through, for example, government programs promoting healthy eating , and more generic berry promotion programs . Per capita consumption of fresh strawberries in the United States almost doubled from 1994 to 2014, increasing from 4.1 to 8.0 pounds . U.S. per capita consumption of fresh raspberries was small by comparison, at just 0.5 pounds in 2014.

Similar consumption data are not available for blackberries, but Cook notes that consumers generally view berries as complementary, and that sales for all berries have increased. Indeed, in 2014, berry sales increased 5.8% over 2013; berries were the number one produce category for U.S. grocery retailers, at $5.7 billion in annual sales . Some berry operations also benefit from their proximity to the area’s urban centers, which have sizeable cohorts of educated, high-income consumers who generally demonstrate an interest in health and wellness, local agriculture and fresh and organic products. In addition to the more traditional grower shipper and direct marketing channels, new technology-driven food marketing companies — virtual food hubs — have evolved to cater to this demographic. They promote the values of sustainable communities, local food economies and business integrity and transparency, all important attributes for new 21st century consumers . These companies form relationships with local growers, provide some technical and market support, and enhance sales and engagement with consumers. It is not yet clear what impacts these still-niche marketing businesses may have on the industry in total. However, growers have responded to the various health and market signals by ramping up production of both conventional and organic products, berries included. Specialists and farm advisors with UC Cooperative Extension have performed economic analyses for Santa Cruz and Monterey county fresh market berry crops for decades . The studies estimate production costs for a representative enterprise based on characteristics common to the area’s farms. Data are collected from established growers, input suppliers and other industry experts so that a diversity of operations and practices are taken into account. Since 1990, UCCE researchers have used a farm budget software program to analyze the data and present results in several formats detailing costs for cultural and harvest practices,hydroponic vertical garden monthly cash costs and business and investment overhead costs. The studies also include an analysis estimating net returns to growers for several yield and price scenarios. Representative costs for food safety and environmental quality programs have been incorporated into more recent studies as they have evolved to become standard business practices. The resulting production and economic information is specifically designed to assist growers, bankers, researchers and government agencies with business and policy decisions. The first economic analysis of fresh market strawberry production for Santa Cruz and Monterey counties was performed in 1969; at least one subsequent analysis has been conducted every decade since then.

Though the level of detail and data included in each study has changed over time, some interesting trends can be noted. Annual land rent climbed from $150 per acre in 1969 to $2,700 in 2014, representing 2.5% and 5.5% of total production costs, respectively. The cost of soil fumigation for conventional strawberry production increased from $350 per acre in 1969 to $3,302 in 2010, representing 5.5% and 6.9% of total production costs, respectively. Production year water use gradually decreased from 80 acre-inches per acre in 1969 to 36 acre-inches by 1996 as drip irrigation became the standard. The amount of water used to bring a crop to harvest has remained roughly the same since that time; however, growers and researchers continue to investigate methods to increase water use efficiency even further. In some areas, soil types and fields, growers have been able to reduce per acre water use by several acre-inches more . When the above costs and water usage are assessed on a per ton rather than a per acre basis, production practice cost increases are less notable, and water savings even greater. Labor-intensive practices such as hand weeding and harvest are consistently shown as costly line items relative to other operations. Representative yields for conventionally produced fresh market strawberries rose from 20 tons per acre in the 1969 study to 30 tons in 2010, an increase of 50%. Even higher yields are discussed for some varieties and production conditions; county production statistics confirm that higher yields are indeed possible . Representative yields for organic strawberries, studied over a much shorter time period, rose from 15 tons per acre in 2006 to 17 tons in 2014, an increase of 13%. As more research is directed towards organic agriculture in general and strawberries in particular, yields will likely increase even more with time. Recent efforts include improvements in cultivar breeding, cultural practices and disease management, especially soil pathogen management. The most recent economic analyses for conventional, second year conventional and organic strawberry production were performed in 2010, 2011 and 2014, respectively. Second year conventional strawberries, or those producing a crop for a second year after having produced the first without replanting, represent about 15% of the total strawberry acreage in the area. Similarities and differences in total, cultural and pest management costs for the three management approaches are shown in figures 1 to 3. Total costs for conventional strawberries were $47,882 per acre and include expenses for all practices from land preparation to harvest . For the second year conventional strawberry crop, total costs were lower at $32,798 per acre, reflecting a reduction in expenditures for land preparation and reduced harvest costs because of lower yield. For organic strawberries, total costs were $49,044 per acre, slightly higher than for conventional production, mostly due to higher soil fertility input costs. Harvest, a labor-intensive practice, clearly represents the lion’s share of total costs, at 58% in organic production, 60% in conventional production and 67% in second year conventional berries. Cultural costs represent 26% of total costs in the conventional and organic systems, but only 15% for second year strawberries because there were no associated planting costs, and because pest management costs were lower . Looking more closely at pest management, soil fumigation is the highest cost category for conventional production at $3,302 per acre, with weed control, another labor-intensive practice, the highest cost in second year and organic strawberries at $1,212 and $2,506 per acre, respectively . However, for organic strawberries the cost to control insects ran a close second at $2,488 per acre, which was dominated by control for lygus bug with a bug vacuum, and two-spotted spider mite with the release of predatory mites. By comparison, estimated costs for insect control in conventional strawberries were lower at $702 per acre and still lower at $579 in second year conventional berries. Raspberry and blackberry production were not routinely studied in years prior to 2003. Since then, several primocane-bearing raspberry and floricane-bearing blackberry cost and return analyses have been performed, with the most recent studies conducted in 2012 and 2013, respectively.

From a mechanistic perspective, tillage directly changes the mixing of soil and crop residue as well as soil structure, which then affect soil biogeochemistry and crop performance through various mechanistic pathways . As such, all other impacts on water, energy, carbon and nutrient cycles from tillage are then simulated as an emergent outcome in a coherent way. In contrast, some models represent the effect of tillage as direct modification of evaporation flux and decomposition rates based on multiplication factors derived from empirical data , which introduces excessive parametric uncertainty and strong context dependence on the empirical data used for model parameterization. Simulate as many measurable variables as we can, such that the model simulation can be thoroughly validated, and measurable constraints can be easily incorporated to further improve the model simulation. For example, as discussed in Section 2.3, GPP largely determines the carbon input to the soil , and crop yield are major carbon outputs from cropland, thus models with observational constraints from ground or satellite measured GPP and/or crop yield will unsurprisingly outperform models without such constraints. From a mass-balance perspective.GPP could serve as a particularly strong constraint for quantifying litter and root exudates, two critical carbon cycle components that have significant spatial heterogeneity but are hard to measure . Another example is the recent paradigm shift from using conceptual and non-measurable SOC pools to using measurable SOC fractions for SOC simulation in process-based models . SOM is a complex mixture of materials with heterogeneous origins, chemical compounds, microbial accessibility, and turnover rates . Physical fractionation of SOM differentiate particulate organic matter and mineral-associated organic matter ,danish trolley which all are measurable in the laboratory and have different characteristic residence times .

