Tag: agriculture

Most of the land trusts in our study were created through the grassroots efforts of a few community leaders or environmental activists, organizing effectively to pursue shared conservation goals. Other land trusts and open space districts originated more directly through local government action, including voter approval.Few of the established programs in California enjoy a steady revenue stream for building large agricultural easement portfolios. Programs with substantial acquisitions have relied largely on fluctuating and opportunistic revenue sources, primarily state government funds and foundation grants. They generally lack the certainty that an ongoing, dedicated local tax source could provide. As a result, most programs acquire easements in fits and starts, limiting their ability to plan and work quickly with interested landowners.Landowners cannot be compelled to enter into an easement transaction by government regulation or eminent domain; selling or donating an easement is entirely voluntary. This means that programs must rely on each landowner’s understanding of the technique and personal estimate of benefits and costs. For many landowners, easements are a foreign or confusing concept. They offer the unwelcome prospect of having less control over their land and create uncertainties about the long-term consequences for immediate heirs and later generations of owners. Landowners located near rapidly urbanizing areas are especially reluctant to consider the easement option, as they believe that they will be able to prosper by selling their parcels for residential or commercial development sometime in the future. Finally, even with a supply of willing landowners, there is the challenge of fitting the available properties into a program’s criteria for location,ebb and flow agricultural quality and easement price. Nonetheless, the successful programs demonstrate that a few early transactions with landowners respected in the local farm community can break the ice for subsequent deals .

Primarily because they are non-regulatory and voluntary, easements on farmland increasingly appeal to landowners and communities attempting to protect open space and agriculture. With about 120,000 farm acres covered statewide, agricultural easements have become an important farmland protection tool in California in less than two decades. A small number of local land trusts and open space districts, assisted by funding opportunities and entrepreneurship, have established successful programs. Yet the active programs operate in only a minority of California’s major agricultural counties. Many of these areas lack easement programs because of the absence of citizen interest and mobilization combined with local government inaction. Most established programs also are limited in their easement acquisitions, largely because of unsteady revenues, limited entrepreneurship and reluctant landowners. Undoubtedly, the few successful programs will continue to grow and expand their easement holdings. But expanding agricultural easements to major agricultural regions is the key to making optimal use of the technique in California.Introductions of non-indigenous species of plants, animals, and microbes cause significant ecological and economic damage worldwide. A 1993 report from the Office of Technology Assessment estimates the monetary costs associated with biological invasions in the US alone is between $4.7 and $6.5 billion annually ; subsequent research revises that estimate for the US upward to over a hundred billion dollars a year . Moreover, since these estimates derive mostly from costs calculated for agriculture1 , there is consensus that these numbers are lower bounds. There are numerous pathways by which non-indigenous species enter a country: contaminated agricultural products, timber, potted plants, ballast water and packing materials are primary conduits for unintentional introductions2. We focus on introductions facilitated by commodities trade and explore how changes in agricultural protection affect patterns of trade and subsequent damage to local agricultural and ecological systems from exotic species introductions. In our stochastic model, exotic species introductions, success, and damage are functions of the volume of trade and agricultural production.

The model is coupled with results from international trade theory that link volumes of production and trade to agricultural policies such as output subsidies. This simple structure generates several compelling insights. First, we show that increases in agricultural subsidies may improve overall ecosystem health despite common opposition to agricultural protectionism by environmental advocates. This arises because protectionist trade policies in agriculture importing countries reduces imports, often from species-rich tropical regions, such that the rate of exotic species introductions will likely fall with reduced subsidies. Second, we establish that crop damages are a poor proxy for overall damages associated with biological invasions. Crop damage arising from biological invasions may rise as a result of increased protectionism, either because there are more crops available to be damaged or because there is more agricultural land available on which non-native species can gain a foothold. But because increased protectionism will reduce the volume of imports in agriculture importing countries, ecological—and hence total—invasion-related damage may nonetheless fall. Third, we argue that the ecological impacts of increasing agricultural subsidies may be markedly different for agriculture exporting versus agriculture importing countries. For countries that initially export agricultural products, increases in production subsidies will lead to an increase in both the volume of agricultural output and in the volume of trade, with unambiguously negative consequences for overall ecological health. In sum, the ecological consequences of raising agricultural subsidies are reversed in agriculture importing countries. In section 2 we discuss the relevant economic and ecological literatures. We then describe our model in section 3, derive results in section 4, and briefly conclude in section 5. Ecologists have studied the consequences of invasive species extensively; see Drake et al. , di Castri , Parker et al. , and Shogren for overviews. This research has established several patterns governing successful exotic species introductions.

For example, successfully introduced exotic species tend to be native to nonisolated habitats within continents and their success is enhanced with the similarity in physical environments between the original and exotic locations . Furthermore, species that inhabit disturbed environments tend to be successful at invading human-modified environments . These and other empirical observations suggest that predictions of the frequency and severity of exotic species introductions can be made on the basis of factors such as similarity in physical environments between trading partners, trade volume, and the extent to which the home country modifies its natural environment. Despite the extensive study of the ecological impacts of non-indigenous species, rigorous economic treatment of the problem is lacking. The little attention paid by economists to the problem of invasive species has focused largely on case studies and analysis of control and risk reduction methods . With the exception of Dalmazzone , none explicitly incorporate the role of commodity trade in their analysis. Using a linear regression model, Dalmazzone finds a strong, positive and statistically significant relationship between the ratio of exotic to native species in a region and both its GDP/capita and its population density. Indicators of disturbance such as percentage of land devoted to agriculture and pasture are also positively correlated . Dalmazzone finds weaker evidence of a link between susceptibility to biological invasions and engagement in trade: although she finds a negative and statistically significant relationship between import duties and presence of non-native species, the influence of other measure of openness such as trade as a percentage of GDP, volume of merchandise imports and tourism are all statistically insignificant. We believe these results underplay the importance of trade volumes for rates of exotic species introduction. Given the biological rules of thumb governing invasions, a superior econometric specification would decompose imports by type and country of origin, as recognized by Dalmazzone. Moreover, we believe empirical testing would benefit from a more thorough understanding of the mechanisms in which trade policies and flows affect introduction and damage rates. The present paper serves as a first pass at establishing these relationships theoretically. We explore the effects of agricultural protectionism,greenhouse benches via an increase in subsidies to domestic agricultural producers, on expected damage arising from biological invasions. It is shown that the magnitude of change in expected damage depend critically on two things: the responsiveness of damages to changes in agricultural output and the response of imports to agricultural subsidies. We show that offering subsidies in an agriculture importing country will reduce both its rate of introductions and the ecological damage caused by the introductions. We further demonstrate that changes in crop damage are a misleading proxy for the effects of protectionist policy on ecological and total damages arising from biological invasions. This latter claim is particularly important if we believe pecuniary losses to agricultural production are more easily observed than ecological damage from exotic pests and hence form the basis for policy decisions.

