Response of Anurans to Wetland Restoration on a Midwestern Agricultural Landscape

Broad-scale predictions of herpetofauna occupancy and colonization in an agriculturally dominated landscape

Predictions of species occurrence allow land managers to focus conservation efforts on locations where species are most likely to occur. Such analyses are rare for herpetofauna compared to other taxa, despite increasing evidence that herptile populations are declining because of landcover change and habitat fragmentation. Our objective was to create predictions of occupancy and colonization probabilities for 15 herptiles of greatest conservation need in Iowa. From 2006-2014, we surveyed 295 properties throughout Iowa for herptile presence using timed visual-encounter surveys, coverboards, and aquatic traps. Data were analyzed using robust design occupancy modeling with landscape-level covariates. Occupancy ranged from 0.01 (95% CI = -0.01, 0.03) for prairie ringneck snake (Diadophis punctatus arnyi) to 0.90 (95% CI = 0.898, 0.904) for northern leopard frog (Lithobates pipiens). Occupancy for most species correlated to landscape features at the 1-km scale. General patterns of species' occupancy included negative effects of agricultural features and positive effects of water features on turtles and frogs. Colonization probabilities ranged from 0.007 (95% CI = 0.006, 0.008) for spiny softshell turtle (Apalone spinifera) to 0.82 (95% CI = 0.62, 1.0) for western fox snake (Pantherophis ramspotti). Colonization probabilities for most species were best explained by effects of water and grassland landscape features. Predictive models had strong support (AUC > 0.70) for six out of 15 species (40%), including all three turtles studied. Our results provide estimates of occupancy and colonization probabilities and spatial predictions of occurrence for herptiles of greatest conservation need across the state of Iowa.

Range-Wide Phylogeography and Ecological Niche Modeling Provide Insights into the Evolutionary History of the Mongolian Racerunner (Eremias argus) in Northeast Asia

The Mongolian racerunner, Eremias argus, is a small lizard endemic to Northeast Asia that can serve as an excellent model for investigating how geography and past climate change have jointly influenced the evolution of biodiversity in this region. To elucidate the processes underlying its diversification and demography, we reconstructed the range-wide phylogeographic pattern and evolutionary trajectory, using phylogenetic, population genetic, landscape genetic, Bayesian phylogeographic reconstruction and ecological niche modeling approaches. Phylogenetic analyses of the mtDNA cyt b gene revealed eight lineages that were unbounded by geographic region. The genetic structure of E. argus was mainly determined by geographic distance. Divergence dating indicated that E. argus and E. brenchleyi diverged during the Mid-Pliocene Warm Period. E. argus was estimated to have coalesced at~0.4351 Ma (Marine Isotope Stage 19). Bayesian phylogeographic diffusion analysis revealed out-of-Inner Mongolia and rapid colonization events from the end of the Last Interglacial to the Last Glacial Maximum, which is consistent with the expanded suitable range of the Last Glacial Maximum. Pre-Last Glacial Maximum growth of population is presented for most lineages of E. argus. The Glacial Maximum contraction model and the previous multiple glacial refugia hypotheses are rejected. This may be due to an increase in the amount of climatically favorable habitats in Northeast Asia. Furthermore, E. argus barbouri most likely represents an invalid taxon. The present study is the first to report a range-wide phylogeography of reptiles over such a large region in Northeast Asia. Our results make a significant contribution towards understanding the biogeography of the entire Northeast Asia.

