The pollination services provided by bees are essential for supporting natural and agricultural ecosystems. However, bee population declines have been documented across the world. Many of the factors ...known to undermine bee health (e.g., poor nutrition) can decrease immunocompetence and, thereby, increase bees' susceptibility to diseases. Given the myriad of stressors that can exacerbate disease in wild bee populations, assessments of the relative impact of landscape habitat conditions on bee pathogen prevalence are needed to effectively conserve pollinator populations. Herein, we assess how landscape-level conditions, including various metrics of floral/nesting resources, insecticides, weather, and honey bee (Apis mellifera) abundance, drive variation in wild bumble bee (Bombus impatiens) pathogen loads. Specifically, we screened 890 bumble bee workers from varied habitats in Pennsylvania, USA for three pathogens (deformed wing virus, black queen cell virus, and Vairimorpha (= Nosema) bombi), Defensin expression, and body size. Bumble bees collected within low-quality landscapes exhibited the highest pathogen loads, with spring floral resources and nesting habitat availability serving as the main drivers. We also found higher loads of pathogens where honey bee apiaries are more abundant, a positive relationship between Vairimorpha loads and rainfall, and differences in pathogens by geographic region. Collectively, our results highlight the need to support high-quality landscapes (i.e., those with abundant floral/nesting resources) to maintain healthy wild bee populations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Bees are important pollinators of numerous crops, and monitoring their abundance and diversity in commercial agricultural ecosystems is of increasing importance due to pollinator declines. In ...season-long field studies conducted in Pennsylvania during 2011–2013, we evaluated five different bee monitoring passive traps—three pan traps (blue, yellow, and white) and two vane traps (blue and yellow)—for their effectiveness and utility for monitoring bees in commercial apple orchards. Traps were placed prebloom and were monitored weekly until the end of crop season (mid-October). We recorded 14,770 bees comprising 118 species, 27 genera, and five families. The most abundant species were Augochlora pura (Say) (34.4% of total), Ceratina calcarata Robertson (15.5%), Bombus vagans Smith (7.8%), Bombus impatiens Cresson (6.4%), and Apis mellifera L. (4.3%). Bee abundance was highly variable among trap types across the three years and during the bloom and postbloom period. Blue vane traps were found to be the most effective trap type, with significantly higher rates of per-sample species accumulation than all other traps. Species richness estimates were highest for the blue vane and blue pan traps. This study reveals the utility and effectiveness of various traps for studying abundance and diversity of pollinator bees in commercially managed apple orchards. It also provides baseline information about the bee community found during the bloom and postbloom periods in Pennsylvania apple orchards that can be used to measure changes in bee community structure and abundance due to conservation efforts, such as reduced risk IPM programs, habitat management, and augmentation.
Yield stability is fundamental to global food security in the face of climate change, and better strategies are needed for buffering crop yields against increased weather variability. Regional- scale ...analyses of yield stability can support robust inferences about buffering strategies for widely-grown staple crops, but have not been accomplished. We present a novel analytical approach, synthesizing 2000-2014 data on weather and soil factors to quantify their impact on county-level maize yield stability in four US states that vary widely in these factors (Illinois, Michigan, Minnesota and Pennsylvania). Yield stability is quantified as both 'downside risk' (minimum yield potential, MYP) and 'volatility' (temporal yield variability). We show that excessive heat and drought decreased mean yields and yield stability, while higher precipitation increased stability. Soil water holding capacity strongly affected yield volatility in all four states, either directly (Minnesota and Pennsylvania) or indirectly, via its effects on MYP (Illinois and Michigan). We infer that factors contributing to soil water holding capacity can help buffer maize yields against variable weather. Given that soil water holding capacity responds (within limits) to agronomic management, our analysis highlights broadly relevant management strategies for buffering crop yields against climate variability, and informs region-specific strategies.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Due to the key role surrounding landscape plays in ecological processes, a detailed characterization of land cover is critical for researchers and conservation practitioners. Unfortunately, in the ...United States, land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this gap, we merged two datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce integrated 'Spatial Products for Agriculture and Nature' (SPAN). Our workflow leveraged strengths of the NVC and the CDL to create detailed rasters comprising both agricultural and natural land-cover classes. We generated SPAN annually from 2012-2021 for the conterminous United States, quantified agreement and accuracy of SPAN, and published the complete computational workflow. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved most conflicts, leaving only 0.6% of agricultural pixels unresolved in SPAN. These ready-to-use rasters characterizing both agricultural and natural land cover will be widely useful in environmental research and management.