Proposition 1 makes the simple point that increased support for Home’s agriculture industry may reduce the rate at which exotic species are introduced because of the effects agricultural subsidies have on the volume of trade. For countries that import agricultural goods, production subsidies lead increased output of locally produced agricultural goods to displace imports, thereby reducing the overall volume of trade as the country moves toward self-sufficiency. As reduced volume of trade reduces the size of the platform for non-native species introductions into a country, the expected rate of introductions N, and consequently the number of non-native species that take hold J, is thereby reduced. Alternately, if a country instead initially exports agricultural goods, an increase in S raises the volume of trade since it induces greater agricultural output, exports of which finance greater imports of manufactured goods. Although there is a tendency to equate species introductions with imports of agricultural goods, trade in non-agricultural goods also frequently serves as a conduit for biological introductions, either through contaminated ballast water from ships, or infestations of packing materials and manufactured goods themselves. It is possible that λ may depend differently on imports of different types—we abstract from this issue in the interest of simplicity—nonetheless the larger volume of trade arising from subsidies in agriculture exporting countries increases the platform for introductions and so raises the expected values of N and J. Some simple interpretations of these classifications are useful at this point. Damages arising from loss of crops —either through infiltration of crop and pasture land by weeds or predation on crops and livestock by pests— increase as the level of agricultural activity increases. Commonly referred to as crop damage, these types fall under the definition of Augmented damage. Other types of invasion related damage are unlikely to depend directly on the level of agricultural activity. Introductions affecting marine and aquatic systems are good examples of this: invading mollusks foul water intake systems at power generation facilities; introduced fish out compete native species, creating losses to recreational activities such as sport fishing. In addition, there are numerous examples of exotic species displacing native species, with consequences for non-monetized assets such as ecosystem health and biodiversity. These examples meet the definition of Neutral damage. In subsequent discussion we will also refer to these types as ecological damage. If instead introduction rates are sufficiently sensitive to the volume of trade, then an increase in agricultural subsidies may instead reduce expected invasion related damage. This latter possibility raises an interesting problem. Since Neutral and Augmented type damages may change in different directions following an alteration in agricultural policy, then estimates of invasion related damage that are based on one type of damage serve as poor—even misleading—indicators of total damage. As noted in the introduction, most real-world estimates of invasion related damage derive predominately from estimates of damage to crops and livestock. However, as proposition 2 indicates, crop damage may be increasing while Neutral and Diminished damages, and hence total damages, are decreasing. This insight confirms our earlier conjecture: economic measures of crop damage are a misleading indicator of total damages arising from biological invasions. For the policy change considered here, an increase in the agricultural output subsidy S changes in crop damage overestimate changes in total damage, and may indicate an increase in total damage even when total damage is in fact declining. As outlined in proposition 3, the effects on an increase in S on damages in an agricultural exporter differ from the effects felt by an importer. Again higher S spurs local agricultural production, however for an agricultural exporter this finances greater imports.

Therefore, our results agree with the existing literature, which suggests that old expenditures impact current productivity positively, and their exclusion tells us only a partial story. The coefficients we have obtained in this study indicate that there is room for improvement in extension research and outreach, and that introduction of new research-based knowledge and technology improves productivity. Results also suggest that primary-occupation farmers may be less efficient than those who are able to maintain more than one profession. Efforts could be focused towards improving any existing gaps in efficiency among farmers in different counties.The results of our analysis can guide policymakers during a period of political pressure to reduce public spending for agricultural extension in the state. The county fixed effects results allow a more targeted policy intervention on higher and lower performing regions .By controlling for individual county and fixed-year effects that may be driving productivity in that county, we find that some of the major agricultural counties in California record high positive impacts of UCCE expenditures stock. Out of the 50 county offices in our study, we observe that UCCE expenditures stock has a significant impact on 21 counties for all values of knowledge depreciation. We observe a statistically significant negative impact on a few counties, such as Amador, Calaveras, Humboldt-Del Norte, Modoc, and Siskiyou. For two counties, the impact is not statistically different from 0. In terms of policy, these coefficients can be used as reference points for allocating budgets to different counties. Extension efforts could be targeted to the counties with inconclusive or negative impacts. Monetary impact of cutbacks on county productivity could also be calculated, using the estimates of extension expenditures in this paper. The analysis driven by county performance helps design policies with heterogenous focus, which has been more relevant when public funds have to be allocated among heterogeneous performing recipients of these funds. And finally, as shown in Section 5.3 extension introduces substitutability of traditional inputs with extension knowledge so that higher expenditure on extension in some of the lower-performing counties can substitute for other traditional inputs, dutch buckets for sale which may be scarce in supply.

In particular, our analysis highlighted and measured substitution of extension knowledge for labor and chemicals.Both biodiversity and the human activities that threaten it are unevenly distributed around the globe. Thus, evaluating whether they are spatially congruent and choosing the best areas for conservation actions given the distribution of these conflicts are central problems in conservation bio-geography . The magnitude of the current biodiversity crisis, coupled with the limited resources available for protecting biodiversity, implies that prioritization is unavoidable. Spatial prioritization seeks to identify the areas that are likely to yield the best benefits for biodiversity given a particular conservation investment. It may be applied at a variety of scales, including global , regional , national and sub-national levels. Spatial conservation prioritization analyses can be based solely on the distribution of the biological features to be protected . Alternatively, prioritization analyses can include socioeconomic variables that represent threats to biodiversity or opportunities for conservation, such as human population density, land cost and land use . Agriculture is the human activity that represents the main threat to the environment . It constitutes the largest land use on the planet, using 38% of Earth’s ice-free land surface and 70% of global human freshwater uptake. Food production accounts for 19% of Earth’s net primary productivity and 30-35% of global greenhouse gases, with direct impacts on biodiversity . The burden on the environment may be higher in the future as the human population is expected to increase to more than 10 billion by 2050 . Moreover, a billion people are currently chronically malnourished as a result of lack of access to food . Given the value of biodiversity for human well-being , understanding the potential impacts of future agricultural expansion on biodiversity is a key issue for humanity. The general aim of my PhD thesis was to evaluate the potential impact of agricultural expansion on biodiversity conservation during the 21st century. Specifically, I evaluated four interrelated issues: conservation conflict between agricultural expansion and the global biodiversity conservation priorities and the Brazilian system of protected areas ; the effect of incorporating agricultural expansion data into spatial prioritization models for the conservation of world carnivores ; and the benefits of a globalized conservation strategy for food production and for biodiversity conservation . The impact of future socioeconomic development pathways, including land-use trends, on biodiversity can be accessed by means of quantitative scenarios . For all analyses presented here, I obtained future scenarios of agricultural expansion from land cover maps produced by the Integrated Model to Assess the Global Environment .

IMAGE forecasts, at a resolution of 0.5° × 0.5°, the number of years that each area will be cultivated during the 21st century for six socioeconomic scenarios . For chapter IV, I also included an estimation of potential agricultural productivity in each grid cell, based on climate, relief, soil constraints and irrigation impact . For the first chapter, I overlaid the spatial polygons of the Global Biodiversity Conservation Priorities onto a grid with a spatial resolution of 0.5° × 0.5°. I tested whether areas defined by their higher vulnerability were more affected by agriculture in the year 2000. The opposite was expected for areas with low vulnerability . I also tested whether these priority areas would be more affected by agricultural expansion during the 21st century than expected by chance . To address the aims of chapter II, I overlaid the IMAGE’s land-use model with Brazilian protected areas to calculate the conflict between these two land uses. I obtained Brazilian protected areas’ polygons from the World Database of Protected Area . I also included 10 km buffers around each protected-area polygon to represent the legal buffer zone usually used in Brazil, which is an area where human activity is restricted. I then tested whether these areas were more affected in the present and in the future than expected by chance. Additionally, I tested whether there was difference between the integral protection protected areas and sustainable use protected areas . In both chapters I and II, I evaluated the probability of such conflicts to be found by chance using spatial randomization tests developed in R , considering 1000 iterations . To meet the objectives of chapters III and IV, I performed global spatial conservation prioritization using Zonation . Zonation’s algorithm provides a nested hierarchical ranking of the sites, maximizing the representation of species’ distributions. To define the ranking of importance of sites for conservation, Zonation analyses can also incorporate costs such as potential agricultural production. For all prioritization analyses, I defined the target proportion of areas to be protected as 17%, following the Convention on Biological Diversity , which proposed this percentage as the goal to be met by 2020. I obtained information about mammal species’ distributions from the International Union for Conservation of Nature’s Red List of Endangered Species. I overlaid the spatial polygons onto a grid with a spatial resolution of 0.5° × 0.5°. For chapter III, I focused on 245 terrestrial carnivore species. In chapter IV, I used 5216 terrestrial mammals. These taxonomic groups have been the focus of many conservation programs and they are often considered to represent a potential surrogate for other taxonomic groups . To test whether there is a spatial conflict between the global carnivore conservation solutions obtained in chapter III and the agricultural expansion, I performed spatial correlation analyses using the Spatial Analysis in Macroecology software .

