Genetic diversity in a long-lived mammal is explained by the past's demographic shadow and current connectivity.

Within-species genetic diversity is crucial for the persistence and integrity of populations and ecosystems. Conservation actions require an understanding of factors influencing genetic diversity, especially in the context of global change. Both population size and connectivity are factors greatly influencing genetic diversity; the relative importance of these factors can, however, change through time. Hence, quantifying the degree to which population size or genetic connectivity are shaping genetic diversity, and at which ecological time scale (past or present), is challenging, yet essential for the development of efficient conservation strategies. In this study, we estimated the genetic diversity of 42 colonies of Rhinolophus hipposideros, a long-lived mammal vulnerable to global change, sampling locations spanning its continental northern range. Here, we present an integrative approach that disentangles and quantifies the contribution of different connectivity measures in addition to contemporary colony size and historic bottlenecks in shaping genetic diversity. In our study, the best model explained 64% of the variation in genetic diversity. It included historic bottlenecks, contemporary colony size, connectivity and a negative interaction between the latter two. Contemporary connectivity explained most genetic diversity when considering a 65 km radius around the focal colonies, emphasizing the large geographic scale at which the positive impact of connectivity on genetic diversity is most profound and hence, the minimum scale at which conservation should be planned. Our results highlight that the relative importance of the two main factors shaping genetic diversity varies through time, emphasizing the relevance of disentangling them to ensure appropriate conservation strategies.

Using Approximate Bayesian Computation to infer sex ratios from acoustic data.

Population sex ratios are of high ecological relevance, but are challenging to determine in species lacking conspicuous external cues indicating their sex. Acoustic sexing is an option if vocalizations differ between sexes, but is precluded by overlapping distributions of the values of male and female vocalizations in many species. A method allowing the inference of sex ratios despite such an overlap will therefore greatly increase the information extractable from acoustic data. To meet this demand, we developed a novel approach using Approximate Bayesian Computation (ABC) to infer the sex ratio of populations from acoustic data. Additionally, parameters characterizing the male and female distribution of acoustic values (mean and standard deviation) are inferred. This information is then used to probabilistically assign a sex to a single acoustic signal. We furthermore develop a simpler means of sex ratio estimation based on the exclusion of calls from the overlap zone. Applying our methods to simulated data demonstrates that sex ratio and acoustic parameter characteristics of males and females are reliably inferred by the ABC approach. Applying both the ABC and the exclusion method to empirical datasets (echolocation calls recorded in colonies of lesser horseshoe bats, Rhinolophus hipposideros) provides similar sex ratios as molecular sexing. Our methods aim to facilitate evidence-based conservation, and to benefit scientists investigating ecological or conservation questions related to sex- or group specific behaviour across a wide range of organisms emitting acoustic signals. The developed methodology is non-invasive, low-cost and time-efficient, thus allowing the study of many sites and individuals. We provide an R-script for the easy application of the method and discuss potential future extensions and fields of applications. The script can be easily adapted to account for numerous biological systems by adjusting the type and number of groups to be distinguished (e.g. age, social rank, cryptic species) and the acoustic parameters investigated.

Variation of adult survival drives population dynamics in a migrating forest bat.

1. Variation of survival across time, between sex and ages strongly affect the population dynamics of long-lived species. Bats are extremely long-lived, but the variation of their survival probabilities is poorly studied with reliable methods. 2. We studied annual local survival probabilities of the migratory Leisler's bats Nyctalus leisleri based on capture-recapture data from 1119 individuals sampled in bat boxes over 20 years in eastern Germany. We assessed variation in survival between sex and age classes, estimated the temporal variance of survival and tested whether survival was affected by weather during hibernation or pregnancy. 3. Among females, our analyses revealed two groups of individuals present with different roosting occupancy, survival and/or dispersal. Local survival of locally born females increased with age [first year: 0.45 +/- 0.04 (SE); later: 0.76 +/- 0.04] and the high recapture probabilities indicate regular presence in the roosts. Recapture probabilities and local survival of foreign adult females were significantly lower, indicating less frequent presence in the roosts and stronger dispersal from the study area. 4. In adult males, locally born and foreign individuals were nearly identical regarding survival and recapture, indicating a more homogenous group. Local survival was very low in the first year (0.04 +/- 0.08), most likely caused by strong natal dispersal. It further increased with age (second year: 0.55 +/- 0.20, later: 0.69 +/- 0.07). 5. Survival probabilities of all females varied significantly and in parallel across time, suggesting that a common environmental factor was operating which affected all individuals similarly. Spring temperature and winter North Atlantic Oscillation explained maximally 9% each of the variation in first year and adult female survival. In contrast to our expectations, the temporal variance of first-year survival was lower than that of adult survival. 6. We found evidence of a complicated social population structure of female Leisler's bats. Our analyses suggest that their population dynamics are driven to a large amount by variation of survival, in particular by adult survival. The reason for the major temporal variations remains to be identified.