Wild pollinators supply essential, historically undervalued pollination services to crops and other flowering plant communities with great potential to ensure agricultural production against the loss ...of heavily relied upon managed pollinators. Local plant communities provision wild bees with crucial floral and nesting resources, but the distribution of floristic diversity among habitat types in North American agricultural landscapes and its effect on pollinators are diverse and poorly understood, especially in orchard systems. We documented floristic diversity in typical mid-Atlantic commercial apple (Malus domestica Borkh.) orchards including the forest and orchard-forest edge (“edge”) habitats surrounding orchards in a heterogeneous landscape in south-central Pennsylvania, USA. We also assessed the correlation between plant richness and orchard pollinator communities. In this apple production region, edge habitats are the most species rich, supporting 146 out of 202 plant species recorded in our survey. Plant species richness in the orchard and edge habitats were significant predictors of bee species richness and abundance in the orchard, as well as landscape area of the forest and edge habitats. Both the quantity and quality of forest and edges close to orchards play a significant role in provisioning a diverse wild bee community in this agroecosystem.
Abstract
Wild and managed pollinators are essential to food production and the function of natural ecosystems; however, their populations are threatened by multiple stressors including pesticide use. ...Because pollinator species can travel hundreds to thousands of meters to forage, recent research has stressed the importance of evaluating pollinator decline at the landscape scale. However, scientists’ and conservationists’ ability to do this has been limited by a lack of accessible data on pesticide use at relevant spatial scales and in toxicological units meaningful to pollinators. Here, we synthesize information from several large, publicly available datasets on pesticide use patterns, land use, and toxicity to generate novel datasets describing pesticide use by active ingredient (kg, 1997–2017) and aggregate insecticide load (kg and honey bee lethal doses, 1997–2014) for state-crop combinations in the contiguous U.S. Furthermore, by linking pesticide datasets with land-use data, we describe a method to map pesticide indicators at spatial scales relevant to pollinator research and conservation.
Introduction
There is overwhelming evidence of declines in native bee populations and therefore a need for increased monitoring to track these declines and assist in conservation and restoration ...efforts. Bees can be sampled non-lethally through visual surveys (e.g., distance transects) or lethally through active (e.g., hand netting) or passive (e.g., traps that lure insects from afar) methods. These lethal methods suffer from imperfect detection that is difficult to account for and can confound inferences about habitat characteristics. Additionally, evidence suggests that lethal sampling methods can even invert habitat quality patterns such that high-quality sites yield fewer individuals and low-quality sites yield more individuals.
Methods
To study potential biases associated with imperfect detection, we used hierarchical density estimation with visual surveys to estimate density of bees within 40 young forest patches across Pennsylvania, USA. We surveyed bee communities non-lethally using visual surveys and lethally using blue-vane traps and bee bowls every two weeks between May and September 2019. We collected data on blooming flowers, vegetation structure, and weather during times of survey.
Results
We found that bee densities estimated from distance transects had a positive relationship with floral resource availability. In contrast, abundance measured via bee bowls and blue-vane traps had no relationship, or sometimes even negative trends with habitat quality, including floral resource availability. Raw bee counts within 2-m of the transect always correlated with modeled densities, showing that some methods do not share the biases of attractive traps.
Discussion
Our study demonstrates that failing to account for imperfect detection can impact the interpretation of pollinator surveys and adds to a growing body of literature that acknowledges the value of distance sampling for insects like bees to better understand species’ habitat needs and to monitor populations for conservation.
Context
The positive correlation between landscape area of semi-natural habitat and wild pollinator richness and abundance in agroecosystems has been well studied. However, we lack a deep ...understanding of local scale floral resource and nest provisioning for wild bees necessary to optimize implementation of pollinator conservation practices.