Beyond the change in total SOC, quantifying the changes and distributions of POM and MAOM may help address the permanence issue of soil carbon credit. However, most previous soil carbon models simulate SOM dynamics as non-measurable fluxes between conceptually defined and non-measurable soil carbon pools . Only if POM and MAOM are properly conceptualized and represented in the models can they be used to simulate the changes of those SOM fractions and can measured SOM fractionation data be used as direct constraints for models . Model-data fusion here refers to a set of techniques that reduce the uncertainty of states and parameters of process-based models or data-driven models using local information to obtain improved estimation of carbon outcomes . MDF also has the ability to evolve by incorporating new sensors/sensing data or new model developments to this framework. MDF is the core part of the “System-of-Systems” solution, with the basic rationale that available observations can only see part of a system, but a model that has the necessary processes can leverage available observations to help constrain the overall system and thus improve prediction accuracy for the processes that observations do not see. The most successful example of MDF is weather forecast – the integration of weather models with satellite observation – leading to its everyday use by different industries . MDF is not a new concept in earth science and ecological studies , as methods such as Bayesian Inference, Data Assimilation, and Emergent Constraint have been extensively used to improve various predictions at some sites, watersheds, or relatively coarse spatial grids ; however, the use of MDF for field-level carbon outcome quantification has many new requirements. We propose a new MDF approach to enable MDF being conducted at every individual field level, while also quantifying critical components of the carbon cycle to inform both science and management practices.

Essentially, for every field in a targeted region, cross-scale sensing provides high-resolution and spatially-explicit E, M, C observations, which are then used as either inputs or constraints for a model with necessary processes represented , and a set of location-specific parameters will be constrained for every field. By doing so, carbon outcome quantification allows the uncertainty quantification at every field, and model verification at every field is also made possible when extra carbon-related observations can be used as independent validation data. This MDF approach to enable high resolution and spatially-explicit model constraining represents a major advance over any of the existing quantification protocols that only require validation at the regional scale. This new MDF approach fulfills the model validation needed to test whether a model or a solution has true scalability, which was defined earlier as the ability of a model to perform robustly with accepted accuracy on all targeted fields. Only models that can reproduce the accepted ‘accuracy’ at any random fields can be used as an accepted MRV tool for agricultural carbon outcome quantification. Meanwhile, such a new MDF calls for new computational techniques, as the conventional implementation of MDF techniques would be too computationally expensive to handle the field-level MDF. Take Champaign county in Illinois alone as an example, it has ~12,000 fields in active cultivation; and the state of Illinois has ~1,000,000 fields in active cultivation; conducting intensive MDF using traditional implementation for each of these fields is infeasible. Moving to AI-based solutions and fully leveraging GPU computing to facilitate efficient and effective scale-up of the field-scale MDF over a broad region is the only path forward, which will be discussed further in Section 3.4. Scaling a System-of-Systems solution to all the individual fields with similar accuracy and at a low cost is a twofold problem: cross-scale sensing to generate rich E, M, C information for constraining various aspects of agricultural carbon cycles ; and scalable application of MDF over millions of individual fields .

To reduce the computation cost to scale up, both problems require the inclusion of AI and a transition from CPU-heavy to GPU-heavy models on super computing or cloud-computing platforms for massive deployment. Below we will specifically discuss three pathways to help realize the upscaling of MDF, spanning across a spectrum of different levels of integrating process based models with AI. Pathway 1: The most straightforward path to reduce model uncertainty is to use MDF to constrain model parameters. However, the high computational cost of parameter optimization limits the scaling of MDF. A feasible bypass without massive re-coding is to leverage deep learning algorithms and develop GPU-based surrogate models. Forward inference of deep neural network-based surrogates can be orders of magnitude faster than CPU-based process-based models, making them particularly suitable for parameter calibration . Successful applications have been reported in hydrologic and Earth system models , this strategy is also practiced in other complex systems such as agroecosystem and climate models . Traditional parameter optimization algorithms work by iteratively searching for the optimal parameter combination to minimize an objective function , but may get stuck at random local optima where multiple parameter combinations correspond to identical model outputs. If parameters are calibrated for individual pixels, this illposed issue may lead to a discrete spatial distribution of the target parameters. Recently, neural network-based parameter learning methods have demonstrated promising possibilities to address this issue without a searching procedure . For example,vertical aeroponic tower garden the differentiable parameter learning framework developed by Tsai et al. enables the inference of model parameters by an unsupervised parameter learning network, which was automatically constrained by the surrogate network to produce reasonable parameter combinations in the training phase. Compared to the traditional SCE-UA method in calibrating the Variable Infiltration Capacity model, the parameter learning network estimates physically more sensible parameter sets with continuous spatial patterns because the inputs of the parameter network are themselves spatially coherent. Although AI-based surrogate models provide a pathway for the MDF upscaling, the objectives of further research should not be limited to speeding up the parameter calibration procedure but to exploring generalized pathways for estimating interpretable and reasonable model parameters. Pathway 2: The second pathway is a hybrid modeling approach to integrate machine learning and mechanistic modeling in one integrated modeling system to achieve computational efficiency, prediction accuracy and model transferability. Knowledge Guided machine learning is one such approach that learns complex patterns from data while incorporating domain-specific knowledge, such as physical rules , causality and nature of variables , informed by process-based models .

Preliminary success has been achieved in many topics including stream flow prediction , lake phosphorus and temperature estimation , and GHG emission modeling . In particular, the KGML-ag model developed by Liu et al. incorporated knowledge from the ecosys model into a GRU model and outperformed both the ecosys model and pure GRU model in predicting the complex temporal dynamics of N2O fluxes . The expanded KGML-ag method for quantifying carbon budgets exhibited strong agreement with the NEE measurements obtained from 11 eddycovariance sites . Combining KGML with Meta-learning may increase model transferability by accelerating hyperparameter learnings that account for spatial heterogeneity . Despite this early success, efforts to develop hybrid models are still in its nascent stage. Scaling field-level KGML for carbon accounting across millions of fields would require innovative approaches to assimilate multimodal remote and insitu sensing data, possibly by assimilating these data via low dimensional embeddings to constrain neural networks. Future research should also address multi-objective learnings, because existing KGML models are mostly mono-objective and lack synergistic considerations for the coupling of soil biogeochemistry. Pathway 3: Fully upgrading existing agroecosystem models to GPUaccelerated systems necessitates intensive code redesign and rewrite, thus requiring longer coordinated efforts with dedicated funding support . Based on previous explorations for Earth System Models  and specific challenges in agricultural carbon outcome quantification , the ideal GPU-accelerated agroecosystem models should have the following characteristics: having the same or higher level of performance and interpretability as in the original model; working freely in the GPU environment and be flexible enough to adapt to hardware improvements; and enabling the assimilation of generic data ensemble from multiple sources with different scales for efficient training/validating/fine tuning and on-time correcting. Progress is faster in upgrading modules with relatively known physical rules, such as in the areas of climate and hydrology than in biogeochemistry or human disturbance . For example, previous efforts on rewriting domain-specific language to adapt the GPU-accelerated systems succeeded in weather modeling  and climate modeling . An extensive effort is currently underway to adapt DOE ESMD/E3SM with modern machine learning techniques to next-generation architectures that are capable of GPU computing and generic data assimilation . The recently proposed concept of neural earth system modeling , aiming for a deep and interpretable integration of AI into ESMs, might be the closest solution for upgrading agroecosystem models as well. One profound step for such upgrading is to replace every submodule of the process-based model with a ML surrogate, and to train those surrogates jointly with real world observations. However, proceeding in this direction needs to conquer the challenge of mapping highly non-linear processes involving partial differential equations with different coefficients at different spatial and temporal resolutions. One solution that has shown some early success in predicting global atmospheric circulations is Fourier Neural Operator , a neural network specifically designed for solving an entire family of PDEs by learning mappings between functions in infinite-dimensional spaces . However, FNO is only one kind of “black box” neutral solver for PDEs. To be adopted in agroecosystem simulations, FNO needs to combine with other machine learning models to consider the connections and heterogeneity in space and time, and needs knowledge-guided constraints to provide predictions following physical/biogeochemical rules. Model validation, a procedure to benchmark model simulation with independent, high-quality observational data, is the only way to build model fidelity. The new MDF approach of high resolution and spatially-explicit model constraining essentially proposes a more strict way to test model scalability, defined as the ability of a model to perform robustly with accepted accuracy on all targeted fields. “Scalability” of a model or a solution should not only be demonstrated by model performance at a limited number of sites with rich data, where extensive parameter calibration is allowed; a true test of model “scalability” should be also demonstrated at many random sites, where only limited measurements are available. The latter is what a real world application entails – we are required to quantify the carbon outcomes at any given field. To achieve the above goal to fully validate the model scalability, a three-tier validation approach is needed, and results from these three tiers should be reported to the community for fair and transparent comparison.

