In this study the authors thoroughly investigate state-dependent optimal decisions in high-latitude bat populations through a detailed model framework, and test the model application by comparing its predictions to data collected on northern bats.

Abstract

Strong seasonality at high latitudes represents a major challenge for many endotherms as they must balance survival and reproduction in an environment that varies widely in food availability and temperature. To avoid energetic mismatches caused by limited foraging time and stochastic weather conditions, bats employ the energy-saving state of torpor during summer to save accumulated energy reserves. However, at high-latitude small-bats-in-summer face a particular challenge: as nocturnal foragers, they rely on the darkness at night to avoid predators and/or interspecific competition, but live in an environment with short, light summer nights, and even a lack of true night at the northernmost distributions of some bat species. To predict optimal behaviour in relation to latitudinal variation in diurnal cycles, we constructed a stochastic dynamic programming model of bats living at high latitudes. Using a stochastic dynamic programming framework with values that are representative for our study system, we show that individual energetic reserves are a strong driver of daytime use of torpor and night-time foraging behaviour alike, with these linked effects being both temperature- and photoperiod-dependent. We further used the model to predict survival probabilities at five locations across a latitudinal gradient (60.1° N to 70.9° N), finding that combinations of photoperiod and temperature conditions limited population distributions in the model. To verify our model results, we compared predictions for optimal decisions with our own empirical data collected on northern bats (Eptesicus nilssonii) from two latitudes in Norway. The similarities between our predictions and observations provide strong evidence that this model framework incorporates the most important drivers of diurnal decision-making in bat physiology and behaviour. Comparing empirical data and model predictions also revealed that bats facing lighter night conditions further north restrict their mass gain, which strengthens the hypothesis that predation threat is a main driver of bat nocturnality. Our model findings regarding state-dependent decisions in bats should contribute to the understanding of how bats cope with the summer challenges at high latitudes.

The increasing availability of fine-scale animal movement data facilitates various options to investigate behaviour-specific habitat selection. Using hidden Markov models and step-selection functions on muskox GPS-tracking data, this study compares different approaches to account for behaviour, highlights methodological intricacies and demonstrates that especially the definition of the availability domain impacts inference. © Lars Holst Hansen.

Abstract

Animal habitat selection—central in both theoretical and applied ecology—may depend on behavioural motivations such as foraging, predator avoidance, and thermoregulation. Step-selection functions (SSFs) enable assessment of fine-scale habitat selection as a function of an animal's movement capacities and spatiotemporal variation in extrinsic conditions. If animal location data can be associated with behaviour, SSFs are an intuitive approach to quantify behaviour-specific habitat selection. Fitting SSFs separately for distinct behavioural states helped to uncover state-specific selection patterns. However, while the definition of the availability domain has been highlighted as the most critical aspect of SSFs, the influence of accounting for behaviour in the use-availability design has not been quantified yet. Using a predator-free population of high-arctic muskoxen Ovibos moschatus as a case study, we aimed to evaluate how (1) defining behaviour-specific availability domains, and/or (2) fitting separate behaviour-specific models impacts (a) model structure, (b) estimated selection coefficients and (c) model predictive performance as opposed to behaviour-unspecific approaches. To do so, we first applied hidden Markov models to infer different behavioural modes (resting, foraging, relocating) from hourly GPS positions (19 individuals, 153–1062 observation days/animal). Using SSFs, we then compared behaviour-specific versus behaviour-unspecific habitat selection in relation to terrain features, vegetation and snow conditions. Our results show that incorporating behaviour into the definition of the availability domain primarily impacts model structure (i.e. variable selection), whereas fitting separate behaviour-specific models mainly influences selection strength. Behaviour-specific availability domains improved predictive performance for foraging and relocating models (i.e. behaviours with medium to large spatial displacement), but decreased performance for resting models. Thus, even for a predator-free population subject to only negligible interspecific competition and human disturbance we found that accounting for behaviour in SSFs impacted model structure, selection coefficients and predictive performance. Our results indicate that for robust inference, both a behaviour-specific availability domain and behaviour-specific model fitting should be explored, especially for populations where strong spatiotemporal selection trade-offs are expected. This is particularly critical if wildlife habitat preferences are estimated to inform management and conservation initiatives.