The objectives of chapter IV were achieved by defining global conservation priorities considering three levels of political integration: individual countries, regions , and globalized . I also evaluated the effect of considering, or not, agricultural costs for spatial conservation prioritization. The different conservation solutions were evaluated in terms of the relative amount of food production lost by setting aside sites for conservation and the representation of the geographic distribution of species within those sites. I also evaluated whether the most underdeveloped countries would be subject to higher losses in food production under the global strategy. For this, I correlated the percentage of food production and area lost to sparing land for biodiversity conservation with three development indicators: the Human Development Index , the per-capita gross domestic product , and the percentage of GDP added by agriculture . I found that reactive global biodiversity priorities had about 49% of their area impacted by agriculture in the year 2000 . Conversely, proactive schemes had a low intersection with the agricultural distribution . By the end of the 21st century, there will be an overall increase in world agricultural area from 26.5% of the analyzed area in 2000 to 34.6% in 2100, according to IMAGE, and the difference between the proactive and reactive schemes is predicted to hold true. However, High Biodiversity Wilderness Areas, a proactive scheme,hydroponic net pots is predicted to suffer agricultural impact similar to the reactive schemes, with 73.5% of its area affected, if the worst-case scenarios are realized . In Brazil, a megadiverse country in which agribusiness is the pillar of economy, agricultural expansion is a major conservation concern . According to IMAGE, agricultural land use represented 22% of Brazilian land coverage in 2000 and is predicted to increase up to 40% by 2100, according to a business-as-usual scenario. Moreover, the percentage of protected areas affected is predicted to increase from 11% to 30%, with no difference between IPPAs and SUPAs . I found spatial conflicts between the best areas for terrestrial carnivore conservation and agricultural expansion in the 21st century . These conflicts were alleviated when I incorporated agricultural expansion information into the spatial prioritization process . Nevertheless, accounting for agricultural expansion resulted in a lower representation of species’ geographical ranges: the average proportion of represented ranges was reduced from 58% to 32%. This reduction affected mainly those species with small geographic distributions. In addition, the best solution for global carnivore conservation changed from a spatial distribution closer to that of the reactive global conservation priority schemes to one more like proactive ones. Looking at the impact of globalization for conservation and food production, I found that combining the use of agricultural expansion data and integrating countries in a globalized conservation blueprint to meet the 17% target for terrestrial protected areas, resulted in a 78% reduction in the costs of food production . Furthermore, this globalized conservation approach represented an increase of 30% in the representation of the species in the protected areas network.

The regional-scale conservation solution resulted in similar losses in food production, compared to the globalized solution, and an increase of 17.5% in terms of representation of mammals’ geographical ranges .Conservation actions in the different areas of the world should be planned according to the expected agricultural expansion in the 21st century. Some areas can hold mega-reserves , while other areas should focus on the development of wildlife-friendly agricultural practices. Within Brazil, my findings suggest that the risk of agricultural expansion should be included in the management of protected areas and associated buffer zones. Globally, conservation actions for carnivores should consider agricultural expansion because this may significantly influence the distribution of areas where conservation actions could be more effective in the future . The regional scale may represent an intermediate step towards the global integration. Economic agreements may evolve to common conservation policies, since this has already been done in the European Union by means of the Natura 2000 network . By comparing differences in the distribution of protected areas among countries in the different scenarios, I found that the poorest countries will not be negatively affected by participating in this globalized conservation blueprint. However, the particular cases in which poor countries would be impaired in their development process should be a focus of compensatory policies in order to guarantee the participation of these countries within the global approach. Moreover, such compensatory policies may help to overcome socioeconomic problems such as poverty and inequality, which are known to be detrimental to the success of conservation actions . Feeding an increasing human population, with rising per-capita consumption, while managing the environmental impacts of agriculture, is one of the greatest challenges for global policy. In my thesis, I demonstrated that agricultural expansion will continue to represent an important threat to biodiversity throughout the 21st century. Reducing food waste, increasing agricultural resource efficiency, closing yield gaps, and fostering organic agriculture are tools available for solving this challenge .

In the regions affected by Human Immunod efficiency Virus / Acquired Immune Deficiency Syndrome , prime-age adult mortality negatively affects household welfare by decreasing household income and consumption. Previous studies on the effects of prime-age adult mortality on household agricultural production show that the mortality decreases household size and productive assets such as land and livestock. In this study, we further ask whether prime-age adult mortality due to HIV/AIDS decreases the endowment of knowledge for agricultural production in Kagera, Tanzania, reducing total factor productivity. Equivalently, we ask whether prime-age adult mortality due to HIV/AIDS destroys household agricultural production by magnitude beyond the decreases in observed productive assets such as household members, land, and livestock. We also quantify how much decreased TFP growth contributes to the decrease in long-term household agricultural income growth compared to the decreased accumulation of each productive asset. Kagera was estimated to be one of the regions in Tanzania most affected by the HIV/AIDS epidemic , Beegle. Kagera is also the region where AIDS cases were reported first in hospitals in Tanzania. In 1983, the first 3 AIDS cases were reported and the number of cases increased rapidly to 5,116 cases in 1994. On the other hand, the share of reported AIDS cases in Kagera to Tanzania decreased from 100% in 1983 to 10% in 1994. In 2003, the percentage of HIV positive in Kagera among age 15-49 is 3.7% while the figure in Tanzania is 7.0% and thus HIV/AIDS pandemic in Kagera has been alleviated compared to other regions in Tanzania. We use the Kagera Health and Development Survey which collects the detailed information on households in Kagera in 1991-94 and 2003. The survey samples households hit by prime-age adult mortality more than households without the mortality and the data allow us to study the long-term effects of prime-age adult mortality on agricultural production. In the data, 36.7% of prime-age adult mortality is considered to be due to HIV/AIDS by deceased individuals’ families.

We will focus on agricultural production among other income generating activities and we will study the effects of prime-age adult mortality on agricultural production in the region. Agriculture is the major income source in Kagera and also in Tanzania. In Kagera, 85% of household heads engage in agriculture in 2000/01 while 70% in Tanzania , Tanzania NBS. In Kagera,grow lights households engage in subsistence and traditional agriculture. Male adult members produce coffee and banana with or without cattle manure. Female adult members produce crops such as maize and yams mainly for own consumption.As shown below, households hit by prime-age adult mortality between 1990 and 2003 have less increase in household members by 1 person from 1991 and 2003 than households without the mortality.They also accumulate less other productive assets; land and livestock. As a consequence, their agricultural income growth is also smaller. However, we do not find such clear differences in per capita asset accumulation and income growth between households with prime-age adult mortality and those without it. In order to explore the effects of the mortality on agricultural production more, we will study the difference in TFP growth. We study the hypothesis that a household hit by the mortality cannot increase TFP as much as a household not hit by it. We also decompose agricultural income growth into the contribution of the accumulation of each productive asset and TFP growth and compare the differences in those factors between households with and without the mortality. The remainder of this paper is organized as follows. Section 2 reviews the previous studies on the effects of prime-age adult mortality on households’ welfare based on household level micro data and the differences between the previous studies and this study. Section 3 outlines our conceptual model, hypothesis, and framework of empirical methods. Section 4 explains the characteristics of the original data, especially with respect to prime-age adult mortality, how we construct our data for the analysis from the original KHDS data, and discuss the relevancy of our specification of the model to study the data. Our empirical methods are explained in more details in Section 5 and the empirical results are shown and discussed in Section 6. Section 7 concludes this paper.Whether and how much HIV/AIDS epidemic affects a household welfare is the important topic. We can categorize the literature of the effects of prime-age mortality due to HIV/AIDS on household welfare into consumption studies and production studies. Beegle, de Weerdt and Dercon studies the effects of prime-age mortality on long-term consumption growth based on KHDS.