Landscape genetics reveal broad and fine-scale population structure due to landscape features and climate history in the northern leopard frog (Rana pipiens) in North Dakota

Prehistoric climate and landscape features play large roles structuring wildlife populations. The amphibians of the northern Great Plains of North America present an opportunity to investigate how these factors affect colonization, migration, and current population genetic structure. This study used 11 microsatellite loci to genotype 1,230 northern leopard frogs (Rana pipiens) from 41 wetlands (30 samples/wetland) across North Dakota. Genetic structure of the sampled frogs was evaluated using Bayesian and multivariate clustering methods. All analyses produced concordant results, identifying a major east-west split between two R. pipiens population clusters separated by the Missouri River. Substructuring within the two major identified population clusters was also found. Spatial principal component analysis (sPCA) and variance partitioning analysis identified distance, river basins, and the Missouri River as the most important landscape factors differentiating R. pipiens populations across the state. Bayesian reconstruction of coalescence times suggested the major east-west split occurred ~13-18 kya during a period of glacial retreat in the northern Great Plains and substructuring largely occurred ~5-11 kya during a period of extreme drought cycles. A range-wide species distribution model (SDM) for R. pipiens was developed and applied to prehistoric climate conditions during the Last Glacial Maximum (21 kya) and the mid-Holocene (6 kya) from the CCSM4 climate model to identify potential refugia. The SDM indicated potential refugia existed in South Dakota or further south in Nebraska. The ancestral populations of R. pipiens in North Dakota may have inhabited these refugia, but more sampling outside the state is needed to reconstruct the route of colonization. Using microsatellite genotype data, this study determined that colonization from glacial refugia, drought dynamics in the northern Great Plains, and major rivers acting as barriers to gene flow were the defining forces shaping the regional population structure of R. pipiens in North Dakota.

Evaluating the individuality of animal-habitat relationships

Examining the ways in which animals use habitat and select resources to satisfy their life history requirements has important implications for ecology, evolution, and conservation. The advent of radio-tracking in the mid-20th century greatly expanded the scope of animal-habitat modeling. Thereafter, it became common practice to aggregate telemetry data collected on a number of tagged individuals and fit one model describing resource selection at the population level. This convention, however, runs the risk of masking important individuality in the nature of associations between animals and their environment. Here, we investigated the importance of individual variation in animal-habitat relationships via the study of a highly gregarious species. We modeled elk (Cervus elaphus) location data, collected from Global Positioning System (GPS) collars, using Bayesian discrete choice resource selection function (RSF) models. Using a high-performance computing cluster, we batch-processed these models at the level of each individual elk (n = 88) and evaluated the output with respect to: (a) the composition of parameters in the most supported models, (b) the estimates of the parameters featured in the global models, and (c) spatial maps of the predicted relative probabilities of use. We detected considerable individual variation across all three metrics. For instance, the most supported models varied with respect to parameter composition with a range of seven to 17 and an average of 14.4 parameters per individual elk. The estimates of the parameters featured in the global models also varied greatly across individual elk with little conformity detected across age or sex classes. Finally, spatial mapping illustrated stark differences in the predicted relative probabilities of use across individual elk. Our analysis identifies that animal-habitat relationships, even among the most gregarious of species, can be highly variable. We discuss the implications of our results for ecology and present some guiding principles for the development of RSF models at the individual-animal level.

Exploring the amphibian exposome in an agricultural landscape using telemetry and passive sampling

This is the first field study of its kind to combine radio telemetry, passive samplers, and pesticide accumulation in tissues to characterize the amphibian exposome as it relates to pesticides. Understanding how habitat drives exposure in individuals (i.e., their exposome), and how that relates to individual health is critical to managing species in an agricultural landscape where pesticide exposure is likely. We followed 72 northern leopard frogs (Lithobates pipiens) in two agricultural wetlands for insight into where and when individuals are at high risk of pesticide exposure. Novel passive sampling devices (PSDs) were deployed at sites where telemetered frogs were located, then moved to subsequent locations as frogs were radio-tracked. Pesticide concentration in PSDs varied by habitat and was greatest in agricultural fields where frogs were rarely found. Pesticide concentrations in frogs were greatest in spring when frogs were occupying wetlands compared to late summer when frogs occupied terrestrial habitats. Our results indicate that habitat and time of year influence exposure and accumulation of pesticides in amphibians. Our study illustrates the feasibility of quantifying the amphibian exposome to interpret the role of habitat use in pesticide accumulation in frogs to better manage amphibians in agricultural landscapes.