Resource fluctuation is a major driver of animal movement, influencing strategic choices such as residency vs nomadism, or social dynamics. The Arctic tundra is characterized by strong seasonality: resources are abundant during the short summers but scarce in winters. Therefore, expansion of boreal-forest species onto the tundra raises questions on how they cope with winter-resource scarcity. We examined a recent incursion by red foxes (Vulpes vulpes) onto the coastal tundra of western Hudson Bay, an area historically occupied by Arctic foxes (Vulpes lagopus) that lacks access to anthropogenic foods, and compared seasonal shifts in space use of the two species. We used 4 years of telemetry data following 8 red foxes and 11 Arctic foxes to test the hypothesis that the movement strategies of both species are primarily driven by temporal variability of resources. We also predicted that the harsh tundra conditions in winter affect red foxes more than Arctic foxes, which are adapted to this environment. Dispersal was the most frequent winter movement strategy in both fox species, despite its association with high mortality (winter mortality was 9.4 times higher in dispersers than residents). Red foxes consistently dispersed towards the boreal forest, whereas Arctic foxes primarily used sea ice to disperse. Home range size of red and Arctic foxes did not differ in summer, but resident red foxes substantially increased their home range size in winter, whereas home range size of resident Arctic foxes did not change seasonally. As climate changes, abiotic constraints on some species may relax, but associated declines in prey communities may lead to local extirpation of many predators, notably by favoring dispersal during resource scarcity.
Aim: Species’ environmental requirements and large-scale spatial and evolutionary processes are known to determine the structure and composition of local communities. However, ecological interactions and historical processes also have major effects on community assembly at landscape and local scales. In this work we evaluate whether two xerophytic shrub communities follow fixed ecological assembly dynamics throughout large geographical extents, or their composition is rather driven by species individualistic responses to environmental and macroecological constraints. Location: SW Iberian Peninsula (Portugal and Spain) Taxa: Stauracanthus genistoides agg. and Ulex australis agg (Fabaceae). Methods:Inland dune xerophytic shrub communities were sampled in 95 plots distributed within their potential area of occurrence. Then, we described the main gradients of vegetation composition and assess the relevance of biotic interactions. We also characterized the habitat suitability of the dominant species, S. genistoides and U. australis, to map the potential distribution of the xerophytic shrub communities. Finally, to identify the relative importance of each factor driving changes in community composition, we examined the relationships between the vegetation gradients and a broad set of explanatory variables. Results: Our results show that xerophytic shrubs follow uniform successional patterns throughout the whole geographical area, but also that these communities respond differently to the main environmental gradients in each region. Soil organic matter is the main determinant of community variations in the northern regions, Setúbal Peninsula and Comporta, while in the South/South-Western region most of the variation between both types of communities is explained by temperature seasonality. Main conclusions: The relative importance of the main factors causing community-level responses varies according to regional processes and the suitability of the environmental conditions for the dominant species in these communities. These responses are also determined by intrinsic community mechanisms that result in a high degree of similarity in the gradient-driven community stages in different regions.
Whole-genome sequencing for generating SNP data is increasingly used in population genetic studies. However, obtaining genomes for massive numbers of samples is still not within the budgets of many researchers. It is thus imperative to select an appropriate reference genome and sequencing coverage to ensure the accuracy of the results for a specific research question, while balancing cost and feasibility. To evaluate the effect of the choice of the reference genome and sequencing coverage on downstream analyses, we used five confamilial reference genomes of variable relatedness and three levels of sequencing coverage (3.5x, 7.5x and 12x) in a population genomic study on two caddisfly species: Himalopsyche digitata and H. tibetana. Using these 30 datasets (five reference genomes × three coverages × two target species), we estimated population genetic indices (inbreeding coefficient, nucleotide diversity, pairwise and genome-wide FST) based on variants and population structure (PCA and admixture) based on genotype likelihood estimates. The results showed that both distantly related reference genomes and lower sequencing coverage lead to degradation of resolution. In addition, choosing a more closely related reference genome may significantly remedy the defects caused by low coverage. Therefore, we conclude that population genetic studies would benefit from closely related reference genomes, especially as the costs of obtaining a high-quality reference genome continue to decrease. However, to determine a cost-efficient strategy for a specific population genomic study, a trade-off between reference genome relatedness and sequencing depth can be considered.
