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Many ecological processes governing agricultural pest abundance occur over a large spatial scale

Additionally, as the amount of land in cropland increases, opportunities for invasion or refuge from pesticide applications may be reduced, thus leading to a negative effect of landscape simplification on pesticide use. Three recent reviews of empirical, landscape-scale ecological studies evaluating the effect of landscape complexity on insect pests reported similarly equivocal results, with some studies finding reduced pest pressure, pest abundance, or pest diversity, whereas others find no relationship or the opposite relationships . The variability in the literature may reflect the inadequacy of current study designs to disentangle the net effect of landscape simplification on pesticide use. Confounding variables, such as crop type, or endogenously determined variables, such as farm size or income, could give misleading results if not properly controlled for. Alternatively, studies that are small scale or over short time periods may miss important underlying drivers of pest abundance. Pests disperse large distances, both naturally and aided by the movement of people and goods. Agricultural pests are thus likely governed in large part by meta population processes . Within an agricultural landscape pests may go locally extinct from crop patches because of pesticide use or because of stochasticity influencing small populations, only to be recolonized from a persistent meta population existing in the surrounding agricultural matrix or from a new invasion into the system. Natural enemies too may require resources outside of individual crop fields for alternative prey and shelter for overwintering or from disturbances, such as pesticide application or harvest . Furthermore,dutch buckets the periodic disturbance of crop fields may disrupt predator–prey dynamics by reducing natural enemies directly or by temporarily reducing pest populations to the level below which predators can be supported.

As a result of pest and natural enemy dispersal and immigration, the effect of local processes on regional abundances may be small, despite large effects on within-field abundances. Thus, small-scale studies that fail to account for the landscape-scale dynamics of agricultural pests and their natural enemies could result in spurious associations of what promotes or limits pest abundance. For these reasons, landscape-scale studies provide the best insight into the effect of habitat simplification on pests . Beyond meta population dynamics and trophic interactions, invasion and spread of insect pests and natural enemies are partly stochastic processes influenced by yearly environmental conditions and by the timing of insect pest and natural enemy arrival . Thus, temporal scale may be equally as important as spatial scale to disentangle the effects of landscape simplification on pest abundance. For example, a heat wave at the right time of the growing season may result in widespread pest mortality and high crop yields, whereas a heat wave at a different time of the season may stress crops, making them more susceptible to pest outbreak but having little effect on the pests themselves. This variability over time could appear like ambivalent results of landscape simplification when it is instead the result of the interaction between insect pests and weather. If we are to mitigate the effects of pesticide use on both human health and ecological systems, it is necessary to understand the underlying abiotic or biotic factors resulting in differences in pesticide use. Here I take advantage of longitudinal data from the US Department of Agriculture Census of Agriculture to revisit whether landscape simplification is a consistent driver of insecticide use. I perform cross-sectional analyses for five USDA census years in seven Midwestern US states at the county level. I follow this with a panel data analysis using a fixed-effects model, which identifies the effect of landscape simplification on insecticide use using year-to-year variation within counties.

I specifically focus on insecticides in these states to compare this multiyear analysis with a recent single-year study by Meehan et al. . I check the robustness of these results by comparing data from the USDA Census of Agriculture to the National Agricultural Statistics Service Cropland Data Layer , and check different selection criteria for included counties. I compare these results to that of Meehan et al. , who used the same data sources and model specifications for 2007 only, and find that incorporating multiple years of data as I do here provides insights impossible to glean from a single data year.Annual expenditure on insecticides is over 4 billion dollars in the United States , which equates to the use of almost 100 million pounds of active ingredients . Given the many health and environmental consequences related to insecticide exposure, it is critical to understand what farm, landscape, or environmental characteristics drive the insect pests that motivate insecticide use. It has long been thought that landscape simplification is one of these characteristics. Reviews of empirical evidence for this theory have been largely inconclusive , although a recent statistical analysis of the Midwestern United States in 2007 found a strong, positive relationship between landscape simplification and insecticide use . Here I analyzed data from five USDA Census of Agriculture years using cross-sectional and fixed-effects models. The cross sectional results show that landscape simplification does not consistently drive higher insecticide use. Although the coefficient on proportion of county in cropland, my metric for landscape simplification, is positive and significant in the 2007 analyses, that relationship is absent or reversed in prior census years. Furthermore, adjacent census years, such as 2002–2007 and 1992– 1997, show large changes in the magnitude and changes in significance of the landscape-simplification coefficient.It is evident that the drivers of insecticide use may not be easily or reliably identified using single time-period studies. Using a fixed-effects model to remove unobserved characteristics, I find a non-significant relationship between landscape simplification and proportion of county in cropland. Counter intuitively, these results suggest that as cropland increases, the proportion of cropland sprayed with insecticides is unaffected.

