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Virtually all agricultural communities worldwide are exposed to agricultural pesticides. Yet, the health consequences of such exposure are poorly understood, and the scientific literature remains ambiguous. Using individual birth and demographic characteristics for over 500 000 birth observations between 1997–2011 in the agriculturally dominated San Joaquin Valley, California, we statistically investigate if residential agricultural pesticide exposure during gestation, by trimester, and by toxicity influences birth weight, gestational length, or birth abnormalities. Overall, our analysis indicates that agricultural pesticide exposure increases adverse birth outcomes by 5–9%, but only among the population exposed to very high quantities of pesticides (e.g., top 5th percentile, i.e., ~4200 kg applied over gestation). Thus, policies and interventions targeting the extreme right tail of the pesticide distribution near human habitation could largely eliminate the adverse birth outcomes associated with agricultural pesticide exposure documented in this study. The health consequences of exposure to pesticides are uncertain and subject to much debate. Here, the effect of exposure during pregnancy is investigated in an agriculturally dominated residential area, showing that an increase in adverse birth outcomes is observed with very high levels of pesticide exposure.

The increase in agricultural production over the past 40 y has greatly altered land-use patterns, often resulting in simplified landscapes composed of large swaths of monocultures separated by small fragments of natural lands. These simplified landscapes may be more susceptible to insect pest pressure because of the loss of natural enemies and the increased size and connectivity of crop resources, and a recent analysis from a single year (2007) suggests this increased susceptibility results in increased insecticide use. I broaden the temporal analysis of this connection between landscape simplification and insecticide use by examining cross-sectional and panel data models from multiple decades (US Department of Agriculture Census of Agriculture years 2007, 2002, 1997, 1992, 1987) for seven Midwestern states composed of over 560 counties. I find that although the proportion of county in cropland—my metric for landscape simplification—was positively correlated with insecticide use in 2007, this relationship is absent or reversed in prior census years and when all years are analyzed together. This broader temporal perspective suggests that landscape simplification has inconsistent effects on insecticide use and that multiyear studies will be key to unlocking the true drivers of variation in insecticide application.

Notwithstanding popular perception, the environmental impacts of organic agriculture, particularly with respect to pesticide use, are not well established. Fueling the impasse is the general lack of data on comparable organic and conventional agricultural fields. We identify the location of ~9,000 organic fields from 2013 to 2019 using field-level crop and pesticide use data, along with state certification data, for Kern County, CA, one of the US’ most valuable crop producing counties. We parse apart how being organic relative to conventional affects decisions to spray pesticides and, if spraying, how much to spray using both raw and yield gap-adjusted pesticide application rates, based on a global meta-analysis. We show the expected probability of spraying any pesticides is reduced by about 30 percentage points for organic relative to conventional fields, across different metrics of pesticide use including overall weight applied and coarse ecotoxicity metrics. We report little difference, on average, in pesticide use for organic and conventional fields that do spray, though observe substantial crop-specific heterogeneity. There is much uncertainty on use and impact of pesticides in organic agriculture. Here, the authors compare pesticide use in conventionally and organically managed fields in Kern County (US), finding that organic fields are less likely to be treated but, when they are, they receive similar pesticide amount as the conventional fields.

Fluctuations in extreme weather such as a shift from an extreme dry to an extreme wet year, termed hydroclimate volatility or precipitation whiplash, present potential challenges and opportunities for agricultural production in water-limited regions. Yet, whether the sudden profusion of precipitation or the presence of flooding has a net positive or negative impact on agricultural production, particularly agricultural pests, is understudied. Using a difference-in-difference approach applied to field-level pesticides from ∼13 000 field/y observations in Kern County, CA, we evaluate how precipitation whiplash impacted agricultural pest control. We show the wet year had an anticipated bump in pesticides targeting molds and weeds and an unanticipated decrease in insecticides. Yet, there was little effect of on-field standing water on pesticide use. County-wide crop statistics, available for a subset of crops, were also similar across years, with similar area harvested, yields and total value in the historically wet versus the prior dry year. Despite the historic nature of the drought and proceeding rainfall events, farmers, on average, appeared to adapt to precipitation whiplash successfully. Given the increasing prevalence of precipitation whiplash as well as policy efforts to increase groundwater recharge through on-field flooding in wet years, such null effects suggest the benefits to harnessing extreme precipitation do not imply major costs for pest control.

