Species with narrow environmental preferences are often distributed across fragmented patches of suitable habitat, and dispersal among subpopulations can be difficult to directly observe. Genetic data collected at population centers can help quantify gene flow, which is especially important for vulnerable species with a disjunct range. Plethodon shenandoah is a Federally Endangered salamander known only from three mountaintops in Virginia, USA. To reconstruct the evolutionary history and population connectivity of this species, we generated both mitochondrial and nuclear data using sequence capture for all three populations and found strong population structure that was independent of geographic distance. Both the nuclear markers and mitochondrial genome indicated a deep split between the most southern population and the combined central and northern population. Although there was some mitochondrial haplotype-splitting between the central and northern populations, there was complete admixture in nuclear markers. This is indicative of either a recent split or current male-biased dispersal among mountain isolates. Models of landscape resistance found that dispersal across north-facing slopes at mid-elevation levels best explain the observed genetic structure among populations. These unexpected results highlight the importance of landscape features in understanding and predicting movement and fragmentation of salamanders across space.

To better understand relations of annual calling phenophases for Pseudacris crucifer, and of the first calls of the season for Hyla chrysoscelis/versicolor, to the timing of the start of the calling season, we compared these dynamics for six wetlands in the St. Croix National Scenic Riverway from 2008 to 2012. We installed an acoustic recorder at each site prior to the start of each calling season and programmed it to record for five minutes at the top of every hour until late summer. We then used the Songscape option in Songscope software to generate annual summaries of all acoustic files recorded at each site. We created contour plots of the summarized median dB values across bandwidths in each recording and then assessed individual calls and calling peaks by visually examining these plots to identify first (and last) calls via the unique call signatures for these two species. We examined individual five-minute recordings aurally and visually as necessary when sound images represented on the contour plots were confounded and to ensure that the calling peaks described below were dates when calling activity was relatively intense. We also determined the daily median dB levels for frequencies across 2900 to 3200 Hz during 2100 to 2300 h, the bandwidth that typically encompassed the primary energy peak in P. crucifer calls and a time period during which P. crucifer typically called most consistently throughout their calling season. We did this for each day from the date when P. crucifer first called during each year to the date when they last called during each year. Because calling activity could vary from one hour to the next, we integrated the area under the curve for the daily median dB levels from 2900 to 3200 Hz during 2100 to 2300 h. We removed dates when overlapping sounds from storms or other sources rendered comparisons to calls of P. crucifer inaccurate. We used the resultant set of integrands to represent the relative sound intensity (as an indicator of calling activity) for P. crucifer across those hours for each date. We then used these integrands to determine the three highest peak calling dates for this species and used the median of those three dates as the overall median peak date for each site in each year.

To help determine when winter conditions were changing to spring conditions annually in our four study areas, we determined the first eight-day interval (in accordance with the scale limitations of satellite data we used to assess the presence of snow) during which the first amphibian of the season called at each of our study wetlands in those areas. To do this, we examined contour plots of summaries of all the acoustic data we collected at that site in a given year to identify the unique call signatures of individual amphibian species by date and time. When necessary due to potential confounding on a contour plot, we also examined relevant individual five-minute recordings aurally and visually to confirm whether a call occurred. When we confirmed the date of the first call we recorded in a given season, we identified the eight-day interval in which that date fell, with the first such interval beginning on January 1 of each year.

To relate water levels in our study wetlands to temperature, precipitation, wetland water depth, and amphibian calling activity, we installed one pressure logger in the deepest spot we could find in each wetland. Soon after thawing conditions allowed, we drove a plastic pipe (anchor pipe) into the sediments at the deepest location and secured another pipe to it that contained one pressure logger (Global Water Model 14 and 15 [College Station, TX, USA] or Onset Computer Corporation Model U20-001-04 [Bourne, MA, USA]) suspended approximately 2.5 cm above the sediments. We installed additional individual pressure loggers in the upper part of the logger pipes (in air) at select locations to measure barometric pressure for calibrating the submerged loggers’ readings. We measured pressure once per hour and used software supplied by the logger manufacturers to upload and convert data to depth at the end of each season.

To describe calling activity of Pseudacris crucifer in relation to temperature, precipitation, and wetland water levels, we programmed an acoustic recorder (Wildlife Acoustics) to sample seasonal amphibian calls remotely at study site SC4DAI2 in the St. Croix National Scenic Riverway from 2008 to 2012. We programmed the recorder to sample for five minutes at the top of every hour of every day from late winter/early spring through late summer. We used the Songscape option in Songscope software to generate annual summaries of all of our acoustic samples from SC4DAI2. These summaries included a median dB level for each prescribed frequency within each recording. Pseudacris crucifer, the spring peeper, inhabited SC4DAI2 and typically called over several weeks each year, depending upon weather conditions and surface-water availability. Most of the energy in their individual calls occurred between 2900 and 3200 Hz, which provided a unique acoustic signature compared with the other anurans that called from the site. We used this information as part of a case study to better understand how the daily calling activity of P. crucifer varied relative to air temperature, precipitation, and water depth at SC4DAI2 across years. We first determined the daily median dB levels for frequencies across 2900 to 3200 Hz during 2100 to 2300 h, a time period during which P. crucifer typically called throughout their calling season. We did this for each day from the date when P. crucifer first called each year to the date when they last called each year and considered any day in this range as one during which they potentially could call. Because calling activity could vary from one hour to the next, we integrated the area under the curve for the daily median dB levels from 2900 to 3200 Hz during 2100 to 2300 h. We removed dates when overlapping sounds from storms or other sources rendered comparisons to calls of P. crucifer inaccurate. We used the resultant set of integrands to represent the relative sound intensity (as an indicator of calling activity) for P. crucifer across those hours for each date. Those integrands are contained in this data set. These data enabled us to then compare daily integrand values with daily measurements of air temperature, precipitation totals, and water depth.