The existence of a null relationship between landscape simplification and insecticide use is not unlike the results of Hutchison et al. , who reported large reductions in the European corn borer in non-Bacillus thuringiensis corn as a positive externality from B. thuringiensis corn plantings. Although pesticides may have negative effects on public health, biodiversity, and ecosystem services,grow bucket the application of pesticides by a nearby farm may reduce pest incidence on surrounding farms because of pesticide drift or pest suppression . Additionally, as the amount of land in cropland increases, opportunities for invasion from natural or untreated areas may be reduced. As a result of landscape simplification, natural lands have been isolated to farm boundaries, fallow lands, or wood lots . Numerous ecological studies have found that these fragmented natural or less intensively managed areas can act as a source for natural enemies and pest species that recolonize species poor crop fields . If the cost of pest invasion is greater than the benefits of natural enemy pest suppression stemming from non-crop land, these habitats can have a net negative impact on the farmer in terms of pest control. The above mechanisms may explain why a null relationship is observed in the fixed-effects model; however, they do not account for the importance of year. What could explain the wild variation in the landscape simplification coefficient in the cross sectional analyses and why year fixed effects are so important? There are a number of drivers that could be behind the year-to year variability, and deciphering which mechanism is at play is critical because different policy measures are needed to address different types of drivers. For example, a stochastic driver such as weather could be the culprit. Insect development is strongly influenced by weather conditions, such as temperature and precipitation, and thus yearly differences in these or other environmental conditions could have an important effect on insecticide demand and the relationship between landscape simplification and insecticide use. Preliminary analysis indicates that the effect of weather on this relationship is complex. [Preliminary analysis using growing season precipitation and degree days based on the National Climatic Data Center Global Historical Climatology Network Daily file does not explain the variation in the cross-sectional relationship between landscape simplification and insecticide use.] This finding may be because the timing of pest arrival relative to the growing season may determine the likelihood of pest outbreaks and the benefits of applying insecticides . Furthermore, temperature and precipitation affect the survival and development of different pests differently, and thus which pests and enemies are present may determine the effect of weather on the relationship between landscape simplification and insecticide use. Refined data on pest outbreaks or type and timing of insecticide use are currently not available for the study area examined. However, the development of such data or further empirical study focusing on abiotic conditions would greatly increase our understanding of the link between weather events and insect outbreaks, and thus increase our ability to forecast variation in insecticide use both now and under future climate change. It is also conceivable that the change in the relationship between landscape simplification and insecticide use between 2007 and all previous years reflects a systematic and predictable trend in insecticide use. For example, in 1996 there was a major change in the regulation of pesticides in the form of the Food Quality Protection Act .