Single species conservation unites disparate partners for the conservation of one species. However, there are widespread concerns that single species conservation biases conservation efforts towards charismatic species at the expense of others. Here we investigate the extent to which sage grouse (Centrocercus sp.) conservation, the largest public-private conservation effort for a single species in the US, provides protections for other species from localized and landscape-scale threats. We compared the coverage provided by sage grouse Priority Areas for Conservation (PACs) to 81 sagebrush-associated vertebrate species distributions with potential coverage under multi-species conservation prioritization generated using the decision support tool Zonation. PACs. We found that the current PAC prioritization approach was not statistically different from a diversity-based prioritization approach and covers 23.3% of the landscape, and 24.8%, on average, of the habitat of the 81 species. The proportion of each species distribution at risk was lower inside PACs as compared to the region as a whole, even without management (land use change 30% lower, cheatgrass invasion 19% lower). Whether or not bias away from threat represents the most efficient use of conservation effort is a matter of considerable debate, though may be pragmatic in this landscape where capacity to address these threats is limited. The approach outlined here can be used to evaluate biological equitability of protections provided by flagship species in other settings.

Infectious diseases are rapidly emerging and many are increasing in incidence across the globe. Processes of land‐use change, notably habitat loss and fragmentation, have been widely implicated in the emergence and spread of zoonoses such as Lyme disease, yet evidence remains equivocal. Here, we discuss and apply an innovative approach from the social sciences; instrumental variables, which seeks to tease out causality from observational data. Using this approach, we revisit the effect of forest fragmentation on Lyme disease incidence, focusing on human interaction with fragmented landscapes. Although human interaction with infected ticks is of clear and fundamental importance to human disease incidence, human activities that influence exposure have been largely overlooked in ecology literature. Using county‐level land‐use and Lyme disease incidence data for ~800 counties from the northeastern United States over the span of a decade, we illustrate (a) that human interaction with fragmented forest landscapes reliably predicts Lyme disease incidence, while ecological measures of forest fragmentation alone are unreliable predictors and (b) that identifying the effect of forest fragmentation on human disease entails addressing the feedback between Lyme disease risk and human decisions to avoid interaction with high‐risk landscapes. Synthesis and applications. Our innovative approach and novel results help to clarify the equivocal literature on the effects of forest fragmentation on Lyme disease and illustrate the key role that human behaviour may be playing in the ecology of Lyme disease in North America. Accounting for human activity and behaviour in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease, as well as actionable intervention strategies to reduce disease burden in a changing world. For example, our model results indicate that forest fragmentation by human settlement increases Lyme disease incidence, which has practical implications for land‐use policy aimed at disease reduction. Specifically, our model suggests land‐use regulations that reduce parcel size would be an actionable approach to reduce Lyme disease transmission for policymakers concerned about increasing Lyme disease incidence in the northeastern United States. Our innovative approach and novel results help to clarify the equivocal literature on the effects of forest fragmentation on Lyme disease and illustrate the key role that human behaviour may be playing in the ecology of Lyme disease in North America. Accounting for human activity and behaviour in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease, as well as actionable intervention strategies to reduce disease burden in a changing world. For example, our model results indicate that forest fragmentation by human settlement increases Lyme disease incidence, which has practical implications for land‐use policy aimed at disease reduction. Specifically, our model suggests land‐use regulations that reduce parcel size would be an actionable approach to reduce Lyme disease transmission for policymakers concerned about increasing Lyme disease incidence in the northeastern United States.

Pesticide usage in the U.S. has more than doubled since 1960, raising concerns on its human and ecological health implications. The literature indicates that pesticide application rates for the same crop vary widely across geographies, while the magnitude of variation and its underlying drivers are poorly understood. Here, we present a new dataset on farm-level pesticide application for maize in the U.S. Using the dataset, we derived four human and ecological health impact metrics, (1) environmental impact quotient, (2) acute hazard quotient, (3) chronic hazard quotient, and (4) freshwater ecotoxicity, and analyzed their relationships with various climatic and biophysical factors including precipitation, growing degree days (GDD), soil conductivity, and irrigation practices. Our results show that the potential human and ecological health impact of pesticide use per unit maize harvested vary by 5-7 orders of magnitude across the 891 maize-producing counties in the U.S. All four best-fitted models are statistically significant, explaining 21% to 28% of the variations in the impact intensities across counties. Among the climatic and biophysical factors examined, GDD was the most significant variable for all four metrics. This suggests that climate change may adversely affect human and ecological health impact intensities of pesticide use for maize, which may increase 22%-471% by 2100 under the 2 °C warming scenario. Besides, electrical conductivity and the percentage of cropland irrigated were significant for multiple impacts. The large remaining variability unexplained by our analysis suggests that behavioral and management factors, which were not captured in our model, play a crucial role in pesticide use, calling for the interventions targeting them.