State land reform efforts also encouraged the deepening of monoculture in the Peloponnese. Two land reform laws, one in 1835 and another in 1871, were passed at moments of swelling demand for currants and enabled investors to plant new vineyards. After the revolution, land that was owned by the Ottoman state—which was most land—was transferred to ownership by the Greek government. The intention was to sell this land quickly, but the assassination of Kapodistrias put these plans on hold. Called the “national estates,” this land remained the property of the Greek state. Private cultivators were permitted to live on the national estates and work the land as their own, and instead of paying rent, they paid a tax to the Treasury called the “right of usufruct,” which amounted to 15% of the total output of the land worked.In the last quarter of the nineteenth century, a crisis in Western Europe caused a sudden spike in demand for Greek currants. Around 1863, the North American insect phylloxera vastatrix arrived in France aboard a steam ship. American vines had evolved an immunity to the aphid over centuries of coexistence, but phylloxera proved fatal to European vines, which had never been exposed to it. In addition to the rise of greenhouses and amateur entomologists in France and the UK, the main cause that enabled phylloxera to travel from America to Europe was the advent of new steam ships. By 1860, steam ships had improved dramatically from earlier models and could now cross the Atlantic in ten days, which was a short enough time for the phylloxera aphid to survive the journey.As a result of uncertainty and misinformation,aeroponic tower garden system phylloxera was allowed to spread slowly but widely throughout France.After the aphid was first positively identified in France in 1868, it spread throughout that country in the 1870s, devastating vineyards.

Even though the aphid had been identified, there was no known treatment. Despite the efforts to stop the spread of phylloxera through the use of flooding and the application of carbon bisulphide, the aphid continued to spread and to cause destruction in France and beyond.Phylloxera destroyed vineyards in sixty out of the seventy-five of the wine-growing provinces in France, and from 1869 to 1883, French wine production decreased by forty percent.By 1881, phylloxera had also been identified in the wine regions of Germany, Italy, Spain, Portugal, and Algeria.Phylloxera did not make it to the vineyards of southern Greece, and Greek cultivation rose to fill the vacuum created by vineyard collapse in Europe—in addition to the foreign demand for Greek currants for British puddings, there was now a demand for Greek currants for the raisin wine they could be used to make. Phylloxera had reduced French wine production by more than half, putting it well below the requirements of domestic demand, not to mention the requirements of the foreign demand for French wines. As a result, French consumers turned to making wine out of Greek currants, importing them cheaply from London since prices had fallen so low and making them into wine in the South of France.The Société Corinthienne in Marseilles was established to import currants from Greece to be processed into raisin wines.French currant imports continued to rise every year, and by 1889/1890, France imported more than 70,000 tons or about half of all of Greek currant production to convert into raisin wine for domestic consumption.Despite accounting for a minority of total land use, currants did account for the majority of the overall exports of Greece . Due to the increased relative profitability of currants, monoculture progressed and currant exports grew at the expense of other commodities. One scholar has called this period, from the 1860s to 1893, the “golden age” of the currant in Greece.During this time, currants were the majority of the overall exports of Greece. From 1850 on, they accounted for around half of the overall value of Greek exports, and in some years over 75%.

In the last quarter of the century, currant exports soared from 50,000 tons to 170,000 tons by 1900.While the rest of Europe was suffering the Great Depression of 1873–96, the Greek economy thrived.Despite the outsize role of currants in the Greek national economy, the state was not heavily involved in the currant industry. The state’s role was limited to imposing a tax on currants, and it occasionally intervened to negotiate a lower tariff in importing countries. Currant taxes remained the same from year to year—a 10% land tax and a 6% export duty, both collected at the customs office. In 1858, these taxes were fixed. For every 1,000 Venetian liters, the land tax was 10.50 drachmas, and the export duty was 5 drachmas.In Patras, the currant tax funded a wide array of projects, including public education, public welfare, public insurance, and university scholarships. Infrastructure in Patras, however, was not funded through taxes on currants, but through taxes on imports. Patras lacked a pier and a quay until 1840. These were constructed through a 0.5% tax on imports imposed in 1836, and from 1840–1869, these funds were used for repairs to the quay and to build wooden storage sheds.Toward the end of the century, big projects like the Athens to Patras railway and the Isthmus Canal were underwritten by the future revenue to be collected through the currant tax. Over the course of the nineteenth century, from the end of the Greek Revolution until 1893, currant cultivation spread through Greece in three distinct phases, punctuated by dips at “crisis” moments . In the first phase of expansion, from 1828 until 1852, the currant vineyards recovered from their destruction during the war, fueled by the continuing strength of the demand for currants from Britain. It took ten to twelve years for a currant vine to reach full productive maturity, and five to seven years before it started bearing any fruit at all.As a result, currant vineyards took a while to recover their pre-independence production. In 1828, because of the war, the Peloponnese was “a large stretch of uncultivated land.” The replanting of currant vineyards in the eparchy of Patras began in 1828 and was finished in 1847.82 While currant vineyards were being planted in Patras, they were also being planted all along the north coast of the Peloponnese, from Patras east to Corinth.

