Large-scale climate variation modifies the winter grouping behavior of endangered Indiana bats

Climate fluctuations influence variation in group size in a cooperative bird

Variation in group size is ubiquitous in social animals, but explaining the range of group sizes seen in nature remains challenging.^1-3 Group-living species occur most frequently in climatically unpredictable environments, such that the costs and benefits of sociality may change from year to year.^4-6 It is, therefore, possible that variation in climate may help to maintain a range of group sizes, but this hypothesis is rarely tested empirically.^7,8 Here, we examine selection on breeding group size in the greater ani (Crotophaga major), a tropical bird that nests in cooperative groups containing multiple co-breeders and non-breeding helpers.⁹ We found that larger groups experience lower nest predation (due to cooperative nest defense) but suffer higher nestling starvation (due to intra-clutch competition). Long-term data revealed that the relative magnitude of these costs and benefits depends on climate, with frequent changes across years in the strength and direction of selection on group size. In wet years, individual reproductive success was higher in large groups than in small groups, whereas the opposite was true in dry years. This was partly a consequence of competition among nestlings in large clutches, which suffered significantly higher mortality in dry years than in wet years. Averaged over the 13-year study period, annual reproductive success was approximately equal for females in small and large groups. These results suggest that temporal changes in the direction of selection may help explain the persistence of a range of group sizes and that a full understanding of the selective pressures shaping sociality requires long-term fitness data.

Long-term changes in bat activity in Quebec suggest climatic responses and summer niche partitioning associated with white-nose syndrome

In North America, the greatest and most sudden threat to hibernating bats is white-nose syndrome (WNS), which has caused massive declines in populations since 2006. Other determinants of bat dynamics, such as the climate, and the effect of reduction in the number of individuals sharing foraging space and summer roosting habitat may have an effect on population dynamics. We analyzed transect acoustic bat surveys conducted with ultrasonic detectors in 16 regions in Quebec, Canada, between 2000 and 2015. We used piecewise regression to describe changes in activity over time for each species and a meta-analytic approach to measure its association with the North Atlantic Oscillation (NAO). As expected, mouse-eared bat (Myotis spp.) activity sharply declined after the onset of WNS, down by 79% after 3 years. In contrast, big brown/silver-haired bat activity increased over the same period, possibly due to a release of competition. Hoary bats and red bats remained present, although their activity did not increase. Myotis activity was positively correlated with a one-year lag to the NAO index, associated with cold conditions in winter, but warm autumns. Big brown/silver-haired and hoary bats were also more active during NAO-positive years but without a lag. We conclude that combinations of threats may create rapid shifts in community compositions and that a more balanced research agenda that integrates a wider range of threats would help better understand and manage those changes.

Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat

Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat (Myotis sodalis), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans, disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity.

Evaluation of downscaled, gridded climate data for the conterminous United States

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates? (2) Are there significant regional differences in accuracy among data sets? (3) How accurate are their mean values compared with extremes? (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

A Bayesian approach for temporally scaling climate for modeling ecological systems

With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre‐1970] and contemporary [post‐2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet–dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

Fluctuating survival selection explains variation in avian group size

Most animal groups vary extensively in size. Because individuals in certain sizes of groups often have higher apparent fitness than those in other groups, why wide group size variation persists in most populations remains unexplained. We used a 30-y mark-recapture study of colonially breeding cliff swallows (Petrochelidon pyrrhonota) to show that the survival advantages of different colony sizes fluctuated among years. Colony size was under both stabilizing and directional selection in different years, and reversals in the sign of directional selection regularly occurred. Directional selection was predicted in part by drought conditions: birds in larger colonies tended to be favored in cooler and wetter years, and birds in smaller colonies in hotter and drier years. Oscillating selection on colony size likely reflected annual differences in food availability and the consequent importance of information transfer, and/or the level of ectoparasitism, with the net benefit of sociality varying under these different conditions. Averaged across years, there was no net directional change in selection on colony size. The wide range in cliff swallow group size is probably maintained by fluctuating survival selection and represents the first case, to our knowledge, in which fitness advantages of different group sizes regularly oscillate over time in a natural vertebrate population.

Estimating the spatial distribution of wintering little brown bat populations in the eastern United States

Depicting the spatial distribution of wildlife species is an important first step in developing management and conservation programs for particular species. Accurate representation of a species distribution is important for predicting the effects of climate change, land-use change, management activities, disease, and other landscape-level processes on wildlife populations. We developed models to estimate the spatial distribution of little brown bat (Myotis lucifugus) wintering populations in the United States east of the 100th meridian, based on known hibernacula locations. From this data, we developed several scenarios of wintering population counts per county that incorporated uncertainty in the spatial distribution of the hibernacula as well as uncertainty in the size of the current little brown bat population. We assessed the variability in our results resulting from effects of uncertainty. Despite considerable uncertainty in the known locations of overwintering little brown bats in the eastern United States, we believe that models accurately depicting the effects of the uncertainty are useful for making management decisions as these models are a coherent organization of the best available information.