Objectives
The primary objective of this study was to use a spatially interactive landscape pollination model (hereafter, the Lonsdorf model) to represent field scale spatial patterns of wild bee abundance and richness within a heterogeneous landscape in the mid-Atlantic USA.
Methods
We parameterized the Lonsdorf model with high resolution aerial imagery and insight from a previously published floristic study. To test the Lonsdorf model predictions, field studies were conducted to measure wild bee abundance and species richness in apple orchards as a function of distance from a forest edge.
Results
Field measurements indicated apple pollinator abundance and species richness significantly decreased with increasing distance from the forest edge. The Lonsdorf model pollination service score was highly sensitive to changes in resource provisioning in orchard and non-crop areas, and including resource rich forest and forest edge habitats in the model significantly improved pollination service estimates.
Conclusions
We demonstrated a novel application of the Lonsdorf model at a field scale to predict trends in pollination service provisioning as a factor of local habitat features. With sufficiently detailed inputs, the Lonsdorf model is a promising tool to quantify field scale pollination service deficits, guiding more cost effective habitat supplementation and other conservation efforts.
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EMUNI, FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
Wild bees, like many other taxa, are threatened by land‐use and climate change, which, in turn, jeopardizes pollination of crops and wild plants. Understanding how land‐use and climate factors ...interact is critical to predicting and managing pollinator populations and ensuring adequate pollination services, but most studies have evaluated either land‐use or climate effects, not both. Furthermore, bee species are incredibly variable, spanning an array of behavioral, physiological, and life‐history traits that can increase or decrease resilience to land‐use or climate change. Thus, there are likely bee species that benefit, while others suffer, from changing climate and land use, but few studies have documented taxon‐specific trends. To address these critical knowledge gaps, we analyzed a long‐term dataset of wild bee occurrences from Maryland, Delaware, and Washington DC, USA, examining how different bee genera and functional groups respond to landscape composition, quality, and climate factors. Despite a large body of literature documenting land‐use effects on wild bees, in this study, climate factors emerged as the main drivers of wild‐bee abundance and richness. For wild‐bee communities in spring and summer/fall, temperature and precipitation were more important predictors than landscape composition, landscape quality, or topography. However, relationships varied substantially between wild‐bee genera and functional groups. In the Northeast USA, past trends and future predictions show a changing climate with warmer winters, more intense precipitation in winter and spring, and longer growing seasons with higher maximum temperatures. In almost all of our analyses, these conditions were associated with lower abundance of wild bees. Wild‐bee richness results were more mixed, including neutral and positive relationships with predicted temperature and precipitation patterns. Thus, in this region and undoubtedly more broadly, changing climate poses a significant threat to wild‐bee communities.
To address critical knowledge gaps, we analyzed a long‐term dataset of wild bee occurrences from Maryland, Delaware, and Washington DC, USA, examining how different bee genera and functional groups respond to landscape composition, quality, and climate factors. Despite a large body of literature documenting land‐use effects on wild bees, in this study, climate factors emerged as the main drivers of wild‐bee abundance and richness.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Managed honey bee (Apis mellifera L.) colonies in North America and Europe have experienced high losses in recent years, which have been linked to weather conditions, lack of quality forage, and high ...parasite loads, particularly the obligate brood parasite, Varroa destructor. These factors may interact at various scales to have compounding effects on honey bee health, but few studies have been able to simultaneously investigate the effects of weather conditions, landscape factors, and management of parasites. We analyzed a dataset of 3,210 survey responses from beekeepers in Pennsylvania from 2017 to 2022 and combined these with remotely sensed weather variables and novel datasets about seasonal forage availability into a Random Forest model to investigate drivers of winter loss. We found that beekeepers who used treatment against Varroa had higher colony survival than those who did not treat. Moreover, beekeepers who used multiple types of Varroa treatment had higher colony survival rates than those who used 1 type of treatment. Our models found weather conditions are strongly associated with survival, but multiple-treatment type colonies had higher survival across a broader range of climate conditions. These findings suggest that the integrated pest management approach of combining treatment types can potentially buffer managed honey bee colonies from adverse weather conditions.
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