FQPA prompted the reevaluation of all registered pesticides, and promoted the use of more selective, less persistent “reduced-risk” pesticides via a fast-track registration process . FQPA could affect the relationship between landscape simplification and insecticide use because insecticides that are effective against a multitude of insect pests and persist in the environment for longer periods of time may have provided higher positive externalities to surrounding crop fields, thus necessitating less insecticide use in landscapes dominated by agricultural fields. The implementation of FQPA and the resulting use restrictions took 10 y, and phasing out of certain chemicals is still in progress . Because changes in available insecticides were occurring between 1996 and 2007, it is difficult to statistically evaluate the effect of FQPA on the results reported here. Future Census’ of Agriculture or more refined insecticide data that include information on the active ingredient in use could elucidate how policy changes are interacting with the relationship between landscape simplification and insecticide use. Agriculture has vast impacts on the Earth’s environment and these impacts are only expected to grow as demand increases in the coming decades . The challenge, as Balmford et al. discuss, is how to meet the increasing demand with the least effect on native biodiversity and the ecosystem services intact ecosystems provide. There are various advantages and disadvantages to whether increased demand should be met by increased intensity of farming on current agricultural land or by increased land conversion to agriculture to be farmed with more biologically harmonious farming methods . In the Midwestern United States, it appears that land-sparing at the county level does not lead to consistent increases in the proportion of cropland treated with insecticides. However, without understanding what is behind the year-to-year variation in the relationship between landscape simplification and insecticide use, it is impossible to predict how land sharing or land-sparing as a policy initiative would affect insecticide use in the future. As suggested by this study and recent empirical reviews , the presence and direction of the relationship between landscape simplification and insecticide use can be positive, negative, or null. If this variation is driven by variation in yearly weather, whether simplified landscapes cause more or less insecticide use could flip flop unpredictably. If the variation is driven by extreme weather or weather characteristics that will be altered with climate change, perhaps there will be some directionality. If the relationship between landscape simplification and insecticide use is an indirect consequence of management policies, perhaps 2007 is a glimpse of the future. The data available are currently inadequate to decipher the underlying mechanisms. However, given the different policy implications of a stochastic driver, such as weather, versus a predictable driver, such as regulatory change, developing the necessary data sources to tease apart the underlying causes is imperative. Perhaps most importantly, this study emphasizes the need for longer-term research agendas, especially when investigating a politically, economically, and ecologically important question, such as insecticide or pesticide use.

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Chemical synthesis is a widely adopted approach to generate such analogs of existing NPs

Humans have been using the potent action of NPs for multiple purposes from medicinal to cosmetic and recreational use as well as in agriculture. During the golden age of NP discovery from the 1960s to the 1980s, scientists in academia and industry identified and characterized an impressive list of NPs that are still being used today: The antibiotic compounds penicillin or amphotericin, the cholesterol-lowering lovastatin, or the cancer drug taxol are just a few examples of how these microbial ecological weapons were repurposed for combatting diseases.In agriculture, NPs have been applied as fungicides, insecticides, and herbicides that have contributed substantially to the increases of crop yield and quality worldwide. From 1997 to 2010, NPs and their derivatives made up about 36% of all new registered pesticide ingredients. For example, spinosyn and avermectin, produced by soil-borne bacteria Saccharopolyspora spinose and Streptomyces avermitilis, can effectively paralyze insects through hyperexcitation of their nervous system . The discovery of avermectin by Satoshi  Omura was awarded the 2015 Nobel Prize in Physiology or Medicine. Phosphinothricin, also known as glufosinate, produced by Streptomyces, has been commercialized by Bayer as an herbicide under the tradename of Finale . By inhibiting glutamine synthetase, glufosinate kills plants via ammonia buildup in the thylakoid lumen, which leads to decoupling of photophosphorylation. Fenpicoxamid is a commercialized fungicide derived from the NP antimycin that inhibits cellular respiration . The sales of both glufosinate and fenpicoxamid exceed US$1 billion annually. There are many other NPs with unique modes of actions that have not been commercialized owing to the high cost of mass production. For example, potential herbicides thaxtomin and tentoxin are able to disrupt cellulose biosynthesis and energy transfer, respectively; cornexistin possesses broad-spectrum herbicidal activity via inactivation of aminotransferases but only low activity against maize .

Nonetheless, new products are constantly needed: It is estimated that up to 50% of global crop yields are lost each year mainly due to pesticide resistance. Hence, there is a continuous demand to discover new insecticides,grow bucket fungicides and herbicides with novel modes of action, accompanied by efforts to decrease their production cost. Not surprisingly, NPs have remained important sources for such discovery efforts. Here, we describe how deeper understanding of NPs and their biosynthesis may lead us to new products for agricultural use.NP discovery was traditionally performed by isolating organic molecules from anorganism of interests. The workflow involves the collection or growth of the organism, followed by extraction of organic molecules and fractionation of the extract. The isolation of a pure NP from complex extracts is typically guided by screens, either via direct biological assays of the target enzyme or through identification of novel structural features. These techniques have proven to be hugely successful during the golden age of antibiotic discovery. In recent years, however, reports of new structures and activities have slowed significantly, leading many pharmaceutical companies to abandon NP programs. The advancement of new techniques in genomics has brought a renaissance to NP discovery. Thanks to the rapid development of DNA sequencing technologies, an increasing number of whole genome sequences are now available for research. Extensive studies into the biosynthesis of NPs and the genes encoding the enzymes involved have shown that the genes for one NP are typically clustered, which presumably facilitates co-regulation during transcription, and horizontal cluster transfer between species. A bio-synthetic gene cluster can be readily identified using powerful software packages through an anchoring bio-synthetic enzyme that produces the core of a NP. Such anchoring enzymes include polyketide synthases, nonribosomal peptide synthetases, or terpene synthases.The number of BGCs in a microorganisms identified in silico is therefore a reasonable estimation of the total number of NPs an organism can potentially produce. Given that only a small fraction of BGCs are associated with known compounds, the true bio-synthetic potential of microbes is much larger than the number of known NPs.