The continuing strength of the demand for currants in Britain made it more profitable to plant currants than it was to plant other crops. Tempted by higher prices and given the opportunity of a blank slate because of the destruction of the war, Greek peasants planted currants instead of food crops for household consumption. In 1829, the agronomist Christophoros Kontachis traveled the Peloponnese to teach peasants to grow potatoes. He wrote, “last February, while traveling the Peloponnese to teach potato cultivation, I saw many people in the region of Achaia planting currants, considering this plant more profitable than other products.”He observed that they were resistant to growing potatoes because it was much more profitable to grow currants. This first phase ended with the outbreak of the “vine sickness” of the early 1850s. This was caused by a fungus known as Uncinula necator, or Odium. This fungus covered the leaves, fruits,dutch buckets for sale and stems of grapevines with a powdery, white mildew. Odium was not just a problem for Greece—far from it. By 1852, the disease was endemic in vineyards all over Europe, Asia Minor, and North Africa. In Greece in 1852, the disease destroyed two thirds of the currant crop. From 1852 to 1855, currant production in Greece—and grape production in general in Greece and in many other countries—was effectively zero.In Greece, the Oidium crisis was compounded by the British blockade of Patras and other ports during the Crimean War from 1851 to 1853 and a rise in the price of wheat. As a result, the economy of the currant zone was very depressed during the 1850s. An indication of the suffering in Patras can be seen in the establishment of a foundling home in the city, and the number of foundlings increased from seven in 1852 to 48 in 1859.This crisis was overcome within a few years when a French botanist at Versailles developed a treatment. He discovered that dusting crops with a sulphur spray killed the fungus and protected vines from becoming infected. At this point, it became common practice in Greece and elsewhere to walk through the vineyards with spray cans, applying a thin spray of sulphur to protect the vines from Oidium . By the end of the decade, all vineyards were being treated in this way, and the Oidium pandemic was fought back.With the recovery from Oidium, Greece entered a second phase of expansion, lasting roughly from 1857 to 1878. The main impetus for growth during this period was the change in consumption patterns in Britain described above. The application of ring-cutting in the Peloponnese around the middle of the nineteenth century also enabled the currant zone to expand further south in the peninsula. Without the application of this technique, it was not possible to grow currants in soil that was too fertile. Before ring-cutting, attempts to transplant currant vines to the fertile plains of Ilia had failed because, “the currant vine, as soon as it was transplanted to rich and humid soils, turned wild and gave no fruit at all.”With ring-cutting, Ilia, which had been a center of cereal production, replaced cereals with currant vines and became the “capital of currant production.”The currant zone thus expanded south, but the currants produced south of the traditional currant-growing zone in Achaea were of an inferior quality.

The dryer soils of the northern Peloponnese produced sweeter fruit. Currants grown in Vostizza and Patras were classed as Α’ quality currants, and currants from other regions were Β’ or Γ’ quality. Nevertheless, because of the fertility of the soil, the quantity of production was much greater in the south.89 In the middle of the nineteenth century, for the first time since the sixteenth century, the center of Greek currant cultivation shifted from the Ionian Islands back to the Peloponnese. From the sixteenth century to 1847, over half of total Greek currant production came from the Ionian Islands of Kephalonia, Zakynthos, and Ithaki. In 1848, the Peloponnese finally overtook the Ionian Islands, and the North and West coasts of the Peloponnese became the center of currant cultivation. By 1870, production in the Peloponnese was almost 80% of overall Greek production. This is not to say that currant production in the Ionian Islands decreased; on the contrary, it also grew. However, production in the Peloponnese grew faster and eclipsed the islands.The final boost in the second phase of the extension of currant vineyards in the Peloponnese occurred after a political change that encouraged currant cultivation to spread even further south in the peninsula. After ring-cutting, the “age of pudding” in Britain, and improved steamship travel promoted the extension of vineyards south to Ilia, it was the land reform law of 1871, which sold the national estates to private land-owners, that allowed currant cultivation to spread south and for vineyards to colonize Messenia. The second phase of expansion stalled with yet another crisis. Responding to an everincreasing British demand for currants, Greek supply grew to the point that it outstripped demand, and Greece entered its first over-production crisis. This state of affairs was largely enabled by the land reform of 1871. In the years following the law, a large segment of the national estates in the Peloponnese were sold to private individuals and planted with currant vines. As mentioned above, it took six to seven years for new plantations to begin bearing fruit, so in 1877/1878, the market was overrun with a sudden flood of low-quality currants. Currant prices fell to all-time lows. In the spring of 1878, the price of currants on the London market barely covered the cost of shipping them from Greece. The Greek currant economy seemed to be on the verge of a crisis. Solutions were proposed by Greek ministers and currant merchants, including instituting a state monopoly on currants and restricting the planting of new vineyards. These plans received much opposition, and they were soon forgotten when rescue to the Greek crisis came from phylloxera and the sudden demand from France.91 The phylloxera crisis in Western Europe rescued Greece from the first over-production crisis. Under the influence of greatly increased global demand and the misfortune of their competitors, Greek currants in the Peloponnese became very profitable, and currant viticulture expanded in response.

To Lampe and Jackson, the Ottoman and Hapsburg empires exerted a greater influence on the Balkans from the sixteenth to the nineteenth centuries than did Northwestern European consumers or businessmen.Despite these and other criticisms, World Systems Analysis has left an indelible mark on the study of market integration in Southeastern Europe and the Eastern Mediterranean. The overall narrative of this process has remained largely unchallenged: over the course of the eighteenth and nineteenth centuries, growing foreign demand for Mediterranean agricultural products facilitated the integration of regions along the Mediterranean littoral into a larger market for goods and labor. This integration caused the states of the Mediterranean to develop in a subordinate—if not altogether dependent—position vis-à-vis Northwestern Europe. The terms “core” and “periphery,” moreover, are still widely used to characterize this unequal relationship, although the more precise terminology of World Systems Analysis, such as “semi-periphery” and “peripheralization,” have receded from use. Instead of “peripheralization,” with its Eurocentric and teleological connotations, this process may be referred to simply as “market integration.”The newer work from a world-systems perspective has attempted to move beyond teleological modernization frameworks. Recent scholarship on “working class cosmopolitanism” in Mediterranean port-cities, for example, utilizes world-systems narratives and terminology, but it conceives of class outside of a Marxian framework, and it also posits important cultural identities other than national ones. This literature shifts focus from the port-cities’ merchant bourgeoisies to their sailors, day laborers, outlaws, and prostitutes, arguing that they constituted a diverse “cosmopolitan” class.

Migration between port-cities in the Eastern Mediterranean created cultural identities that no longer exist and have receded from view because of the rise of national historiography—market integration and the consequent rise of the Mediterranean port cities not only created a non-Muslim bourgeoisie,hydroponic fodder system but it also created a lower class of cosmopolitans.Other world-system studies attempt to transcend the literature’s overwhelmingly urban focus, for example by studying the ways rural banditry helped incorporate the countryside into the world economy.This newer world-systems-inspired literature fits neatly with other historical approaches to the modern Mediterranean region. First, it fits surprisingly well with other economic historical approaches, such as the more classical and “cliometric” study of modern Mediterranean economies.These once-oppositional frameworks have converged—the Mediterranean was not fully dependent, and the post-Ottoman nation-states did not suffer from a failed modernity, but they did develop in a subordinate position vis-à-vis Northwestern Europe, and this was largely due to aspects of the international trade of agricultural commodities. Second, this literature fits well with cultural and intellectual historical approaches to the modern Mediterranean region, such as the study of modern Mediterranean diasporas and of political and intellectual networks.With respect to Greece specifically, the story of market integration with Western Europe begins in the second half of the eighteenth century. The main catalyst was the rise of Greek merchant houses which opened in all the major cities of Europe and the Mediterranean in the eighteenth century. The result was that Greeks in Ottoman port cities controlled a significant portion of the empire’s trade with Europe. This was further facilitated by the Treaty of Küçük Kaynarca, signed in 1774 between the Ottoman and Russian empires, which was interpreted to allow Orthodox Christians in the Ottoman Empire to sail under the Russian flag.