Their regression equations have change in logarithm of per capita consumption from 1991 to 2003 as the dependent variable and dummy variables for deaths as explanatory variables. They use household fixed effects methods in order to control unobserved time-invariant characteristics and relax the endogeneity and self-selection problem of HIV/AIDS as other previous studies based on panel data do. They take into account which year each death occurred by using dummy variables for deaths in 1991-1995, 1996-1999, and 2000-2004. Their results show that the coefficients of dummy variables for deaths are negative but only dummy variables for deaths in 2000-2004 are statistically significantly different from zero. This characteristics of the results are robust in various specification of regression equations. Their results imply that there are negative effects of prime-age adult mortality on consumption growth but households may recover from the negative shock of the mortality after 5 years. They find that a prime-age adult death results in a 7% drop in consumption in the first 5 years after the death. Carter, May, Aguero and Ravindranath use KwaZulu-Natal Income Study , South Africa data and study the effects of prime-age mortality due to HIV/AIDS on long-term growth rate of per capita consumption and find the negative coefficients for dummy variables for deaths although they are not statistically significantly different from zero. They also find the large magnitude of the negative effects: a prime-age adult death lowers a household’s 5 year growth rate by 21%. Although the consumption studies above find the negative effects of prime-age adult mortality on household 5-year consumption growth, channels of the causality has not been made clear. Production studies analyze some potential channels of the causality. Beegle uses the first 4 waves of KHDS from 1991 to 1994 and studies the short-term effects of prime age adult mortality in a household on the household members’ labor supplies. She constructs dummy variables for male and female deaths in future and past 0-6 months and 7-12 months and uses them as explanatory variables in regression equations. The dependent variables are the probabilities of being in wage employment, non-farm self-employment, working on coffee production, banana production or maize, cassava, or beans production. She finds coefficients of some dummy variables for deaths are negative and statistically significantly different from zero in regression equation of being in wage employment, working on coffee production and maize, cassava, or beans production.

Yamano and Jayne use two-year panel of rural Kenyan households and study the effects of prime-age adult mortality on households’ size and composition, crop production, asset levels and off-farm income. They find the mortality decreases households’ size, area under high-valued crops, gross and net outputs, farm equipment, small animals, and off-farm income. They find that the death of a male household head is associated with a 68% reduction in the net value of the household crop production implying large negative effects of the mortality on households welfare and that channels of the causality are decreases in productive inputs above. Chapoto and Jayne use nationally representative 3-year panel data in Zambia and find the results similar to Yamano and Jayne . These production studies show that the negative effects of prime-age adult mortality on household income and channels of the causality. HIV/AIDS also increases an household’s expenditure for medical care for the sick and funeral for the deceased. Tibaijuka finds that this expenditure is almost equivalent to the cash income for the 10 households in her data from Kagera, Tanzania. We can think that decreased income and increased expenditure for health care and funeral due to HIV/AIDS and prime-age adult mortality contribute to the decreased consumption which is found in the consumption studies above. Households hit by HIV/AIDS have to face tighter budget constraints and invest less in productive assets than the other households. Smaller investment in productive assets brings smaller income in the future. We contribute to the literature with the following three points. First, we provide an answer to the question whether prime-age adult mortality decreases total factor productivity in the long run. Previous studies do not ask this question although it is an important question to study the channels from prime-age adult mortality to decreased income and welfare. This question is closely linked to the question how important an adult’s knowledge stock of agriculture is for his/her household income generation. Since subsistence agriculture in Kagera, Tanzania depends on weather and is erratic,led grow lights the knowledge may be important. On the other hand, its agriculture is traditional and does not depend on new technologies and new market opportunities so much, the knowledge may not be important. If the knowledge is important, prime-age adult mortality destroys not only household members but also the quality of household as an agricultural enterprise. Second, we decompose the agricultural income growth into TFP growth and the contribution of each productive asset. Previous production studies analyze the effects of prime-age adult mortality on each productive asset separately and cannot show how much change in each productive asset due to prime-age adult mortality contributes to change in agricultural income or output.

We quantify this channel from change in each productive asset to change in agricultural income by estimating an agricultural production function and decomposing the long-term change in agricultural income growth into TFP growth and change in contribution of each productive asset for households with and without prime-age adult mortality. Third, we study the effects of prime-age adult mortality on long-term agricultural production and link the previous studies on long-term consumption with the previous studies on short-term change in production mentioned above in this section.We can categorize channels through which the mortality changes the investment decision into two: First, the household changes future asset accumulation path as a response to changes in current asset levels due to the mortality and inheritance. For example, the household may sell land and livestock in order to achieve efficient and smaller productive asset level as a response to decreased household members and productivity due to the mortality. Second, the household’s budget constraint becomes tighter due to the mortality and the household has to change its allocation of income into consumption and investment over time. The household lost labor for income generation since the member who was sick and deceased did not and will not contribute to the household as labor and other members take care of the sick and thus the household income decreases. Furthermore, the household faces expenditure for medical care and funeral. Tibaijuka finds that this expenditure is almost equivalent to the cash income for the 10 households in her study. Although there is no consensus on what adult age range we should use to study the effects of adult mortality on household welfare1, we set the age range for prime-age adults is from 15 and 50. In this subsection, we discuss the relevancy of this age range. Our focus is the effects of prime-age adult mortality on agricultural production. We will focus on prime-age adult’s death rather than other household members’ deaths since prime-age adults contribute to their household as main labor force for agricultural production and they are the age group who are affected by HIV/AIDS directly.We set the lower bound of prime-age adult to be 15 since 15 year old individuals is physically adult and start to face the risk of HIV/AIDS through heterosexual sex. Although under 15 year old children can contribute to their households with their labor, we do not think that decreasing the lower bound would change the results since most of them do not die due to HIV/AIDS shown below. On the other hand, we set the upper bound of the age range at 50. Figures 1 and 2 show the distribution of age by gender in the data. Figures 3 and 4 show the distribution of deceased individuals’ age by gender. Figures 5, 6, 7, and 8 show the distribution of age of deceased individuals due to HIV/AIDS .