Indeed, most BGCs remain silent owing to their complex regulation and our inability to reproduce the natural environmental cues that are needed to turn them on: It is estimated that more than 90% of BGCs remain as genomic “dark matter” encoding secondary metabolites that have eluded traditional NP discovery. It is therefore tantalizing to speculate how many new NPs could be discovered if we can efficiently tap into these silent BGCs. Different approaches have been applied to awaken these gene clusters, including constitutively expressing pathway-specific transcription factors, epigenetic modifications to alter chromatin structure and transcriptional activities, and heterologous expression of desired pathways in model hosts. While these approaches are successful in inducing BGCs to produce new NPs, their true biological activities are typically unknown: Compared to more traditional NP discovery, the genomic approaches are not activity-guided. Giventhe large number of BGCs available, it is essential to prioritize genome-driven discovery of NPs by biological activity. How can we predict the activity of a NP based on genomic sequence? The answer to this question can unlock the true untapped potential of the tens of thousands of BGCs.To find agriculturally useful NPs with new modes of action from tens of thousands predicted BGCs, we developed a resistance gene-guided approach. The rationale is that host organisms producing NPs that target housekeeping enzymes must have a method of protecting themselves. Several mechanisms of self-resistance are known: efflux pumps that actively transport the metabolite to the extracellular space; proteins that stoichiometrically bind to the NPs; and enzymes that modify the housekeeping target to evade NPs. Nature also evolved the clever strategy to encode a mutated copy of the sensitive housekeeping gene in the NP BGC . This self-resistance enzyme can carry out the same function as the housekeeping enzyme, but is sufficiently mutated to be insensitive to the NP. Because the self-resistance gene is required for survival during NP production, it is frequently co-localized in the same BGC. An example is the lovastatin BGC: A second copy of 3-hydroxy-3-methylglutaryl-coenzyme A reductase , which is the target of lovastatin, is encoded in the lovastatin BGC in Aspergillus terreus . This co-localization has been exploited to link BGCs to compounds with known targets. We propose that using the self-resistance gene as a predictive marker, one can mine NPs from collections of BGCs with desired bio-activity. A workflow for such guided genome mining looks as follows: After identifying a desired target enzyme that is also present in microorganisms, one can search through genome databases for BGC carrying duplicate copies of the target gene that is located close to a bio-synthetic anchoring enzyme; different synthetic biology approaches can be applied to produce the NP encoded in the cluster; the NP is isolated and the structure is elucidated using NMR spectroscopy; and inhibition of the housekeeping enzyme and insensitivity toward the self-resistance enzyme are validated biochemically or genetically. We applied this approach to search for herbicide leads with novel modes of action to target dihydroxy acid dehydratase within the branched-chain amino-acid bio-synthetic pathway. We first scanned fungal genomes in publicly available databases for a BGC that encodes a possible resistant copy of DHAD. We eventually found a conserved four-gene cluster in Aspergillus terreus, which encodes a terpene synthase, two cytochrome P450s and a duplicate copy of DHAD that is about 60% identical to the well-conserved housekeeping DHAD. The cluster was introduced into Saccharomyces cerevisiae, which produced aspterric acid at 20 mg/l. Consistent with our hypothesis,dutch bucket for tomatoes aspterric acid was verified as a potent competitive inhibitor of the housekeeping DHAD enzyme from A. terreus and Arabidopsis thaliana. In contrast, the Aspergillus self-resistance DHAD was insensitive to aspterric acid.When applied in planta, aspterric acid showed strong growth inhibition of representative monocots and dicots.