Over the course of the nineteenth century, market integration was further promoted by several forces, especially advances in technology such as steam ships, liberal trade policies in the UK, the establishment of an independent Greek nation-state in the 1830s that was able to trade more freely with the West, and industrialization in Western Europe, which caused an increase in aggregate demand for commodities produced in Greece and elsewhere. As a result of all these processes, over the course of the nineteenth century, there was a marked increase in the volume of trade between Greece and Western Europe.In the second half of the nineteenth century, this process of market integration accelerated to an even greater degree. Beginning around 1860, there was a sharp rise in global demand for agricultural products grown in the Mediterranean region, and the vast majority of nuts, citrus, and dried fruits consumed in Europe and North America came from Mediterranean Europe— Southern Spain specialized in raisins, for example, and Southern Italy in citrus and almonds. In the middle of the nineteenth century, demand for these and other Mediterranean agricultural products rose due to general demographic growth in importing countries and the growing prosperity of the middle class in Western Europe.At the same time, industrialization created an ever-growing need for cotton for the textile mills of England, and Britain’s colonies and trade associates in the Mediterranean felt the pull of this demand. As a result, production of these agricultural commodities in Mediterranean Europe intensified. In sum, for the Mediterranean in general and for Greece in particular, the focus of scholarship on market integration and the globalization of Mediterranean agricultural products has been on its social, economic, and political consequences. The environmental consequences and the effects on agricultural practice, however, are not well understood. While the sub-field of environmental history has enjoyed great success in other regions, above all in North America and Germany, there is no environmental history of modern Greece per se.

There is, however, great potential to construct an environmental history of globalization in nineteenth-century Greece by combining disparate approaches and putting them into conversation with environmental histories of other parts of the world in the nineteenth and twentieth centuries.These approaches include the literature on the economic history of Greece and the Mediterranean;the historical, geographical, anthropological, and archaeological literature on land use, historical demography, and agricultural practice in Greece and the Mediterranean; and historical ecologies of the Mediterranean.Scholarship on the Mediterranean has envisioned the region as a unit from antiquity to the early modern era. This literature has had difficulty, however, in dealing with the nineteenth and twentieth centuries. It is generally acknowledged that sometime in the nineteenth century, Mediterranean unity was destroyed by the fracturing of the region into nation-states and by the globalization of trade. As a result, scholarship divides the study of the Mediterranean in the nineteenth and twentieth centuries into the rival civilizational spheres of Europe and the Middle East. For the literature on the pre-modern Mediterranean, ecology and agricultural practice are often regarded as key commonalities—Mediterranean agriculture is understood as a series of integrated strategies developed in concert with the environment for making productive use of diverse micro-ecologies and for limiting the risk of subsistence failure. In this section, I adapt this model in order to apply it to the study of the nineteenth century. I contend that the agricultural system outlined in the literature on pre-modern Mediterranean agriculture and historical ecology was the norm in Greece and Mediterranean Europe generally at the beginning of the nineteenth century,fodder system and that it was transformed over the course of the century. In applying this model to the present study, I historicize “traditional” Mediterranean agricultural practice, arguing that it was not an unchanging structure, but a dynamic process that was influenced by a variety of factors, particularly economics, demography, and climate. The literature on the pre-modern Mediterranean is largely grounded in historical ecology, as studies of the Mediterranean in history identify it as a unit based either wholly or in part on environmental or ecological factors. One approach is to define the Mediterranean region as a unit based on a shared climate—the Mediterranean is the region with a “Mediterranean” climate, characterized by hot, dry summers and mild, wet winters.Other definitions rely on the areal extent of the production of certain crops associated with the region—the northern limit of the growth of the olive tree, for example, is offered as a border between Europe and the Mediterranean.Another approach which has gained in recent years employs the concept of “micro-ecologies” to describe the Mediterranean in history. This approach, particularly as elaborated by Horden and Purcell in their 2000 book Corrupting Sea, conceives of the premodern Mediterranean as a unit not because it is homogenous; on the contrary, the region is defined as such by its great internal diversity.This approach has attracted scholars studying the history of places along the Mediterranean littoral from antiquity to the early modern era.

The lands surrounding the Mediterranean Sea and the islands contained within it possess a myriad of physical features including Alpine mountains, arid deserts, lush forests, and volcanic islands, and the distance between two distinct ecologies can be very small. As Grove and Rackham write, “In Crete there is an immense contrast between the misty, well-vegetated rain-excess areas on the north sides of high mountains and the arid rain-shadows a few kilometers away on the south sides.”The result is that one slope of a snow-capped mountain is a desert, the other slope is a jungle, and at its base is a boggy marsh. The Mediterranean region is not unique for its ecological diversity and fragmented landscape, but it is exceptional for its degree of fragmentation as well as the degree of connectivity between fragmented landscapes. As one scholar has written, “Nowhere else is the weave of the world’s surface so fine.”Mediterranean micro-ecologies are understood to be shifting and unstable. Due to natural erosion, variations in precipitation, regular fires and occasional natural disasters, such as earthquakes and volcanic eruptions, micro-ecologies do not remain the same from year to year. They also transform due to changes in human interactions with the land.As a result of their differing productive strengths as well as their volatility from year to year, pre-modern Mediterranean micro-ecologies were highly interdependent. A single micro-ecology was unlikely to be able to support the various needs of its population, but various forms of connectivity are built into the landscape, the sea being the most important of these. This is a large part of what gave the Mediterranean its unity. It was very highly fragmented into small ecologies, the populations of these places needed products from other places in order to survive, and the sea and other forms of connectivity facilitated exchange between these micro-ecologies. In a Mediterranean region composed of shifting micro-ecologies, instability and uncertainty were built-in factors of life. The instability and uncertainty were caused above all by two forces: variable climate and variable markets. With respect to climate: from one year to the next, rainfall could vary dramatically. As a result, a given location might provide very productive agricultural land one year and be barren the next. The other factor that shifted from year to year and affected the characteristics of a micro-ecology is what Horden and Purcell call “its changing configuration within the web of interactions around it,”or what for the purposes of this study might more simply be called “markets.” Precipitation was variable, but so were the needs of the populations within a given micro-ecology. Moreover, precipitation and needs varied in neighboring micro-ecologies and in more distant ones that were nevertheless connected through exchange. All of these variables were relevant at the micro-scale to the productive capacities and the overall fate of a given locale from year to year. It was in this context that traditional Mediterranean agriculture took shape as a way to manage risk and ensure that subsistence needs were always met. As a result of the capricious Mediterranean climate and shifting interactions with other micro-regions, populations living in Greece had to be flexible in order to meet the needs of their own subsistence from year to year. In the words of Paul Halstead, “Each year the farmer may be aiming for a different production target, from a different area of land, with a different labour force and with the cushion of a greater or lesser amount of produce in store.”On the local scale, Greek populations adopted certain strategies in order to maximize their potential for meeting their subsistence needs as well as those of their families. The three over-arching strategies undertaken by Mediterranean populations in order to survive were “diversify, store, redistribute.”Diversification can be seen in every choice made by Greek populations to meet their subsistence needs. In terms of agricultural production, Greek populations knew that they could not rely on a single plot of land to meet the needs of their subsistence from year to year. As a result, they undertook strategies to diversify their production.