They added that flock sizes were determined by resource availability, which caused annual variability, as competition for land resources for grazing in the region was increasing.Goat rearing was a largely seasonal activity, and it was more predominant in the summer or taken up based on the income needs of individual HHs.Herd sizes ranged from 10 to 55 goats per household, depending on whether goat rearing was a primary or supplementary source of income.Focus-group participants stated that goats were grazed mainly on lands with tree and shrub cover.Large goat flocks would require large tracts of grazing land.The scarcity of such land has therefore reduced goat keeping.Sheep-rearing HHs rarely depended on off-farm labor, whereas those rearing goats frequently depended on off-farm labor or agricultural wage work.HHs also depended on markets or the public food distribution system to meet their food needs, although dependence was greater for goat-rearing HHs.The least prevalent category was the CWDL system.Most HHs in this category were medium farmers , followed by small and marginal farmers.Only 4% were large farmers.Crop production in this system veered towards food crops, using seasonally available water resources, and limited external inputs.In this case, livestock keeping was integrated and intended to support crop production.According to the participants in the focus groups, this had been the most prevalent system in the 1990s.Diverse livestock species were reared in this system.Crop and livestock products were consumed predominantly at home, and only surplus production, if available, was sold.The primary source of income for these HHs consisted of remittances from family members working in cities.Land and herd sizes are presented in Table 2.Land and herd sizes differed across systems.HHs in the CSR system had the highest herd size in comparison to all systems.The CD, CSR, and CWDL systems had comparable land sizes.

The LWL system was not comparable to any system in both land and herd sizes.In this section, we present the results of the economic-performance study of only the CWL, CD, and CSR systems ,ebb flow table as they provided consistent income from agriculture.The revenue, costs of production, and total GM per household are displayed in Table 3 for all three systems under study.For HHs in the CD and CSR systems, GM comprised income from crop and livestock production.For those in the CWL system, it consisted of crop production and off-farm activities.The economic performance of crop production is explained by the various crop management and input requirements across systems.As indicated in the focus-group discussions, the CWL and CD systems limited crop production to the monsoon agricultural season each year, while the CSR system managed crop production for both monsoon and winter seasons each year.In terms of inputs, the CWL system incurred the highest crop production costs, followed by the CSR system and then the CD system.The differences were due to the types of crops grown, with cash crops having higher costs, associated inputs, and the availability of livestock manure, which replaced expenses for inorganic inputs.Detailed information about the production costs for livestock rearing is presented in Table 4.The costs for dairy farming were substantially higher than those for small ruminants.The CD system also exhibited the greatest variation in the GM.Some of the HHs in this system had negative GMs in the summer due to low milk production combined with high feed requirements by the cattle.The CSR system was the most profitable farming system, due to low feed costs and high market price for meat.The highest costs per annum in the CSR system were for animal health care and for leasing grazing lands.These factors nevertheless did not seem to impair economic performance.The CSR system managed to obtain a high GM in the summer, the most unproductive season in dryland regions due to high temperatures and water shortages.Another factor addressed in the survey was loan access and repayment.The findings revealed that HHs took loans from multiple sources to continue farming.Among the three systems, CD HHs had the most loans from cooperative banks , local pawnbrokers , and selfhelp groups simultaneously.The loan values were also higher in comparison to those of HHs in the other two systems.In the CWL system, HHs accessed government crop loans , self-help group loans , and government schemes to manage crop production.In contrast, only 50% of CSR HHs took loans, and only from cooperative banks.

Focus group discussions indicated that loans from self-help groups were entirely availed by women, however, loans from banks were from both genders, as women also had access to banks.Despite formal credit sources, informal credit sources are still being accessed particularly by the CD HHs.This situation can be related to the high investment and production costs in dairying farming, where formal credit options work due to pending loan repayment.The GM of the HHs in the CSR system was statistically higher than that of those obtained by HHs in the CD and CWL systems.There were no statistical differences between the CD and CSR groups.The linear regression analysis revealed that factors explaining the GM were dependent on the farming system.First, caste and family type were not significant in any of the farming systems.For the CWL system, land size was the only statistically significant variable clarifying the GM.For the CSR system, both herd size and land size were significantly and positively correlated with GM.For the CD system, however, none of these variables was statistically significant.In Fig.2 below, we further illustrate the relationship between herd size and GM, which helps to explain why herd size is an explanatory variable for the CSR system, but not for the CD system.For the CSR system, GM increased along with herd size, as indicated by the significant regression line.In contrast, the CD system exhibited high variation, as CD farms with low herd size obtained both negative and positive GMs, while those with large herd sizes obtained only moderate to low GMs.The CWL system had the lowest gains and no livestock.The characterization of farming systems in the study region revealed that the CWL, CD, and CSR systems were variants of intensive, specialized, and market-oriented farming systems, while the LWL and CWDL were variants of subsistence farming systems.The majority of the HHs in the region fell into two farm categories: CWL and CD.The CSR system, although lucrative, was dominated by the BC communities in the region, given that sheep rearing has been their traditional occupation for generations.

For LWL and CWDL systems, livestock rearing was a need-based livelihood activity, and it usually involved poultry and seasonal goat rearing.Although the CWDL system was the most prevalent in the past, the majority of HHs have now transitioned away from this system.Further analysis of the three systems revealed that the CWL system is a medium-input/low-output system, the CD system is a high-input/highoutput system, and the CSR system is a medium-input/medium-output system.In terms of economic performance, the CSR system showed the best performance, as explained by the low water requirements and low feed production costs.The profitability of this system was further enhanced by growing market demand and the current market price for small ruminant meat.The system also adapted to the dynamic context by adjusting herd sizes to the decreasing availability of common property resources.All these factors make the CSR system suited to the dryland context.Despite having the highest revenues, the CD system was less profitable, due to high production costs.This system exhibited high variability in GMs from moderate to substantially negative records across HHs.This variability might have been due to the influence of other factors not included in this study.In addition, the consistent income obtained from dairy farming came at the expense of crop production in the winter season, as scarce water resources were diverted for dairying.This strategy resulted in the loss of additional income for CD HHs, in contrast to those in the CSR system, which cultivated crops for two seasons each year, in addition to rearing small ruminants.These findings thus suggest that engaging in dairy production may not be a resilient option for HHs in semi-arid regions.The CWL system consistently exhibited low economic performance, with low revenues attributable primarily to higher production costs for cash crops and market volatility.In line with other studies such as, Sallu et al.; Ten Napel et al.; Ayeb-Karlsson et al.; Kuchimanchi et al.we find that the trend of intensification and specialization in farming, particularly in the CWL and CD systems, has increased generic risks and decreased flexibility for coping with disturbances and shocks.For example, the CWL system reflected the absence of crop diversity and livestock and was dependent on off-farm employment, which was not regularly available.

The lack of crop livestock integration at the farm level increases dependence on inorganic fertilizers , which reduces soil carbon levels, subsequently affecting soil fertility, crop productivity, and revenue in the long term.These factors make HHs in this system more reliant on external inputs and market conditions to continue farming, leading to higher risks in the long term.The CD system was the most desired by HHs in the region, as it provided consistent income throughout the year.However, this system had compromised GMs and can be seen as entailing high risk,hydroponic grow table as dairy farming is heavily dependent on external markets for feed resources, scarce water resources and milk collection.Small landholdings limit feed production and increase the amount of external feed that HHs are forced to purchase to guarantee production.Further, as reported in studies by Sishodia et al.and the Central Ground Water Board , the region is currently experiencing high water scarcity, and the situation is likely to worsen.In addition to being risky, therefore, the CD system may be economically unviable in dryland regions , contrary to general perceptions.For this reason, the promotion of dairy farming among poor HHs should be a point of concern for development programs, especially in dryland regions.In the farming systems examined, higher revenues were associated with higher costs due to increased use of purchased inputs, credit, and animal healthcare services.If these costs cannot be limited, they offset revenues, hinder profits, and perpetuate the ‘poverty trap’.In this study, this situation is illustrated by the fact that HHs in the CWL and CD systems had high levels of credit and debt, due to insufficient income and low profits.Increasing credit and debt thus pose a risk, as they are likely to become intertwined with farming strategies aimed at simply adopting a system and continuing to farm.Over time, this situation often leads to a range of social-ecological consequences , all of which perpetuate vulnerability to climate change.Although the CSR system has adapted into a modernized version of traditional small ruminant production, it is likely to be subject to further constraint due to dwindling common property resources and the decreasing availability of private lands for grazing in the future.Moreover, the scarcity of grazing resources has deprived low-income HHs of alternative and profitable livelihood opportunities from goat rearing.

