Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis.

Understanding how spatially variable selection shapes adaptation is an area of long-standing interest in evolutionary ecology. Recent meta-analyses have quantified the extent of local adaptation, but the relative importance of abiotic and biotic factors in driving population divergence remains poorly understood. To address this gap, we combined a quantitative meta-analysis and a qualitative metasynthesis to (1) quantify the magnitude of local adaptation to abiotic and biotic factors and (2) characterize major themes that influence the motivation and design of experiments that seek to test for local adaptation. Using local-foreign contrasts as a metric of local adaptation (or maladaptation), we found that local adaptation was greater in the presence than in the absence of a biotic interactor, especially for plants. We also found that biotic environments had stronger effects on fitness than abiotic environments when ignoring whether those environments were local versus foreign. Finally, biotic effects were stronger at low latitudes, and abiotic effects were stronger at high latitudes. Our qualitative analysis revealed that the lens through which local adaptation has been examined differs for abiotic and biotic factors. It also revealed biases in the design and implementation of experiments that make quantitative results challenging to interpret and provided directions for future research.

Quantifying the impacts of future sea level rise on nesting sea turtles in the southeastern United States.

Sandy beaches, a necessary habitat for nesting sea turtles, are increasingly under threat as they become squeezed between human infrastructure and shorelines that are changing as a result of rising sea levels. Forecasting where shifting sandy beaches will be obstructed and how that directly impacts coastal nesting species is necessary for successful conservation and management. Predicting changes to coastal nesting areas is difficult because of a lack of consensus on the physical attributes used by females in nesting site choice. In this study, we leveraged long-term data sets of nesting localities for two sea turtle species, loggerhead sea turtle, Caretta caretta, and green sea turtle, Chelonia mydas, within four barrier island National Seashores in the southeastern United States to predict future nesting beach area based on where these species currently nest in relation to mean high water. We predicted the future location of nesting areas based on a sea level rise scenario for 2100 and quantified how impervious surfaces will inhibit future beach movement, which will impact both the total available nesting area and the percentage of nesting area predicted to flood following a hurricane-related storm surge. Contrary to our expectations, those barrier islands with the greatest levels of human infrastructure were not projected to experience the greatest percentage of sea turtle nesting area loss due to sea level rise or storm surge events. Notably, loss of nesting beach areas will not have equal impacts across the four Seashores; the Seashore projected to have the least amount of total nesting area lost and percentage nesting area lost currently has the highest nesting densities of our two study species, suggesting that even low levels of beach loss could have substantial impacts on future nesting densities and disproportionate impacts on the population growth of these species. Our novel method of estimating current and future nesting beach area can be broadly applied to studies requiring a bounded area that encompasses the part of a beach used by nesting coastal species and will be useful in comparing future global nesting densities and population trajectories under projected future sea level rise and storm surge activity.