Shade trees preserve avian insectivore biodiversity on coffee farms in a warming climate

Coffee is an important export in many developing countries, with a global annual trade value of $100 billion. Climate change is projected to drastically reduce the area where coffee is able to be grown. Shade trees may mitigate the effects of climate change through temperature regulation for coffee growth, temperature regulation for pest control, and increase in pest-eating bird diversity. The impact of shade on bird diversity and microclimate on coffee farms has been studied extensively in the Neotropics, but there is a dearth of research in the Paleotropics. I examined the local effects of shade on bird presence and temperature on coffee farms in Kenya and then created regional Maxent models for avian insectivores in East Africa. I adjusted current and future Bioclim layers based on mean differences in temperatures between shade and sun on coffee farms. I then projected models into the future and onto adjusted temperature layers to predict the impact of shade tree removal on climatic suitability for avian insectivores. I found that avian insectivore richness is projected to decrease significantly in the future, as is avian insectivore climatic suitability and suitable area, but shade trees on coffee farms can mediate this. Temperature is not currently a limiting factor for avian insectivores on Kenyan coffee farms, indicating that bird presence is determined by site-level factors. Future temperatures will become a regionally limiting factor for bird distribution in East Africa, but its effects can be potentially mediated through planting and maintaining shade trees on coffee farms

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Behavioral responses of terrestrial mammals to COVID-19 lockdowns