The decrease in native poultry rearing is having a similar impact on these HHs, despite the presence of a niche market.In dryland regions, the current reduction in livestock rearing is leading to income losses, while also translating into decreased dietary diversity during lean periods and the loss of a critical buffer in times of drought or dry spells, as crop production is highly vulnerable to such threats.Characterization and economic performance studies like this one thus provide insight into the socio-economic and ecological dimensions of farming systems and support a more customized approach to agricultural development in dryland regions.Following, we discuss some outcomes from this study under the perspective of the WDP policy, given that it is India’s leading strategy for the development of dryland regions.Firstly, this study shows that 86% of the HHs are now practicing intensive market-oriented farming.Intensive systems are often associated with increased specialization and low integration between crop and livestock production, resulting in high-water usage and the doctoral thesis by Kuchimanchi.We thus infer that water resources generated through the soil and water conservation measures due to WDPs in the region are apparently being over-utilized by some HHs thereby decreasing the availability of water throughout the year.Likely, this also explains why only 38% of the HHs in the region have been able to adopt the CD system, or why the CWL and CD systems limit crop production to the monsoon season.A second notable outcome of the study is that, while intensification and specialization in farming have increased agricultural production, it has not led to economic prosperity.For example, the average daily per capita income for HHs in the CWL, CD, and CSR systems were USD 0.2, USD 1.2, and USD 2.4, respectively.These income values are lower than the per diem wage rate of USD 2.5, as prescribed by the Indian Ministry of Labor and Employment , and the World Bank extreme-poverty threshold of USD 1.9 day/person.Lastly, while WDPs tend to promote specific farming systems , that has induced changes in land use, cropping patterns, and livestock rearing in terms of herd size, animal type, and purpose.

The mean difference for good governance between organic and conventional farming systems was significantly different for sub-themes, mission statement and full-cost accounting.For instance, ‘Mission statement’ was significantly better for organic as organic farmers were aware of their cooperative certification and what it stood for.Similarly, in Ssebunya et al., the governance dimension recorded low scores.The sustainability performance of farming systems has several important implications for cocoa farm managers/farmers.The context in which farmers manage their cocoa farms has changed rapidly, often with little warning.The environmental specifications for producing cocoa, the socially stringent measures of abolition of child labour ensure fairness in labour conditions.These create uncertainty regarding future threats and potentials of producing cocoa through the organic or conventional farming system.This article emphasises the need to think about sustainability at the farm level at a basic level rather than the crop level.This underscores the need for improvement across the value chain.Notably, the paper highlights that farm level activities are within broader social and natural boundaries.An accurate picture of the sustainability performance of a farming system cannot be developed if these boundaries are ignored.Explicit recognition of these points in managerial decision-making would represent a marked departure for crop level that have thus far been reluctant to look beyond their walls.The SMART-FARM Tool provides the needed basis for measuring the economic, environmental, good governance and social impacts of farming systems.This, in turn, would help decision-makers better understand their sustainability risks and opportunities.This is needed because farming systems must be proactive in addressing any potential economic, environmental,vertical grow table good governance and social challenges that could emerge throughout their value chains.

Given the significant number and variety of these sustainability challenges, farming systems must prioritise the issues that need the most urgent attention.The sustainability performance of farming systems using the SMART-FARM tool provides a basis for developing comprehensive strategies to improve performance and informed decision making towards prioritising farm outputs.Implementing these strategies comes at a cost so that farmers need to tackle the inevitable tradeoffs between efficiency and adaptability.However, unless farmers master this challenge, they cannot ensure the sustainability of their farms.Climate change-induced weather anomalies, such as extreme droughts and intense rainfalls, have been increasingly observed in places where people are highly vulnerable to their various effects in recent years.Assessing the vulnerability and unequal coping capabilities to climate change and weather events has been a focus of research attention, for example, vulnerability to flooding , urban vulnerability to extreme heat , agricultural vulnerability to drought , to climate change , and to severe snowstorms.It is observed that climate change has caused polar cold air and anomalously cold extremes moving southward as a result of winter atmospheric circulation at high northern latitudes associated with Arctic sea ice loss.The increases in winter storm intensity and frequency are evident in the US, especially in both mid- and high-latitude zones , and have produced non-negligible winter weather-related losses.However, as one of the commonly seen catastrophic weather events, winter storms and their impacts are often overlooked and understudied.Winter storms have been recognized as one of the catastrophic events leading to agricultural damage and loss.In farming regions, severe winter storms such as blizzards, unending snowfalls and extremely low temperatures can lead to building damage, animal losses, and reduction in milk production.Winter storms on farmlands can also create other issues including the removal of fertile soils, traditional routines failure, and crops being wiped out.In the US, the Midwest is well recognized as a major producer of vegetables, dairy, beef cattle, and pigs.It is also a region that has experienced severe cold-air outbreaks and record numbers of snowstorms.

However, research is notably lacking in the vulnerability of farm communities to increasing winter storm events.The Intergovernmental Panel on Climate Change has contributed to assessments on climate change impacts, adaptation, and vulnerability since 1990 and created the distinct definition of vulnerability in 1997.Many climate-related vulnerability studies adopted the IPCC’s definition of vulnerability as a function of exposure, sensitivity, and adaptive capacity.The three vulnerability dimensions are defined as 1) exposure that characterizes the stressors and the entities under stress, 2) sensitivity that characterizes the direct effects of the stresses, and 3) capacity of the system to cope, adapt or recover from the effects of those conditions.Building on the concept of vulnerability, several investigators have advanced the characterization of the vulnerability components and approaches to assessing vulnerability.Among them, Hahn et al.constructed the Livelihood Vulnerability Index and categorized major indicators into contributing dimensions of vulnerability to evaluate livelihood risks specifically resulting from climate change.Since then, the vulnerability index further evolved with the replacement and addition of other indicators to suit local contexts and to be more relevant for target groups.There has been an increasing recognition of the linkage between vulnerability and five core categories of capitals including natural, physical, human, social, and financial capital.These capitals were described in the Sustainable Livelihoods Framework as resources used in the vulnerable context to cope with short- and long-term problems and have been integrated into indices to measure adaptive capacity.Despite various indices developed to estimate the level of vulnerability of agricultural communities to extreme weather events, suitable metrics of rural winter storm vulnerability remain under explored.To address the lack of vulnerability assessment regarding threats of winter storms in agricultural regions, this study identified rural areas of different vulnerabilities and explained factors leading to these differences by integrating local knowledge, existing indices, and statistical analyses.The synthetic vulnerability index developed in this study was anticipated to serve as a tool for adaptation planning and be adjusted to suit other climate-related vulnerability assessments or study regions.It is located in the Midwest of the United States between 40◦35′ N-43◦ 30′ N latitude and 90◦ 8′ W- 96◦ 38′ W longitude.

