Niche partitioning in an assemblage of granivorous rodents, and the challenge of community-level conservation.

Coexistence of competing species in the same foraging guild has long puzzled ecologists. In particular, how do small subordinate species persist with larger dominant competitors? This question becomes particularly important when conservation interventions, such as reintroduction or translocation, become necessary for the smaller species. Exclusion of dominant competitors might be necessary to establish populations of some endangered species. Ultimately, however, the goal should be to conserve whole communities. Determining how subordinate species escape competitive exclusion in intact communities could inform conservation decisions by clarifying the ecological conditions and processes required for coexistence at local or regional scales. We tested for spatial and temporal partitioning among six species of native, granivorous rodents using null models, and characterized the microhabitat of each species using resource-selection models. We found that the species' nightly activity patterns are aggregated temporally but segregated spatially. As expected, we found clear evidence that the larger-bodied kangaroo rats drive spatial partitioning, but we also found species-specific microhabitat associations, which suggests that habitat heterogeneity is part of what enables these species to coexist. Restoration of natural disturbance regimes that create habitat heterogeneity, and selection of translocation sites without specific competitors, are among the management recommendations to consider in this case. More generally, this study highlights the need for a community-level approach to conservation and the usefulness of basic ecological data for guiding management decisions

Adding pattern and process to eco-evo theory and applications

Eco-evolutionary dynamics result when interacting biological forces simultaneously produce demographic and genetic population responses. Eco-evolutionary simulators traditionally manage complexity by minimizing the influence of spatial pattern on process. However, such simplifications can limit their utility in real-world applications. We present a novel simulation modeling approach for investigating eco-evolutionary dynamics, centered on the driving role of landscape pattern. Our spatially-explicit, individual-based mechanistic simulation approach overcomes existing methodological challenges, generates new insights, and paves the way for future investigations in four focal disciplines: Landscape Genetics, Population Genetics, Conservation Biology, and Evolutionary Ecology. We developed a simple individual-based model to illustrate how spatial structure drives eco-evo dynamics. By making minor changes to our landscape’s structure, we simulated continuous, isolated, and semi-connected landscapes, and simultaneously tested several classical assumptions of the focal disciplines. Our results exhibit expected patterns of isolation, drift, and extinction. By imposing landscape change on otherwise functionally-static eco-evolutionary models, we altered key emergent properties such as gene-flow and adaptive selection. We observed demo-genetic responses to these landscape manipulations, including changes in population size, probability of extinction, and allele frequencies. Our model also demonstrated how demo-genetic traits, including generation time and migration rate, can arise from a mechanistic model, rather than being specified a priori. We identify simplifying assumptions common to four focal disciplines, and illustrate how new insights might be developed in eco-evolutionary theory and applications by better linking biological processes to landscape patterns that we know influence them, but that have understandably been left out of many past modeling studies

Adding pattern and process to eco-evo theory and applications.

Eco-evolutionary dynamics result when interacting biological forces simultaneously produce demographic and genetic population responses. Eco-evolutionary simulators traditionally manage complexity by minimizing the influence of spatial pattern on process. However, such simplifications can limit their utility in real-world applications. We present a novel simulation modeling approach for investigating eco-evolutionary dynamics, centered on the driving role of landscape pattern. Our spatially-explicit, individual-based mechanistic simulation approach overcomes existing methodological challenges, generates new insights, and paves the way for future investigations in four focal disciplines: Landscape Genetics, Population Genetics, Conservation Biology, and Evolutionary Ecology. We developed a simple individual-based model to illustrate how spatial structure drives eco-evo dynamics. By making minor changes to our landscape's structure, we simulated continuous, isolated, and semi-connected landscapes, and simultaneously tested several classical assumptions of the focal disciplines. Our results exhibit expected patterns of isolation, drift, and extinction. By imposing landscape change on otherwise functionally-static eco-evolutionary models, we altered key emergent properties such as gene-flow and adaptive selection. We observed demo-genetic responses to these landscape manipulations, including changes in population size, probability of extinction, and allele frequencies. Our model also demonstrated how demo-genetic traits, including generation time and migration rate, can arise from a mechanistic model, rather than being specified a priori. We identify simplifying assumptions common to four focal disciplines, and illustrate how new insights might be developed in eco-evolutionary theory and applications by better linking biological processes to landscape patterns that we know influence them, but that have understandably been left out of many past modeling studies

Evaluating potential effects of solar power facilities on wildlife from an animal behavior perspective

Solar power is a renewable energy source with great potential to help meet increasing global energy demands and reduce our reliance on fossil fuels. However, research is scarce on how solar facilities affect wildlife. With input from professionals in ecology, conservation, and energy, we conducted a research-prioritization process and identified key questions needed to better understand impacts of solar facilities on wildlife. We focused on animal behavior, which can be used to identify population responses before mortality or other fitness consequences are documented. Behavioral studies can also offer approaches to understand the mechanisms leading to negative interactions (e.g., collision, singeing, avoidance) and provide insight into mitigating effects. Here, we review how behavioral responses to solar facilities, including perception, movement, habitat use, and interspecific interactions are priority research areas. Addressing these themes will lead to a more comprehensive understanding of the effects of solar power on wildlife and guide future mitigation

Teaching Evolutionary Concepts in Elementary School

Charles Darwin would be pleased to know that elementary school children in states that have adopted the Next Generation Science Standards (NGSS) are expected to demonstrate their understanding of several core evolutionary concepts, including trait variation and inheritance, fossils and extinct organisms, common ancestry, natural selection, and adaptation. However, he might also wonder how this is accomplished in the demanding 21st-century science curriculum. In files linked to this article, we provide four lesson plans – with engaging examples, natural selection games, and other interactive activities – that were designed to cover the NGSS Disciplinary Core Ideas in evolutionary biology for grades 3–5, in two one-hour lessons. The lesson plans were developed by college students under the guidance of evolutionary biologists and in consultation with elementary school teachers, and then field tested in elementary school classrooms, as described in an accompanying research article