The study examined the relationship between climate, physiology and distribution of Lampropholis skinks in eastern Australia. Widespread species showed broader physiological tolerance than range-restricted species, and incorporating physiological and behavioural data improved species distribution models, particularly for range-restricted species.

Abstract

Climate has a key impact on animal physiology, which in turn can have a profound influence on geographic distributions. Yet, the mechanisms linking climate, physiology and distribution are not fully resolved. Using an integrative framework, we tested the predictions of the climatic variability hypothesis (CVH), which states that species with broader distributions have broader physiological tolerance than range-restricted species, in a group of Lampropholis skinks (8 species, 196 individuals) along a latitudinal gradient in eastern Australia. We investigated several physiological aspects including metabolism, water balance, thermal physiology, thermoregulatory behaviour and ecological performance. Additionally, to test whether organismal information (e.g. behaviour and physiology) can enhance distribution models, hence providing evidence that physiology and climate interact to shape range sizes, we tested whether species distribution models incorporating physiology better predict the range sizes than models using solely climatic layers. In agreement with the CVH, our results confirm that widespread species can tolerate and perform better at broader temperature ranges than range-restricted species. We also found differences in field body temperatures, but not thermal preference, between widespread and range-restricted species. However, metabolism and water balance did not correlate with range size. Biophysical modelling revealed that the incorporation of physiological and behavioural data improves predictions of Lampropholis distributions compared with models based solely on macroclimatic inputs, but mainly for range-restricted species. By integrating several aspects of the physiology and niche modelling of a group of ectothermic animals, our study provides evidence that physiology correlates with species distributions. Physiological responses to climate are central in establishing geographic ranges of skinks, and the incorporation of processes occurring at local scales (e.g. behaviour) can improve species distribution models.

The authors use a long-term experiment spanning more than two decades to show that a large herbivore (moose) has significant impacts on boreal plant communities but little effect on boreal soils. The data show that soils may be resilient to above-ground impacts in unproductive ecosystems such as the boreal forest.

Abstract

1.

Experimental studies across biomes demonstrate that herbivores can have significant effects on ecosystem functioning. Herbivore effects, however, can be highly variable with studies demonstrating positive, neutral or negative relationships between herbivore presence and different components of ecosystems. Mixed effects are especially likely in the soil, where herbivore effects are largely indirect mediated through effects on plants.

We conducted a long-term experiment to disentangle the effects of non-native moose in boreal forests on plant communities, nutrient cycling, soil composition and soil organism communities.

To explore the effect of moose on soils, we conduct separate analyses on the soil organic and mineral horizons. Our data come from 11 paired exclosure-control plots in eastern and central Newfoundland, Canada that provide insight into 22–25 years of moose herbivory. We fit piecewise structural equations models (SEM) to data for the organic and mineral soil horizons to test different pathways linking moose to above-ground and below-ground functioning.

The SEMs revealed that moose exclusion had direct positive impacts on adult tree count and an indirect negative impact on shrub percent cover mediated by adult tree count. We detected no significant impact of moose on soil microbial C:N ratio or net nitrogen mineralization in the organic or mineral soil horizon. Soil temperature and moisture, however, was more than twice as variable in the presence (i.e. control) than absence (i.e. exclosure) of moose. Overall, we observed clear impacts of moose on above-ground forest components with limited indirect effects below-ground. Even after 22–25 years of exclusion, we did not find any evidence of moose impacts on soil microbial C:N ratio and net nitrogen mineralization.

Our long-term study and mechanistic path analysis demonstrates that soils can be resilient to ungulate herbivore effects despite evidence of strong effects above-ground. Long-term studies and analyses such as this one are relatively rare yet critical for reconciling some of the context-dependency observed across studies of ungulates effects on ecosystem functions. Such studies may be particularly valuable in ecosystems with short growing seasons such as the boreal forest.