The state comprises 35.7 million acres, with over 85 percent of the land farmed, and has long led nationally in hog, egg, corn, and soybean productions.Iowa has an estimated population of 3.17 million in 2020 and maintains a diversified economy dominated by agriculture, manufacturing, biotechnology, finance and insurance services, and government services.There are 21 out of a total of 99 counties designated as metropolitan statistical areas in Iowa.Main metropolitan cities with a population of more than 100,000 include the capital city of Des Moines in Polk County, Cedar Rapids in Linn County, and Davenport in Scott County.Iowa is located in the heart of the blizzard belt and experiences frigid temperatures as well as dramatic storms in the winter.Average winter temperatures in the state could drop well below freezing, for example, even as low as below 6 ◦F in Cedar Falls-Waterloo, Black Hawk County.Most field investigations in this study were conducted in Black Hawk County, where about 133, 000 people reside in its twin cities of Cedar Falls and Waterloo.The vulnerability was analyzed at the county level for which the complete data was available.This study conducted several semi-structured interviews in the counties of Black Hawk, Buchanan, Kossuth, and Washington to obtain farmers’ narrated perceptions on winter storm impacts.This step is important because the interviews with stakeholders can provide the necessary information and knowledge in the local context.During January to February 2019, 14 farmers that produced different types of commodities were selected using a purposive snowball sampling approach so that they can represent main on-farm activities such as crop farming and cattle ranching coded in the North American Industry Classification System.Among the interviewed farmers, 5 operated diversified farms producing animal and crop commodities, 3 operated crop farms, 4 operated livestock farms, 1 was an orchard farmer, and 1 was a poultry farmer.Their farms ranged in size from 0.25 acres for a chicken farm to 500 acres for a livestock farm.Each interview took between 30 min to 1 h to complete the questions covering topics of the three key components of vulnerability assessment.A detailed list of questions is provided in Appendix A.While the visited places did not cover the entire state, they spread across different parts of Iowa, collectively enabling a comprehensive view of winter-related issues on farms in the state.Table 2 summarizes the winter storm-related impacts on farms and Fig.2 presents the frequency of content mentioned by respondents.They have revealed that, mobile vertical grow tables in the face of winter storms, Iowa farmers were mostly concerned about animal health, building damage, water and feed shortage, and power outage.

Efficient information delivery, insurance, and windbreaks were considered important in reducing storm losses.Additionally, blizzard, extreme cold, strong wind, and icing appear to be among the main threats associated with winter storms.Extreme weather can cause significant losses and damages such as decreasing yields and commodity quality levels in agricultural production systems.The interview results showed that farmers were exposed to losses from extreme winter weather such as winter temperature fluctuations and ice storms that threaten animal health and power supplies.The increases in storm occurrences and temperature variation lead to higher exposure.Event occurrences and temperature deviation have been used in previous climatic vulnerability assessments to represent the frequency of exposure and the level of changes in daily mean weather conditions.In this study, winter storm occurrences and winter temperature deviation were selected to measure the different exposure of Iowa counties to winter.The data on event counts was collected from the Storm Event Database provided by the National Centers for Environmental Information , which contains records on the occurrence of threatening weather phenomena.Various winter-related event types were considered in this study, including blizzard, cold/wind chill, extreme cold/wind chill, frost/freeze, heavy snow, ice storm, strong wind, winter storm, and winter weather.A Python script was created to calculate the total event counts for all counties in Iowa during the winter months of December, January, and February between 2010 and 2017.Winter temperature deviation was calculated using the minimum and maximum temperatures for each county downloaded from Parameter-elevation Regressions on Independent Slopes Model website which provides climate observations in the US at multiple spatial/temporal resolutions.From the interview results, it was found that the immediate impacts of winter storms came from affected on-farm structures and activities such as animal husbandry and building damage.Poorly constructed buildings appear to increase sensitivity to climate impacts.Animal health can be threatened by low temperatures and restrained freshwater access.Livestock farms are highly dependent on the climate conditions of a given year and they have to make considerable efforts to prepare supplies, implement actions, and recover in the face of winter storms.On the contrary, crop farms appear less sensitive during winter since crops are usually harvested back in the autumn.Thus, animal commodities sale and building age were selected as sensitivity determinants and represented using the 2012 farm sale statistics retrieved from the United States Department of Agriculture QuickStats and the 2012–2016 housing characteristics data collected from the US Census Bureau.Adaptive capacity is the ability to take actions and make adjustments to reduce adverse impacts resulting from climate-related hazards.The ability to cope with extreme weather events varies depending on assets, tangible and intangible, that support people’s livelihoods.These livelihood resources are seen as “capitals” and can influence adaptive capacity and thus vulnerability.Based on the five forms of capitals described in the Sustainable Livelihoods Framework, this study identified multiple adaptive capacity indicators from five dimensions: Natural capital.Farms surrounded by trees as windbreaks are assumed to be more protected from strong wind, therefore less vulnerable.This study used a georeferenced, raster-formatted and cropland specific land cover data layer downloaded from CropScape to extract pasture and tree cover in each county.Pastures with windbreaks were identified using a specified search radius of 200 feet as the recommended distance of a proper tree windbreak.Financial capital.Poverty has been included as a vulnerability factor.It is assumed that households with lower income possess fewer assets such as equipment and appliances that can help with the maintenance of buildings and animals.Thus, farm income and poverty were included as indicators for financial capital.The poverty rate and farm income for the year of 2012 were collected from the US Census Bureau and USDA QuickStats, respectively.Physical capital.Access to the Internet is considered the dominant way to collect all sorts of environmental knowledge to assist with decision-making.With sufficient Internet access, households can stay informed and are more likely to benefit from new policies and plans launched in real-time.This mirrors the qualitative interview results that have highlighted the importance of information.In this study, internet access was indicated by internet operations collected from USDA QuickStats.

Studies indicate that gender, religion, class, and positions within households, and other cultural values also affect the uptake of information.As a result of the variety of social-economic and cultural factors which affect the uptake of forecast information, there is the need to focus on context-specific issues rather than wholesale generalizations of challenges.Hence, in Ghana, dissemination and farmers’ access to WIS has drastically improved.And the substantial body of knowledge on climate information science is developing in Ghana and elsewhere in sub-Sahara Africa.However, there is little evidence that WIS is applied in decision-making processes, including adaptive for smallholder farmers.Meanwhile, variability in climatic conditions affect farmers’ decision-making strategies, leading to low crop yield and increasing financial burdens on farmers in Ghana.We argue that the use of WIS for informed decision-making in farming requires an understanding of the usefulness and usability of WIS in terms of farmers’ definitions and perceptions.This knowledge gap is not well understood in the literature in Ghana and elsewhere in developing countries.Thus, providing WIS that is readily usable for decision-making in farming requires navigation and bridging any differences that might exist between what scientists/information providers perceive as useful and what is usable in practice.Therefore, this study examines the weather information services usability for farming decision-making with evidence from Ghana’s Ada East District.We organised the study into six sections.The study’s conceptual framework is presented in the next section, followed by a section on research methods.Subsequently, the study findings are presented in section 4,dutch buckets system followed by the discussion and conclusion in sections 5 and 6.

Usable information is defined in various ways to understand the relationship between information providers and users.We build on earlier definitions by attuning them to the farming context, where usable information is information that farmers are able to use as input for farming decisions.Although the terms useful and usable are often used interchangeably in the literature, they do not mean the same thing.Useful information is potentially relevant for decision-making, yet, because users may not know or may have unrealistic expectations about how it fits their decision-making, they may choose to ignore it.On the other hand, usable information is the knowledge that is readily applicable by users in the formulation of strategies under uncertain conditions like climate change and variability.Hence, although all forms of user-inspired knowledge are in principle useful, they are not always usable unless users and producers take specific steps to ensure that useful information is applied.On this note, it can be said that useful information relates to information providers’ outlook.In contrast, usable information pertains to users’ viewpoint about how applicable the information is for decision making in their context, considering factors such as availability of resources.It is precisely these different perceptions and understandings of useful and usable information between information providers and users that create the usability gap reflected in the low uptake of WIS.Dilling and Lemos distinguished the usability gap in climate information by indicating two broad areas: context and information production.For farming, context relates more to the farmer and issues arising from the farming community; for example, conservatism towards applying new information.Although this aspect of the usability gap is relevant, our study focuses on the information design and delivery aspect, which pertains to how information providers produce and deliver information to enable its usability.We build on Dilling and Lemos’ framework to develop analytical criteria for our study by attuning some of their factors with ours.