DATA AND MATERIALS AVAILABILITY : The full dataset used in the final analyses (33) and associated code (34) are available at Dryad. A subset of the spatial coordinate datasets is available at Zenodo (35). Certain datasets of spatial coordinates will be available only through requests made to the authors due to conservation and Indigenous sovereignty concerns (see table S1 for more information on data use restrictions and contact information for data requests). These sensitive data will be made available upon request to qualified researchers for research purposes, provided that the data use will not threaten the study populations, such as by distribution or publication of the coordinates or detailed maps. Some datasets, such as those overseen by government agencies, have additional legal restrictions on data sharing, and researchers may need to formally apply for data access. Collaborations with data holders are generally encouraged, and in cases where data are held by Indigenous groups or institutions from regions that are under-represented in the global science community, collaboration may be required to ensure inclusion.COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals’ 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.The Radboud Excellence Initiative, the German Federal Ministry of Education and Research, the National Science Foundation, Serbian Ministry of Education, Science and Technological Development, Dutch Research Council NWO program “Advanced Instrumentation for Wildlife Protection”, Fondation Segré, RZSS, IPE, Greensboro Science Center, Houston Zoo, Jacksonville Zoo and Gardens, Nashville Zoo, Naples Zoo, Reid Park Zoo, Miller Park, WWF, ZCOG, Zoo Miami, Zoo Miami Foundation, Beauval Nature, Greenville Zoo, Riverbanks zoo and garden, SAC Zoo, La Passarelle Conservation, Parc Animalier d’Auvergne, Disney Conservation Fund, Fresno Chaffee zoo, Play for nature, North Florida Wildlife Center, Abilene Zoo, a Liber Ero Fellowship, the Fish and Wildlife Compensation Program, Habitat Conservation Trust Foundation, Teck Coal, and the Grand Teton Association. The collection of Norwegian moose data was funded by the Norwegian Environment Agency, the German Ministry of Education and Research via the SPACES II project ORYCS, the Wyoming Game and Fish Department, Wyoming Game and Fish Commission, Bureau of Land Management, Muley Fanatic Foundation (including Southwest, Kemmerer, Upper Green, and Blue Ridge Chapters), Boone and Crockett Club, Wyoming Wildlife and Natural Resources Trust, Knobloch Family Foundation, Wyoming Animal Damage Management Board, Wyoming Governor’s Big Game License Coalition, Bowhunters of Wyoming, Wyoming Outfitters and Guides Association, Pope and Young Club, US Forest Service, US Fish and Wildlife Service, the Rocky Mountain Elk Foundation, Wyoming Wild Sheep Foundation, Wild Sheep Foundation, Wyoming Wildlife/Livestock Disease Research Partnership, the US National Science Foundation [IOS-1656642 and IOS-1656527, the Spanish Ministry of Economy, Industry and Competitiveness, and by a GRUPIN research grant from the Regional Government of Asturias, Sigrid Rausing Trust, Batubay Özkan, Barbara Watkins, NSERC Discovery Grant, the Federal Aid in Wildlife Restoration act under Pittman-Robertson project, the State University of New York, College of Environmental Science and Forestry, the Ministry of Education, Youth and Sport of the Czech Republic, the Ministry of Agriculture of the Czech Republic, Rufford Foundation, an American Society of Mammalogists African Graduate Student Research Fund, the German Science Foundation, the Israeli Science Foundation, the BSF-NSF, the Ministry of Agriculture, Forestry and Food and Slovenian Research Agency (CRP V1-1626), the Aage V. Jensen Naturfond (project: Kronvildt - viden, værdier og værktøjer), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy, National Centre for Research and Development in Poland, the Slovenian Research Agency, the David Shepherd Wildlife Foundation, Disney Conservation Fund, Whitley Fund for Nature, Acton Family Giving, Zoo Basel, Columbus, Bioparc de Doué-la-Fontaine, Zoo Dresden, Zoo Idaho, Kolmården Zoo, Korkeasaari Zoo, La Passarelle, Zoo New England, Tierpark Berlin, Tulsa Zoo, the Ministry of Environment and Tourism, Government of Mongolia, the Mongolian Academy of Sciences, the Federal Aid in Wildlife Restoration act and the Illinois Department of Natural Resources, the National Science Foundation, Parks Canada, Natural Sciences and Engineering Research Council, Alberta Environment and Parks, Rocky Mountain Elk Foundation, Safari Club International and Alberta Conservation Association, the Consejo Nacional de Ciencias y Tecnología (CONACYT) of Paraguay, the Norwegian Environment Agency and the Swedish Environmental Protection Agency, EU funded Interreg SI-HR 410 Carnivora Dinarica project, Paklenica and Plitvice Lakes National Parks, UK Wolf Conservation Trust, EURONATUR and Bernd Thies Foundation, the Messerli Foundation in Switzerland and WWF Germany, the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions, NASA Ecological Forecasting Program, the Ecotone Telemetry company, the French National Research Agency, LANDTHIRST, grant REPOS awarded by the i-Site MUSE thanks to the “Investissements d’avenir” program, the ANR Mov-It project, the USDA Hatch Act Formula Funding, the Fondation Segre and North American and European Zoos listed at http://www.giantanteater.org/, the Utah Division of Wildlife Resources, the Yellowstone Forever and the National Park Service, Missouri Department of Conservation, Federal Aid in Wildlife Restoration Grant, and State University of New York, various donors to the Botswana Predator Conservation Program, data from collared caribou in the Northwest Territories were made available through funds from the Department of Environment and Natural Resources, Government of the Northwest Territories. The European Research Council Horizon2020, the British Ecological Society, the Paul Jones Family Trust, and the Lord Kelvin Adam Smith fund, the Tanzania Wildlife Research Institute and Tanzania National Parks. The Eastern Shoshone and Northern Arapahoe Fish and Game Department and the Wyoming State Veterinary Laboratory, the Alaska Department of Fish and Game, Kodiak Brown Bear Trust, Rocky Mountain Elk Foundation, Koniag Native Corporation, Old Harbor Native Corporation, Afognak Native Corporation, Ouzinkie Native Corporation, Natives of Kodiak Native Corporation and the State University of New York, College of Environmental Science and Forestry, and the Slovenia Hunters Association and Slovenia Forest Service. F.C. was partly supported by the Resident Visiting Researcher Fellowship, IMéRA/Aix-Marseille Université, Marseille. This work was partially funded by the Center of Advanced Systems Understanding (CASUS), which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament. This article is a contribution of the COVID-19 Bio-Logging Initiative, which is funded in part by the Gordon and Betty Moore Foundation (GBMF9881) and the National Geographic Society.https://www.science.org/journal/sciencehj2023Mammal Research InstituteZoology and Entomolog

