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ABSTRACT 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. 

Abstract Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture’s hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California’s Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond. 

Abstract 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. 

Abstract Mosquito-borne diseases (MBD) threaten over 80% of the world’s population, and are increasing in intensity and shifting in geographical range with land use and climate change. Mitigation hinges on understanding disease-specific risk profiles, but current risk maps are severely limited in spatial resolution. One important determinant of MBD risk is temperature, and though the relationships between temperature and risk have been extensively studied, maps are often created using sparse data that fail to capture microclimatic conditions. Here, we leverage high resolution land surface temperature (LST) measurements, in conjunction with established relationships between air temperature and MBD risk factors like mosquito biting rate and transmission probability, to produce fine resolution (70 m) maps of MBD risk components. We focus our case study on West Nile virus (WNV) in the San Joaquin Valley of California, where temperatures vary widely across the day and the diverse agricultural/urban landscape. We first use field measurements to establish a relationship between LST and air temperature, and apply it to Ecosystem Spaceborne Thermal Radiometer Experiment data (2018–2020) in peak WNV transmission months (June–September). We then use the previously derived equations to estimate spatially explicit mosquito biting and WNV transmission rates. We use these maps to uncover significant differences in risk across land cover types, and identify the times of day which contribute to high risk for different land covers. Additionally, we evaluate the value of high resolution spatial and temporal data in avoiding biased risk estimates due to Jensen’s inequality, and find that using aggregate data leads to significant biases of up to 40.5% in the possible range of risk values. Through this analysis, we show that the synergy between novel remote sensing technology and fundamental principles of disease ecology can unlock new insights into the spatio-temporal dynamics of MBDs. 

Genetically modified (GM) crops have been adopted by some of the world’s leading agricultural nations, but the full extent of their environmental impact remains largely unknown. Although concerns regarding the direct environmental effects of GM crops have declined, GM crops have led to indirect changes in agricultural practices, including pesticide use, agricultural expansion, and cropping patterns, with profound environmental implications. Recent studies paint a nuanced picture of these environmental impacts, with mixed effects of GM crop adoption on biodiversity, deforestation, and human health that vary with the GM trait and geographic scale. New GM or gene-edited crops with different traits would likely have different environmental and human health impacts. 

The environmental impacts of organic agriculture are only partially understood and whether such practices have spillover effects on pests or pest control activity in nearby fields remains unknown. Using about 14,000 field observations per year from 2013 to 2019 in Kern County, California, we postulate that organic crop producers benefit from surrounding organic fields decreasing overall pesticide use and, specifically, pesticides targeting insect pests. Conventional fields, by contrast, tend to increase pesticide use as the area of surrounding organic production increases. Our simulation suggests that spatially clustering organic cropland can entirely mitigate spillover effects that lead to an increase in net pesticide use. 

Human–wildlife conflict is an important factor in the modern biodiversity crisis and has negative effects on both humans and wildlife (such as property destruction, injury, or death) that can impede conservation efforts for threatened species. Effectively addressing conflict requires an understanding of where it is likely to occur, particularly as climate change shifts wildlife ranges and human activities globally. Here, we examine how projected shifts in cropland density, human population density, and climatic suitability—three key drivers of human–elephant conflict—will shift conflict pressures for endangered Asian and African elephants to inform conflict management in a changing climate. We find that conflict risk (cropland density and/or human population density moving into the 90th percentile based on current-day values) increases in 2050, with a larger increase under the high-emissions “regional rivalry” SSP3 - RCP 7.0 scenario than the low-emissions “sustainability” SSP1 - RCP 2.6 scenario. We also find a net decrease in climatic suitability for both species along their extended range boundaries, with decreasing suitability most often overlapping increasing conflict risk when both suitability and conflict risk are changing. Our findings suggest that as climate changes, the risk of conflict with Asian and African elephants may shift and increase and managers should proactively mitigate that conflict to preserve these charismatic animals. 

A replication package for the article The impact of genetically modified crops on bird diversity.