The more successful Turén farmers sought to diversify production to cope with price and yield fluctuations and also expanded into new areas to counter the loss of soil fertility the increasing chemical-dependent production system engendered . By 1990, the original colony had expanded from 15,000 to 250,000 hectares and had established a production system of rice, maize, sesame and sorghum, crops favorable to mechanization and that could feed into the agro-industrial system . Agricultural development, and the resultant growth in production of cereals and oilseeds, in Portuguesa between 1949-69 was considered a national agriculture ‘miracle’ as the government invested resources into irrigation projects, roads, windbreaks, housing and a rice processing plant that helped to solidify the new class of farmers in the area . However, while grower strategies of expansion and diversification were important for commercial farmers in Portuguesa, outcomes in the state varied. Successful commercial farmers in the Acarigua-Araure center grouped together in producer associations and used alternative sources of capital investment to expand into more profitable areas of the agroindustrial chain by developing processing plants for oilseed and cotton refining . Unlike the Acarigua- Araure growers, however, Turén producers didn’t have access to alternative financing to enable vertical integration, and although were able to expand and diversify production, became largely subordinated to the more powerful agro-industry sector as they assumed a role as producers of raw materials for processing centers . This dynamic intensified in the late 1970s and early 1980s as Venezuelan agriculture entered a crisis. A confluence of factors including reduced government subsidies and private investment in the sector, stagnant prices,hydroponic dutch buckets and the rapid increase of food imports contributed to a squeeze on the nation’s producers .

By 1983 vegetable production was 15% below 1977 levels, and the area under cultivation had fallen 25% . In the same time period, food imports rose from 35% to 65% of national consumption . Much of the disruption to the agriculture sector was due to OPEC’s—and by extension Venezuela’s—successful efforts to raise oil prices. The resultant influx of petro-dollars to Venezuela’s newly nationalized oil sector drove currency appreciation, which facilitated increased food imports and reduced the competitiveness of domestic producers. The crisis drove further mechanization and intensification in Portuguesa’s agricultural sector, as the state’s commercial elite saw increasing production as the solution to a context of stagnant prices coupled with rapidly rising costs of production . The agrarian malaise reflected the general political and economic crisis of the 1980s as oil prices dropped. The Venezuelan government implemented reforms to boost agricultural production, including deregulating controlled food prices, issuing of low-interest loans, increasing fertilizer subsidies, and mandating that commercial banks lend to a portion of their reserves to farmers . The policy prescriptions fed the so-called Venezuelan ‘agricultural miracle’ of 1983-87 that saw strong sectoral growth and production rises in a number of key crops. Maize, sorghum and cotton production levels doubled over 1983 levels . Continuing macroeconomic woes however pressured subsequent governments to accept orthodox conditionalities of the International Monetary Fund that began to restructure the economy at large and largely dismantled polices aimed at food self sufficiency by reducing agricultural price supports and input subsidies. The implementation of structural adjustment policies, however, resulted in severe social upheaval, including the 1989 Caracazo. The upswell of protest from Venezuela’s citizenry opened political space for the government to reinstate some subsidies to the agricultural sector. In sum, as the 20th century closed Portuguesa had been transformed into dominant agrarian player, with a vertically-integrated commercial agricultural sector.

With Acarigua-Araure serving as the agro-industrial core and as an important regional market for seeds, machinery and agricultural services in the state, Portuguesa functioned practically as an agrarian enclave economy as it became the premier agro-industrial center in the country . The success of the commercial sector was predicated on interventionist state policy that broke up landowner power, provided credit, input subsidies, infrastructure and technical support, and maintained government-protected, domestic markets . The emergent agro-industrial sector had little connection to the earlier agricultural export sector of coffee and cacao, although some traditional latifundio interests did evolve into commercial elite. The agrarian reform sector near agro-industrial commercial development was subordinated to the accumulation needs of the commercial sector. While commercial agriculture established itself in areas with well-developed and largely government-financed infrastructure much of the state remained largely untransformed. Agrarian development established two coexisting production systems: an agro-industrial model centered in the municipalities of Páez, Araure, Esteller, Turén and Ospino; and areas of continued peasant production, especially prevalent in Guanare, Guanarito and Sucre . The peasant sector in the immediate geographical path of commercial agriculture had been displaced and sometimes absorbed into the new industrial sector as labor, or had continued to function largely as before in areas further afield from Portuguesa’s agro-industrial corridors.Portuguesa’s commercial sector is concentrated along the number 5 highway, the major transportation artery in the area that links Portuguesa to the important commercial cities of Barquisiemto, Valencia and Caracas. Agro-industrial crop production is focused near the main transportation corridors while mostly small-scale coffee production is located primarily in the highland areas of Sucre, Ospino and Monseñor José Vicente de Unda municipalities.

Cattle ranching— primarily for milk production—remains in some savanna areas, particularly in low laying lands that seasonally flood and remain relatively far from infrastructure networks in Guanarito and Papelón. In 2001 Portuguesa accounted for 90.5% of domestic sesame production, 51% of rice, 41% of sorghum, 40% of corn and over 30% of sugarcane . In 2013, Portuguesa accounted for over half of all maize production in the country, producing 1,031,765 tons . Portuguesa is not a site of petroleum production or processing. Of theoretical note is that in the oil curse literature, oil development displaces agriculture in terms of share of national GDP, contributes to Dutch disease dynamics that favor imports over national production, and—at a regional level—can displace agriculture at specific sites of production.Yet, Portuguesa demonstrates—in areas with favorable conditions—agriculture can become a regionally dominant sector in particular historical contexts. According to Grinberg and Starosta , capitalist sectors in oil states are limited in their capital accumulation process by the nature of oil rent redistribution. While the capture oil rent allows for their reproduction on a domestic scale they are generally unable to compete in international markets . In Venezuela, a contingent of Portuguesa growers were successful in consolidating a dominant position in supplying domestic markets. Part of this success was also based in expanding vertically in domestic agro-industrial chains, and using smaller producers to help feed the local processing and packaging enterprises they now controlled. The issues of land reform and domestic food production have been prominent controversies within Venezuela in the Chavista period. The intense reaction of commercial grower associations to the 2001 Land Reform Law and its explicit calls for the elimination of Venezuela’s latifundia established an early context of conflict between agriculture elites and the state. The perceived attack on private property rights codified in the Land Reform Law has been cited as one of the primary drivers of sharpening opposition resistance to the Chavista government and of contributing to the 2002 coup de tat that briefly removed Chávez from power . The government’s anti-latifundia rhetoric was portrayed by government critics as generating class conflict, violence and sense of lawlessness in rural areas . Agriculture, food and land reform policies have, thus, served as important points of conflict between the Chavista government and its political opposition and cannot be separated from broader social conflict over the Chavista-era ‘revolutionary’ program. However,bato bucket conceptualizations of dynamics between the state and the commercial agriculture sector as primarily conflictive mask a set of policy relationships that are more ambivalent. A closer examination of policy dynamics reveal that state policies often support sectors of commercial agriculture and reinforce agribusiness socio-economic position in rural areas. Perhaps most salient issue in terms of conflict between commercial agriculture and the state is the threat of confiscation of land via the Land Reform Law. Indeed, the law was one of the most controversial components of the government’s 2001 reform package . Through 2013, 6,897,872 hectares have been recovered, and 11,901,752 hectares have been regularized by the state under the Land Reform Law .