We expand on their framework, which focuses mainly on the formal scientific production of climate information services on a global scale.We do so by building five information design and delivery analytical criteria by adapting aspects of their framework and other new criteria derived from the literature to assess information design and delivery for farming.Local embeddedness refers to how information design and delivery connect with local farming conditions and context in a specific community.This criterion can relate to a situation where WIS is provided, including the knowledge of farmers, so that their unique characteristics, rules, farmers’ exposure to different sources of information, and information seeking and sharing behaviour are captured in the information design.Additionally, an information design with local embeddedness may include other relevant information design features such as agrometeorological indicators, agronomic tips, and so forth.The information should also be linked to farmers’ personal characteristics and social networks.Legitimacy denotes that information design and delivery conform to farmers’ interests, values, concerns, and perspectives, resulting in acceptability.Farmers may judge the legitimacy of the WIS based on who participated or not in its design and delivery.Here, the information design and delivery may consider several options, such as respect for farmers’ value and how the WIS connects to the contextual needs of farmers.Information providers may also attain legitimacy by maintaining mutual trust and respect.It also implies the alignment of the information to farmers’ local knowledge and values.Furthermore, the legitimacy of information can be affected if a forecast fails, is irregularly delivered, or is associated with long delivery chains and political biases.The temporal aspect of information design and delivery indicates when to expect specific weather conditions for farming, whereas the spatial resolution denotes the surface area for which information providers produce the forecast.The temporal criterion of information design and delivery may consider when the information delivery will be relevant to determine when to plough, sow seeds, or select crop varieties.Also, the presentation of timing as early onset, usual onset, and late onset in a seasonal forecast may be a relevant information design characteristic.

Information providers can tailor the information into high spatial resolution by integrating farmers’ local forecasts and analysing the implications of the projection with farmers.When the information design includes the delivery of high spatial resolution, some trade-off needs to be made between skill and scale criteria.We conducted the study in the Ada East District in the coastal savanna agroecological zone, where agriculture is the main economic activity.Agricultural activity in the district consists mainly of cultivating of vegetables, cassava, maize, watermelon, and other crops.Despite the relevance of farming for livelihood development and food supply to urban markets, the area experiences long dry spells, frequent dry spells, and low mean rainfall during the rainy seasons.The coastal savanna agroecological zone also experiences interannual variability interms of seasonal rainfall.In the area, the complex series of coastal/oceanic and atmospheric interactions including the role of the inter-tropical convergence zone contribute to uncertainty in weather conditions.These incidences have several implications, such as loss of planting materials, crop failure, and low yield.The Ada East District is selected for the study among other districts in the coastal savanna agroecological zones because the district is one of vegetable producing areas, including the Anloga-Keta area.Although the district shares the same climatic conditions with other districts, the availability of water to support the growth of crops is a challenge, compared to other districts such as the Anloga District and the Keta Municipality, which has groundwater available for farming throughout the year.In the district, the application of forecast information to support decision-making in farming is crucial.Despite growing research on the climate information sector in Ghana, most studies have focused on the Guinea, Sudan and the Sahal savanna agroecological regions.Hence, little knowledge exists on the provision of forecast information for farming in the coastal savanna agroecological area.

We argue that for the country to be food secure, there is the need to focus on regions especially, the Ada area, where water availability is a challenge despite its prominent role in the supply of food to rural and urban areas in Ghana.A qualitative research approach was applied in this study to establish rapport with research participants and use the findings to inform policy.Hence, in this study, we combined semi-structured interviews and focus group discussion methods to cross validate research findings and derived detailed information concerning the study’s objective.The qualitative research was conducted from June 2017–March 2018 in two phases, with results from phase one informing the organisation of the subsequent phase.The period stated above includes the performance of activities such as community entry, reconnaissance survey, informal conversations with farmers and stakeholders, and the actual data collection.The application of semi-structured interviews and FGDs as two phases of the research is described below.In the Ada East District, three farmers from each of the following communities were engaged in semi-structured interviews: Kasseh, Asigbekope, Bedeku, Ada Foah, Toje, Ocanseykope, Anyarkpor, Angorsekope, Dogo, Totimekope, Kajanya, Atortorkope and Tovie.At Detsekope, we interviewed one farmer, and at Kpodokope, we interviewed two farmers.This amounted to a total number of 42 semi-structured interviews in the Ada East District.With the assistance of agricultural extension agents and some community leaders, farmers were selected based on their availability, gender, dutch buckets use of WIS for farming, age, experience in farming, social status, and farming practices.We conducted interviews with either one male and two female household heads or two male and one female household head in each community.Participants in the interviews and the FGDs consented to partake in the study, and we assured them that their identity would be concealed in presenting research findings.The lead author conducted interviews in person, and respondents agreed that the researcher recorded the discussions.In the interviews, questions were posed on the types of WIS used, the extent of use, the ranking of the extent of use, explanations for a specific WIS’s choice over others, and other emerging issues were discussed.

The outcome of the semi-structured interviews informed the design of FGDs, to derive an in-depth understanding of farmers’ views concerning the types of WIS and the emerging factors which affected the usability of WIS for farming in the study district.Through the FGDs, we uncovered personal and communal attitudes, beliefs, and preferences of discussants concerning the types of WIS and their usability for farming.We designed the FGDs to elicit the interwoven factors that enhanced or obstructed WIS usability in the communities, when a participant indicated that an information provider delivered regular information, the group discussed and agreed on the definition.For example, guided by the lead author, discussants agreed that ‘regular’ could mean the daily or weekly provision of WIS.Overall, three FGDs were conducted in three communities: Toje, Anyarkpor, and Wassakuse.The three communities were representative of the three agricultural zones in the district, namely, the Kasseh, Big Ada, and the Ada Foah Zones.Through this cluster, we analyzed and derived general issues that affected the usability of WIS for farming in the district.The FGDs comprised eight to ten male and female farmers who were not part of the semi-structured interviews.At Toje, the discussants consisted of two older women, two younger women, three young men, and three older men.At Anyarkpor, there were nine participants in the FGD, comprising of three older women; one young woman; two young men; and three older men.At the same time, the FGD conducted in Wassakuse consisted of eight participants , for a total of 27 participants.There were no exclusive groupings of participants because, in the study district, women are allowed to freely express their views on issues in the presence of their male counterparts.Also, we sort to generate answers to the research in a context where participants could respond to multiple opinions.Thus, when a participant responded to a question, other discussants corrected or realigned some views together.Since we conducted the FGD purposively with different generational groups mixed together, we catered for the possible emergence of power and gender inequalities by calling each participant to express their opinion on a specific question.This approach helped to moderate the discussion and ensured that overactive participants did not dominate the entire discussion.We also called participants to vote on certain opinions, especially about the factors that enhance or obstruct the usability of weather information services and the ranking of the different information providers, including the district.Data analysis was carried out in three stages.The first stage involved the transcription of audio recordings of the semi-structured interviews and FGDs.We edited the transcripts by identifying the responses generated to specific questions, realigned sentence structures, and clarified the construction of some sentences.During this time, in addition to the field notes, we took notes on emerging issues.The next aspect of this stage involved grouping the transcript contents into specific identifiable themes.Second, we conducted inductive coding to identify the factors that affect WIS usability based on recurring words running through the transcripts.