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

Long-term, interdisciplinary studies of relations between climate and ecological conditions on wetland-upland landscapes have been lacking, especially studies integrated across scales meaningful for adaptive resource management. We collected data in situ at individual wetlands, and via satellite for surrounding 4-km2 landscape blocks, to assess relations between annual weather dynamics, snow duration, phenology, wetland surface-water availability, amphibian presence and calling activity, greenness, and evapotranspiration in four U.S. conservation areas from 2008 to 2012. Amid recent decades of relatively warm growing seasons, 2012 and 2010 were the first and second warmest seasons, respectively, dating back to 1895. Accordingly, we observed the earliest starts of springtime biological activity during those two years. In all years, early-season amphibians first called soon after daily mean air temperatures were ? 0°C and snow had mostly melted. Similarly, satellite-based indicators suggested seasonal leaf-out happened soon after snowmelt and temperature thresholds for plant growth had occurred. Daily fluctuations in weather and water levels were related to amphibian calling activity, including decoupling the timing of the onset of calling at the start of season from the onset of calling events later in the season. Within-season variation in temperature and precipitation also was related to vegetation greenness and evapotranspiration, but more at monthly and seasonal scales. Wetland water levels were moderately to strongly associated with precipitation and early or intermittent wetland drying likely reduced amphibian reproduction success in some years, even though Pseudacris crucifer occupied sites at consistently high levels. Notably, satellite-based indicators of landscape water availability did not suggest such consequential, intra-seasonal variability in wetland surface-water availability. Our cross-disciplinary data show how temperature and precipitation interacted to affect key ecological relations and outcomes on our study landscapes. These results demonstrate the value of multi-year studies and the importance of scale for understanding actual climate-related effects in these areas.

Occupancy models provide a reliable measure of species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that occupancy surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of estimating detection probabilities would allow more sites to be surveyed for the same effort, resulting in more information about the ecological processes leading to occupancy. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough and occupancy high enough to reliably estimate the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, relative abundance was negatively related to the time to initial detection of all species, and pond area was positively related to time to initial detection for Sierran Treefrogs (Hyliola sierra) and Rough-skinned Newts (Taricha granulosa). Rough-skinned newt time to initial detection also was affected by date, with lowest initial detection time in early summer. California Red-legged Frog (Rana draytonii) time to detection was lowest in ponds with a mean depth of 0.6 m, and higher in shallower and deeper ponds. Probability of occurrence of Sierran Treefrogs and Rough-skinned Newts was negatively related to the presence of fish and pond area. Rarely detected species required constraints on priors to fit time-to-detection models. Time-to-detection surveys can provide an efficient method of estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.

The introductions of non-native predators often reduce biodiversity and affect natural predator-prey relationships. However, non-native predators may increase the abundance of potential disease vectors (e.g. mosquitoes) indirectly through competition or predation cascades. The Santa Monica
Mountains, situated in a global biodiversity hotspot, is an area of conservation concern due to climate change, urbanization, and the introduction of non-native species. We examined the effect that non-native crayfish (Procambarus clarkii) have on an existing native predator, dragonfly nymphs (Aeshna sp.) and their mosquito larvae (Anopheles sp.) prey. We used laboratory experiments to compare the predation efficiency of both predators, separately and together, and field data on counts of dragonfly nymphs and mosquito larvae sampled from 13 local streams. We predicted a lower predation efficiency of crayfish compared to native dragonfly nymphs as well as a reduced efficiency of dragonfly nymphs in the presence of crayfish. Dragonfly nymphs were an order of magnitude more efficient mosquito predators compared to crayfish and dragonfly
nymphs suffered reduced efficiency in the presence of crayfish. Analyses of field count data showed that populations of dragonfly nymphs and mosquito larvae were strongly correlated with crayfish presence in streams, such that sites with crayfish tended to have fewer dragonfly
nymphs and more mosquito larvae. Under natural conditions, it is likely that crayfish reduce the abundance of dragonfly nymphs and their predation efficiency, and thereby, directly and indirectly, lead to higher mosquito populations and a loss of ecosystem services related to disease vector control.

Comparative landscape genetics has uncovered high levels of variability in which landscape factors affect connectivity among species and regions. However, the relative importance of species traits vs. environmental variation for predicting landscape patterns of connectivity is unresolved. We provide a test with a landscape genetics study of two sister taxa of frogs, the Oregon spotted frog (Rana pretiosa) and the Columbia spotted frog (R. luteiventris) in Oregon and Idaho, USA. Rana pretiosa is relatively more dependent on moisture for dispersal than R. luteiventris, so if species traits influence connectivity, we predicted that connectivity among R. pretiosa populations would be more positively associated with moisture than R. luteiventris. However, if environmental differences are important drivers of gene flow, we predicted that connectivity would be more positively related to moisture in arid regions. We tested these predictions using eight microsatellite loci and gravity models in two R. pretiosa regions and four R. luteiventris regions (n = 1,168 frogs). In R. pretiosa, but not R. luteiventris, connectivity was positively related to mean annual precipitation, supporting our first prediction. In contrast, connectivity was not more positively related to moisture in more arid regions. Various temperature metrics were important predictors for both species and in all regions, but the directionality of their effects varied. Therefore, the pattern of variation in drivers of connectivity was consistent with predictions based on species traits rather than on environmental variation.