Despite the quantity of land recovered by the state and political controversy and violence connected to the agrarian reform, the process of land expropriation has largely bypassed producers in much of the commercial agriculture sector. The relatively low land seizure pressure on commercial producers in Portuguesa results from government negotiations with estate owners, dynamics between state institutions and producers at the local level, and an increasing policy trend focused on maintaining agricultural production levels rather than on addressing levels of land inequality. It is difficult to ascertain how much land was seized by the government from private interests, especially on the level of individual states. At the time of writing, government data on land recovery and redistribution released by the MPPAT and INTI were national totals and did not break down numbers by individual states or municipalities. There were no available, reliable data on how many private estates in Portuguesa had been subject to recovery by the state or had been occupied by peasant groups. Commercial growers in Portuguesa, however, stated that the threat of expropriation was a central incentive to continue production in the face of low prices and other productive or profitability challenges . In Portuguesa, growers cited the cases of the 2,276 hectare Dos Caminos and the 1,779 hectare Palo Gordo estates recovered in 2012 by INTI as emblematic cases of seizures from landowners in the region. Negotiation with landowners for partial redistribution is often attractive for policymakers as it theoretically speeds up land redistribution and avoids drawn-out legal process and appeals. It also potentially diminishes opposition to reforms as landowners can receive payment for lands lying idle on estates, as under the Land Reform Law estate owners are entitled to compensation for seized lands. Oil revenue theoretically allows the government to pay market rates for seizures, giving it an advantage over more cash-poor countries attempting an agrarian reform that compensates landholders. It is unclear, however, to what degree compensation has been paid in the Venezuela land reform. A high-profile expropriation case involving estates owned by the British Vestey Group was resolved with the government and the company negotiating the transfer of two estates to the government in exchange for the retention of 8 other estates and a payment of £2.4 million . Yet there is no clear data on whether or not payment was delivered to landowners in the majority of cases of land recovery. Some seizures of sugar plantations in the state of Yaracuy, for example, were ultimately implemented under the rationale that private land titles were invalid due to the area being designated as an indigenous reserve before the establishment of the plantations . As the plantations occupied technically state land no indemnity was paid. Regardless, a strategy of negotiation with landowners by the state in policy implementation has implications for the nature of the reform. As in the case of many historical land reforms the division of estates with property owners can often leave the most productive land—with better soils and well-developed infrastructure—in the hands of landowners, which solidifies their relative position in the agriculture system even as it may diminish the size of absolute holdings. Redistribution pressure on private interests in the agrarian sector was also dependent on changing relationships between government institutions and commercial interests. In early periods of the reform government positions at the state or municipal level in some areas were in the hands of politicians that opposed the Land Reform Law. In Yaracuy and Cojedes states early land occupations by peasants were removed violently by state police forces under the control of opposition governors . The subsequent election of Chavista politicians to state-level offices was an important shift in local conditions that allowed peasant groups to re-occupy estates with a greatly reduced—although not entirely eliminated—threat of removal by state security forces . The control of key local offices by Chavista politicians or functionaries, however, did not ensure an even approach to policy implementation. Growers in Portuguesa cited that the changing of directors of MPPAT and INTI at the state level impacted how aggressively redistribution was promoted by the government.

The November 2016 state legalization of recreational cannabis prompted Siskiyou to examine a possible licensure and taxation system for local growers . Amidst sustained, vocal opposition, the proposal stalled for several reasons that further aggravated cultural and racial tensions: A key proponent of licensure was discovered to be running an unauthorized grow, three Hmong Americans died of carbon monoxide poisoning due to heaters in substandard housing, and a cannabis cultivation enterprise run by two Hmong-Americans attempted to bribe the sheriff. These developments were interpreted not as outcomes of restrictive regulations and criminalizing strategies, but as proof that, in the words of one supervisor, regulation was impossible until the county could “get a handle on the illegal side of things.” The sheriff encouraged this interpretation, arguing in an interview that statewide legalization was “just a shield that protects illegal marijuana” and efforts to regulate it would always be subverted by criminals. This anti-regulatory logic prevailed in August 2017 when the county placed a moratorium on cannabis commerce. Still, the sheriff argued for stronger powers, citing an “overwhelming number of cannabis cultivation sites,” which, according to the Sheriff’s Office, continued to “wreak … havoc [with] potentially catastrophic impacts” across the region . Just 1 month later, at the sheriff’s urging, the Siskiyou Board of Supervisors declared a “state of emergency” aimed at garnering new resources and alliances to address the cannabis cultivation problem. Soon, the Sheriff’s Office enlisted the National Guard, Cal Fire and the California Highway Patrol in enforcement efforts, and, by 2018, numerous other agencies joined,planting gutter including the Siskiyou County Animal Control Department, California Department of Toxic Substances Control, State Water Resources Control Board, California Department of Fish and Wildlife and a CDFA inspection station.

These alliances multiplied the civil and criminal charges cultivators might face . Ironically, California’s cannabis legalization has enabled a kind of multi-agency neoprohibitionism at the county level, one that reinforces older criminal responses with new civil-administrative strategies and authorities. The need to “get a handle” might be regarded as a temporary emergency measure, but it may also propagate new criminalizing methods and institutional configurations. The more enforcement occurs, the bigger the problem appears, requiring more resources and leading to a logic of escalation symmetrical to the much-critiqued War on Drugs . And the more cannabis cultivators are viewed as criminal, the less likely they are to be addressed as citizens, residents and farmers.Given concerns about biased county policy and enforcement, the Sheriff’s Office held the first Hmong American and Siskiyou County Leader Town Hall in May 2018 to “foster a closer, collaborative relationship with members of the Hmong-American community,” exchange information about Hmong and Siskiyou culture and educate attendees on county policies . According to public records, racial tensions surfaced at this meeting when some white participants expressed that “our county” had been “invaded” and that Hmong-Americans were not fitting into local cultural norms . Meeting leaders — both government officials and Hmong-Americans — however, identified cultural misunderstanding, rather than criminalization and racialized claims by whites on what constitutes local culture, as the core problem to be addressed. “Misunderstanding” was an inadequate framing, given that Hmong-Americans had attempted to make themselves understood by attending public meetings, forming advocacy groups, signing petitions, demanding interpreters and administrative hearings, and registering to vote since their arrival in Siskiyou. At the 2018 town hall, and numerous prior meetings, they emphasized their status as legitimate community members — veterans, citizens, consumers of county goods, local property owners, “good” growers and medical users — not nuisances, criminals, foreigners or outsiders.