Lidar Prediction of Small Mammal Diversity in Wisconsin, USA

Vegetation structure is a crucial component of habitat selection for many taxa, and airborne LiDAR (Light Detection and Ranging) technology is increasingly used to measure forest structure. Many studies have examined the relationship between LiDAR-derived structural characteristics and wildlife, but few have examined those characteristics in relation to small mammals, specifically, small mammal diversity. The aim of this study was to determine if LiDAR could predict small mammal diversity in a temperate-mixed forest community in Northern Wisconsin, USA, and which LiDAR-derived structural variables best predict small mammal diversity. We calculated grid metrics from LiDAR point cloud data for 17 plots in three differently managed sites and related the metrics to small mammal diversity calculated from five months of small mammal trapping data. We created linear models, then used model selection and multi-model inference as well as model fit metrics to determine if LiDAR-derived structural variables could predict small mammal diversity. We found that small mammal diversity could be predicted by LiDAR-derived variables including structural diversity, cover, and canopy complexity as well as site (as a proxy for management). Structural diversity and canopy complexity were positively related with small mammal diversity, while cover was negatively related to small mammal diversity. Although this study was conducted in a single habitat type during a single season, it demonstrates that LiDAR can be used to predict small mammal diversity in this location and possibly can be expanded to predict small mammal diversity across larger spatial scales

Beach Wrack Nutrient Leaching and Community Composition on Gravel Beaches

Beaches world-­‐wide have low primary production due to a stressful environment and action of strong hydrodynamic forces. For this reason, input from marine wrack as well as terrestrial debris is an important source of production in food webs. Wrack can also provide food and habitat for meiofauna that help transfer nutrients up the food web. These interactions have been examined on sandy beaches, but not on gravel beaches. I examined the relationship between beach wrack type, nutrient leaching, and meiofauna colonization on a gravel beach in San Juan County, WA. I used three different types of wrack: Fucus disticus, Zostera marina, and leaves from Prunus avium (Cherry). I conducted two different experiments: a nutrient leaching experiment by measuring nitrate and phosphate leaching from wrack over seven weeks relative to seawater controls with daily tidal simulation, and a community composition experiment using wrack-­‐filled packets placed on a gravel beach. Both nitrate and phosphate showed similar patterns across all wrack types. Nitrate was absorbed by all wrack types at the beginning of the experiment, released in the middle, then absorbed again at the end. Phosphate was absorbed by Zostera and Fucus (though released by cherry) at the beginning, then released by all types of wrack, then all types had similar nutrients as seawater. Diversity of meiofauna was significantly correlated with final weight of the wrack inside the packets. Diversity of meiofauna changed significantly across type of wrack by date sampled. My data suggest that external factors such as bacteria, weather, and decomposition are more important than wrack type in nutrient leaching and community composition

A review of caracal and jungle cat diets across their geographical ranges during 1842–2021

Abstract Co‐occurring carnivore species that are phylogenetically related or of similar size, morphology, and ecological needs often reduce competition by partitioning shared resources through temporal, spatial, and dietary niche segregation via behavioral adaptations. Caracals (Caracal caracal) and jungle cats (Felis chaus) co‐occur in portions of their geographical ranges and are expected to display resource segregation in these ranges. We compiled scat, stomach content, and prey remains found data from published and unpublished sources to summarize information on the diets of caracals and jungle cats across their geographical ranges during 1842–2021. We obtained 63 sources from 26 countries in Europe, Asia, and Africa, in which caracal diet included 151 species while jungle cat diet included 61 species. We found that caracals and jungle cats did not exhibit dietary niche partitioning and had greater dietary similarities in areas of range overlap. We also found that caracals consumed more diverse prey species including prey with greater average body mass compared to jungle cats. Our results suggest that greater prey diversity in areas of range overlap, caracal predation on wide range of prey, and opportunistic feeding behavior that facilitates consumption of more diverse prey species compared to jungle cats, may facilitate co‐occurrence between these two felid species

Elk Raspberry herd growth rate predicted by mean winter temperature and population count.

Model-predicted response of semi-annual Raspberry herd abundance as a function of (A) mean winter temperature in the previous year and (B) elk population count, with 95% credible intervals (shading), Raspberry Island, Alaska, USA, 1958–2020.</p

Island-wide elk age ratios predicted by date of first fall freeze and brown bear abundance.

Model-predicted response of semi-annual island-wide elk age ratios (calves per 100 adult females) as a function of (A) date of first fall freeze in the previous year and (B) brown bear abundance with 95% credible intervals (shading), Afognak and Raspberry islands, Alaska, USA, 1967–2013.</p

Full dataset used to model elk recruitment and abundance, Afognak and Raspberry islands, Alaska, USA, 1958–2020.

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Explanation and parameterization of Bayesian linear (recruitment) and hierarchical logistic Gompertz (abundance) models.

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