When applied at lower concentration, aspterric acid could specifically inhibit the formation of pollen without harming pistil development. Hence, aspterric acid may be used as a chemical hybridization agent in the field to facilitate out cross and hybrid seed production. Motivated by the success of using a combination of glyphosate-based herbicide and glyphosate-tolerant crops in weed control, we also demonstrated the possibility of creating transgenic plants that can tolerate aspterric acid treatment through expression of the resistance gene astD.Discovery and proof of action is just one part of the process though; for using NPs in agriculture also requires large-scale and cost effective production. Microbial fermentation using genetically modified organisms has therefore great potential to produce a given compound at high titer. Furthermore, the use of a generally regarded as safe organisms such as S. cerevisiae as a production host can alleviate public concerns. In recent years, S. cerevisiae has been intensely pursued as a host for production of biofuels, chemicals, and pharmaceuticals, the last of which mostly consist of NPs. For example, a 23-step biosynthesis of opioids was recently achieved by combining enzymes from different organisms into a bio-synthetic pathway in yeast. Similarly, strictosidine, the common precursor to thousands of plant monoterpene indole alkaloid NPs, can now be produced from yeast after introducing more than twenty genetic changes. NPs are secondary metabolites that are synthesized from primary metabolites as building blocks. For example, aspterric acid is a sesquiterpene, which is synthesized from five-carbon isoprenoid building blocks that are universally used in terpene biosynthesis. The isoprenoid building blocks, IPP and DMAPP, are in turn synthesized from acetyl-CoA, a central metabolite in aerobic respiration, fatty acid biosynthesis, and protein acetylation. Thus, the yield of terpene-derived NPs can be increased through engineering of the host primary metabolism to elevate acetyl-CoA concentrations.In recent years, metabolic engineering and synthetic biology have turned Baker’s yeast into efficient microbial factories. Metabolic engineering approaches, such as ove rexpression of pathway genes to produce NPs, or increasing flux of building blocks, such as acetyl-CoA, can lead to dramatic increases in target compound titers. One milestone example is the production of the plant metabolite artemisinic acid at titers of 25 g/l from yeast, as a sustainable source of the antimalarial compound artemisinin. Artemisinic acid, like aspterric acid, is an oxidized sesquiterpene synthesized by the collaborative action of terpene synthase and a P450 monooxygenase. It is therefore reasonable to expect there is ample room to further increase the titers of aspterric acid from the current levels of ~20 mg/l. Moreover, gene-editing tools have further revolutionized our capability to genetically engineer microorganisms. A suite of recently developed CRISPR-based strain evolution strategies are promising multiplex tools for strain engineering. Other synthetic biology tool kits for yeast, including product compartmentalization and enzyme prospecting, as well as directed evolution of bottleneck enzymes, will help to further increase NP titers.Although some NPs can be directly used in agriculture or medicine, most compounds require further modification to improve their biological activity. A diversified library of NPs can help to illuminate the structure–activity relationships of the compound and allow screening of analogs that are more potent, or that can overcome evolved resistance mechanisms.However, many NP structures are difficult to manipulate chemically and often degrade quickly if chemists try to modify them. Moreover, chemically modified compounds are no longer considered “natural” and can face significant regulatory hurdles. Therefore, engineering of the bio-synthetic pathway to create structural analogs is an attractive alternative to chemical modification or synthesis. This requires a thorough understanding of the microbial NPs bio-synthetic machinery, including the sequence of enzymatic transformations, the mechanisms and substrate flexibilities of individual enzymes. NP biosynthesis usually follows a “linear” sequence of enzymatically catalyzed reactions, reflecting nature’s bio-synthetic logic in constructing a complex molecule. Some of these enzymes are promiscuous and can function out of sequence or use alternative substrates. This allows synthetic biologists to exploit the bio-synthetic machineries for the synthesis of many NPs to produce “unnatural” NPs. One effective method to expand NP structural diversity is through precursor-directed biosynthesis and mutasynthesis . In contrast, de novo biosynthesis of diversified NP molecules can be achieved by mixing and matching enzymes from different bio-synthetic pathways . Combinatorial biosynthesis, which parallels the concept of combinatorial synthesis, is particular successful in bio-synthetic pathways that utilize modular enzymes such as polyketide synthases and nonribosomal peptide synthetases . Individual domains of these “assembly-line” enzymatic machineries canbe inactivated, inserted, or swapped to precisely introduce modifications to the final NP structure.