Species distribution patterns are essential for the conservation of biodiversity. The aim of this study was to evaluate the influence of multiple ecological hypotheses on the spatial patterns of rodent species richness in China. First, we divided the geographic region of China into 80 × 80 km2 grid cells and mapped the distribution ranges of the 237 rodent species. Rodent taxa were separated into three response variables based on their distribution: (a) all species, (b) non-endemic species, and (c) endemic species. The predictors were divided into four factor sets: (a) energy-water, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human factors, which were used to represent four different ecological hypotheses. We then performed multiple regression analysis (OLS), spatial autoregressive models (SAR), and variation partitioning analyses to determine the effects of predictors on the spatial patterns of rodent species. The Hengduan Mountains and surrounding mountains in southwest China showed the highest species richness and endemism. Habitat heterogeneity is the most important factor explaining the species richness distribution patterns across all species and non-endemic species. Endemic species richness patterns are most susceptible to seasonal changes in climate and least affected by human factors. The effects of energy and water on the three response variables showed consistent levels of importance.
The eastern tree hyrax is thought to be a solitarily living arboreal species of the forests of East Africa. However, in the coast of Kenya, indigenous forests have been almost entirely cleared, and some of the last tree hyrax populations live in limestone rocky formations and caves. Interestingly, they seem to be living in social groups. Here, we describe and document photographically these unique tree hyrax populations. We also describe their acoustical communication and their calling activity in three different habitats. Based on these animals' physical appearance and acoustic analyses of their calls, they represent the species eastern tree hyrax, Dendrohyrax validus. Due to immence pressure from humans, the future of these small and isolated, cave-living tree hyrax populations does not seem bright.
1. Our understanding of how bees (Apoidea) use temperate forests is largely limited to sampling the understory and forest floor. Studies over the last decade have demonstrated that bee communities are vertically stratified within forests, yet the ecology of bee assemblages immediately above the canopy, the canopy-aerosphere interface, remains unexplored. 2. We sampled and compared bee communities above the canopy of a temperate forest to the understory (1 m), midstory (10 m), and canopy (20 m) on the campus of the University of Massachusetts, in Amherst, Massachusetts, USA from April – August, 2021. 3. Overall, we found that assemblages above the canopy had more bees than in the understory, were distinct in composition from all other strata, and included the greatest proportion of unique species. Bee abundance and species richness were highest in the understory throughout the spring (April and May) and decreased as the season progressed, while bee abundance and species richness at higher strata increased into the summer months. We also found that bees with preferences to nest in moist and rotting wood were largely restricted to canopy and midstory strata. 4. We conclude that bee assemblages occupying the space above the forest canopy are abundant and diverse, and their unique composition suggests that this canopy-aerosphere interface plays an additional role in the bee community of temperate forests. Alternatively, our findings question how forest bee communities should be defined while highlighting the need for research on fundamental processes governing species stratification in and above the canopy.
Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well-performing models has never been implemented. We integrated input data manipulation and model tuning for four commonly-used SDMs; generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model-specific parameters considering two background selection methods; random and background weighting schemes. The performance of the fine-tuned models was assessed based on a recently identified localities of the species. The results indicated that although the fine-tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out-of-bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over-predict non-sampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced-biased data in species distribution modeling approaches.
1. Animal abundance estimation is increasingly based on drone or aerial survey photography. Manual post-processing has been used extensively, however volumes of such data are increasing, necessitating some level of automation, either for complete counting, or as a labour-saving tool. Any automated processing can be challenging when using the tools on species that nest in close formation such as Pygoscelid penguins. 2. We present here an adaptation of state-of-the-art crowd-counting methodologies for counting of penguins from aerial photography. 3. The crowd-counting model performed significantly better in terms of model performance and computational efficiency than standard Faster RCNN deep-learning approaches and gave an error rate of only 0.8 percent. 4. Crowd-counting techniques as demonstrated here have the ability to vastly improve our ability to count animals in tight aggregations, which will demonstrably improve monitoring efforts from aerial imagery.
Understanding the drivers of morphological convergence requires investigation into its relationship with behavior and niche-space, and such investigations in turn provide insights into evolutionary dynamics, functional morphology, and life history. Mygalomorph spiders (trapdoor spiders and their kin) have long been associated with high levels of homoplasy, and many convergent features can be intuitively associated with different behavioral niches. Using genus-level phylogenies based on recent genomic studies and a newly assembled matrix of discrete behavioral and somatic morphological characters, we reconstruct the evolution of burrowing behavior in the Mygalomorphae, compare the influence of behavior and evolutionary history on somatic morphology, and test hypotheses of correlated evolution between specific morphological features and behavior. Our results reveal the simplicity of the mygalomorph adaptive landscape, with opportunistic, web-building taxa at one end, and burrowing/nesting taxa with structurally-modified burrow entrances (e.g., a trapdoor) at the other. Shifts in behavioral niche, in both directions, are common across the evolutionary history of the Mygalomorphae, and several major clades include taxa inhabiting both behavioral extremes. Somatic morphology is heavily influenced by behavior, with taxa inhabiting the same behavioral niche often more similar morphologically than more closely-related but behaviorally-divergent taxa, and we were able to identify a suite of 11 somatic features that show significant correlation with particular behaviors. We discuss these findings in light of the function of particular morphological features, niche dynamics within the Mygalomorphae, and constraints on the mygalomorph adaptive landscape relative to other spiders.