Agricultural landscape intensification has enabled food production to meet growing demand. However, there are concerns that more simplified cropland with lower crop diversity, less noncrop habitat, and larger fields results in increased use of pesticides due to a lack of natural pest control and more homogeneous crop resources. Here, we use data on crop production and insecticide use from over 100,000 field-level observations from Kern County, California, encompassing the years 2005–2013 to test if crop diversity, field size, and cropland extent affect insecticide use in practice. Overall, we find that higher crop diversity does reduce insecticide use, but the relationship is strongly influenced by the differences in crop types between diverse and less diverse landscapes. Further, we find insecticide use increases with increasing field size. The effect of cropland extent is distance-dependent, with nearby cropland decreasing insecticide use, whereas cropland further away increases insecticide use. This refined spatial perspective provides unique understanding of how different components of landscape simplification influence insecticide use over space and for different crops. Our results indicate that neither the traditionally conceived “simplified” nor “complex” agricultural landscape is most beneficial to reducing insecticide inputs; reality is far more complex.

Quantifying ecosystem services provided by mobile species like insectivorous bats remains a challenge, particularly in understanding where and how these services vary over space and time. Bats are known to offer valuable ecosystem services, such as mitigating insect pest damage to crops, reducing pesticide use, and reducing nuisance pest populations. However, determining where bats forage is difficult to monitor. In this study, we use a weather‐radar‐based bat‐monitoring algorithm to estimate bat foraging distributions during the peak season of 2019 in California's Northern Central Valley. This region is characterized by valuable agricultural crops and significant populations of both crop and nuisance pests, including midges, moths, mosquitos, and flies. Our results show that bat activity is high but unevenly distributed, with rice fields experiencing significantly elevated activity compared to other land cover types. Specifically, bat activity over rice fields is 1.5 times higher than over any other land cover class and nearly double that of any other agricultural land cover. While irrigated rice fields may provide abundant prey, wetland and water areas showed less than half the bat activity per hectare compared to rice fields. Controlling for land cover type, we found bat activity significantly associated with higher flying insect abundance, indicating that bats forage in areas where crop and nuisance pests are likely to be found. This study demonstrates the effectiveness of radar‐based bat monitoring in identifying where and when bats provide ecosystem services. This study uses a weather‐radar‐based monitoring algorithm to track bat foraging in California's Northern Central Valley, revealing high bat activity concentrated around rice fields. Bat presence was significantly linked to areas of high mosquito abundance and West Nile Virus transmission risk, highlighting the potential of bats to provide ecosystem services in agriculture and public health.

ContextGlobal environmental change is expected to dramatically affect agricultural crop production through a myriad of pathways. One important and thus far poorly understood impact is the effect of land cover and climate change on agricultural insect pests and insecticides.ObjectivesHere we address the following three questions: (1) how do landscape complexity and weather influence present-day insecticide use, (2) how will changing landscape characteristics and changing climate influence future insecticide use, and how do these effects manifest for different climate and land cover projections? and (3) what are the most important drivers of changing insecticide use?MethodsWe use panel models applied to county-level agriculture, land cover, and weather data in the US to understand how landscape composition and configuration, weather, and farm characteristics impact present-day insecticide use. We then leverage forecasted changes in land cover and climate under different future scenarios to predict insecticide use in 2050.ResultsWe find different future scenarios—through modifications in both landscape and climate conditions—increase the amount of area treated by ~ 4–20% relative to 2017, with regionally heterogeneous impacts. Of note, we report large farms are more influential than large crop patches and increased winter minimum temperature is more influential than increased summer maximum temperature. However, our results suggest the most important determinants of future insecticide use are crop composition and farm size, variables for which future forecasts are sparse.ConclusionsBoth landscape and climate change are expected to increase future insecticide use. Yet, crop composition and farm size are highly influential, data-poor variables. Better understanding of future crop composition and farm economics is necessary to effectively predict and mitigate increases in pesticide use.