In interviews and public forums many Hmong-American cultivators expressed a desire to comply with the rules. Their efforts, however, they said, were frustrated not only by linguistic and cultural differences, but also understaffed and underfunded permitting, licensing and community services agencies. Hmong-American cultivators routinely told us about their desires to settle down, build homes and plant other crops. “I’m growing watermelons, pumpkins and tomatoes,” one cultivator told us, but he was waiting for a permit to build his house, a process another interviewee reported took 3 years. Though the town hall meeting sought to address cultural misunderstanding, this framing overlooks how misunderstanding — of Hmong-Americans or cannabis producers generally — is produced by criminalizing enforcement practices. Properties given as gifts in the Hmong-American community were seen as evidence of criminal conspiracy, not generous family assistance; land financing networks evidenced drug trafficking organizations, not kin-based support and weak credit access; repetitive farm organization patterns suggested “organized crime” , not ethnic knowledge-sharing circuits. When Hmong-Americans, leery of engagement with government agencies and unfriendly civic venues, self-provisioned services, including firefighting teams, informal food markets and neighborhood watches, these actions were taken to confirm suspicions that they could not assimilate. Now that some Hmong-Americans are considering, or already are, moving away in response to county efforts, the sheriff’s prior description of them as temporary residents seems prophetically manufactured.Anti-cannabis pressure creates a precarious state of impermanence — a season’s crop might be destroyed, infrastructure confiscated and investments of limited resources lost at any moment, disallowing longer-term investments. The impermanence makes noncompliance and deleterious environmental and health effects more likely, thereby perpetuating perceptions of cannabis cultivators as nuisances and dangers.

As enforcement makes private land cultivation more risky, cultivators move “back up the hill,” namely onto ecologically sensitive public lands, thus substantiating characterizations of cannabis growers as criminal polluters. These stigmas even spread to county residents who do not grow cannabis themselves but if perceived to assist cannabis cultivation can face social sanctions. One agriculturalist reported receiving death threats after selling water to cannabis cultivators. Meanwhile, well-resourced cultivators have an advantage over small-scale producers. They can protect their crops from visibility and complaints by concealing them on large plots of land or inside physical infrastructures ; and for white growers there is the anonymity of not being marked as ethnically different and therefore subject to heightened scrutiny. Greater access to capital, land and racial privileges insulates some from visibility and criminalization, resulting in uneven development and disparities in California’s expanding cannabis industry. Additionally, jurisdictions like the Siskiyou municipalities of Mt. Shasta and Weed are welcoming regulated cannabis commerce, thus capitalizing on its expulsion from the rest of Siskiyou and benefiting entrepreneurs with social capital and network access to successfully navigate complex public regulatory systems.After a century of cannabis’s criminal exclusion in California, state voters have elected to integrate cannabis farmers into civil regulation. An important facet of evolving cannabis regulations is local determination. As one interviewee pointed out, a 1-acre farm might be permitted in rural San Joaquin County but would not make sense in downtown San Diego. Yet,gutter berries when cannabis cultivation is disqualified from consideration as agriculture by localities, as it has been in Siskiyou County, it can be substantively recriminalized and placed beyond the regulatory reach of civil institutions. Prohibitionist strategies that blur lines between civil and criminal enforcement lead to penetrating forms of visibility and vulnerability that produce inequity and disparity. The result, as this case illustrates, can be a narrow, exclusive definition of agriculture that affirms dominant notions of land use and community. The definition of cannabis cultivation as agriculture by the CDFA creates an opportunity for service providers and regulators — including agricultural institutions, public health departments and environmental agencies — to craft programs and policies that openly address the negative impacts of production. Owley advises that “if we treat cultivation of marijuana the same as we treat cultivation of other agricultural crops, we gain stricter regulation of the growing process, including limits on pesticide usage, water pollution, wetland conversion, air pollution, and local land-use laws.” Presently, however, many agencies are being enlisted in locally crafted criminalizing efforts, thus limiting their ability to work cooperatively with cultivators and address issues through customary civil abatement processes.

Though unregulated cannabis cultivation can pose threats to public health, safety and welfare, police enforcement is only one of many possible ways to address it. Siskiyou’s cannabis cultivators experience familiar agricultural challenges around access to land, water and credit. These challenges are amplified without technical assistance or institutional support. If recognized statewide as farmers, these cultivators would be better positioned to access agricultural training and support services, thus addressing ecological and social concerns around cannabis production. Additionally, new cannabis cultivators might be considered “beginning” farmers according to the CDFA, and minority farmers, including Hmong-Americans, who experience poverty at twice the national rate , would be considered “socially disadvantaged” under the California Farmer Equity Act of 2017 . Farmers with these designations would, in fact, be prioritized for technical assistance and support from farm service providers — if, that is, they were recognized as farmers. Uniformly treating cannabis cultivation as agriculture would also help enable the collection of accurate and robust data by researchers. This information base is necessary if agricultural institutions are to take an assistive and educational orientation toward cannabis farmers. Continued enforcement tactics that amplify distrust, frustration and confusion will further hinder data collection , leaving little basis to understand basic dynamics of complex, interdisciplinary systems like agriculture . In a criminalized situation, it is inevitable that information is metered and brokered by community leaders in ways that inhibit full understanding of cannabis cultivation. We suggest, for all these reasons, that a decisive break with enforcement-led, prohibitionist trajectories is needed and that agricultural institutions lead civil policy development and support farmers who cultivate cannabis. Agricultural service providers could play a leadership role in addressing the pressing needs of farmers — both those impacted by and engaging in cannabis cultivation. Yet, UC Agriculture and Natural Resources Cooperative Extension advisors, for instance, consistently report that they are currently prohibited from engaging with cannabis issues . Additionally, many county-based agricultural commissions, Siskiyou County’s included, feel that cannabis is not an agricultural enterprise and therefore do not see its cultivators as their clientele. Without leadership from agricultural institutions and agencies, the expanding cannabis cultivation industry is left to develop unevenly across the state — with wealthy private interests capitalizing in some locales while vulnerable and unregulated growers may retreat, to avoid criminalization, into ecologically sensitive areas. UC ANR and CDFA have an opportunity to fulfill their missions and facilitate, for a burgeoning farming population, greater parity in farmer rights, capacities and resource access.Organic strawberry production has become big business in California, generating more than $17 million in sales annually on over 1,200 acres—nearly 5% of California’s total strawberry acreage. But as producers have found, growing this specialty crop without conventional pesticides requires a new toolbox of pest and disease control techniques. For the past five years, researchers from the Center for Agroecology and Sustainable Food Systems have been refining the use of trap crops in organic strawberry systems as a way to limit damage from the western tarnished plant bug and boost populations of the pest’s natural enemies. A serious pest native to California’s central coast, WTPB feeds on developing strawberries, causing gnarled, “cat-faced” berries with enlarged, straw-colored seeds. These damaged fruit can’t be sold on the fresh market. Although some organically acceptable sprays exist to treat WTPB, they’re expensive and relatively ineffective.A broad range of winter weeds in central coastal California, including wild radish, mustards, chickweed, lupine and other legumes, and knotweed, offer a winter food source for WTPB. As the rainy season tapers off in the spring and wild vegetation dries out, the WTPB adults move to flowering crops, including strawberries, and begin feeding. Trap crops planted along the edges of crop fields or within the field have the potential to limit WTPB damage by offering the pests a food source they prefer over the crop itself. “That’s the definition of a trap crop—that it’s a preferred host or food source for the insect you’re targeting when compared with the main crop,” says Sean L. Swezey, the Center’s associate director, and director of the UC Sustainable Agriculture Research and Education Program. Trap crops can also serve as habitat for beneficial insects, which can supplement pest control efforts.Once attracted to the trap crop, pests must be managed so that they don’t eventually disperse into the fields and damage the crop you’re trying to protect.