Saltwater- and freshwater environments have opposing physiological challenges, yet, there are fish species that are able to enter both habitats during short time-spans, and as individuals they must therefore adjust quickly to osmoregulatory contrasts. In this study, we conducted an experiment to test for plastic responses to abrupt sainity changes in two poplulations of threespine stickleback, Gasterosteus aculeatus, representing two ecotypes (freshwater and ancestral saltwater). We exposed both ecotypes to abrupt native (control treatment) and non-native salinities (0 and 30‰) and sampled gill-tissue for transcriptomic analyses after six hours exposure. To investigate genomic responses to salinity, we analysed four different comparisons; one for each ecotype (in their control and exposure salinity; 1 and 2), one between ecotypes in their control salinity (3), and the fourth comparison included all transcripts identified in (3) that did not show any expressional changes within ecotype in either the control or the exposed salinity (4). Abrupt salinity transfer affected the expression of 10 and 1530 transcripts for the saltwater and freshwater ecotype, respectively, and 1314 were differentially expressed between the controls, including 502 that were not affected by salinity within ecotype (fixed expression). In total, these results indicate that factors other than genomic expressional plasticity are important for osmoregulation in stickleback, due to the need for opposite physiological pathways to survive the abrupt change in salinity.
DNA barcoding has been used worldwide to identify biological specimens and to delimit species. It represents a cost-effective, fast and efficient way to assess biodiversity with help of the public Barcode of Life Database (BOLD) accounting for more than 236,000 animal species and more than ten million barcode sequences. Here, we performed a meta-analysis of available barcode data of central European Coleoptera to detect intraspecific genetic patterns among ecological groups in relation to geographic distance with the aim to investigate a possible link between infraspecific variation and species ecology. We collected information regarding feeding style, body size as well as habitat and biotope preferences. Mantel tests and two variants of Procrustes analysis, both involving the Principal Coordinates Neighborhood Matrices (PCNM) approach, were applied on genetic and geographic distance matrices. However, significance levels were too low to further use the outcome for further trait investigation: these were in mean for all ecological guilds only 7.5, 9.4, or 15.6 % for PCNM+PCA, NMDS+PCA, and Mantel test, respectively, or at best 28% for a single guild. Our study confirmed that certain ecological traits were associated with higher species diversity and foster stronger genetic differentiation. Results suggest that increased numbers of species, sampling localities, and specimens for a chosen area of interest may give new insights to explore barcode data and species ecology for the scope of conservation on a larger scale.
Sexual imprinting is widespread in birds and other species but its existence requires explanation. Here we show that sexual imprinting leads to speciation in locally-adapted populations if a neutral mating cue – e.g., novel plumage coloration – arises through mutation. Local adaptations occur when evolution results in stable genetic polymorphisms with one allele predominating in some areas while others predominate elsewhere. Here we use a deterministic two-niche population genetic model to map the set of migration and selection rates for which polymorphic evolutionary outcomes, i.e., local adaptations, can occur. Equations for the boundaries of the set of polymorphic evolutionary outcomes were derived by (Bulmer, 1972), but our results, obtained by deterministic simulation of the evolutionary process, show that one of Bulmer’s equations is inaccurate except when the level of dominance is 0.5, and fails if one of the alleles is dominant. Having an accurate map of the set of migration and selection rates for which polymorphic evolutionary outcomes can occur, we then show using the model of (Sibly et al., 2019) that local adaptation in all cases leads to speciation if a new neutral mating cue arises by mutation. We finish by considering how genome sequencing makes possible testing of our results.
Many populations of long-distance migrant shorebirds are declining rapidly. Since the 1970s, the Lesser Yellowlegs (Tringa flavipes) has experienced a pronounced reduction in abundance of ~63%. The potential causes of the species’ decline are complex and interrelated yet understanding the timing of migration and seasonal routes used by this species will aid in directing conservation planning to address potential threats. During 2018–2021, we tracked 118 adult Lesser Yellowlegs using GPS satellite tags deployed on birds from five breeding and two migratory stopover locations spanning the boreal forest of North America from Alaska to eastern Canada. Our objectives were to quantify migratory connectivity and identify key stopover and non-breeding locations. Individuals tagged in Alaska and central Canada followed similar southbound migratory routes through the Prairie Pothole Region of North America, whereas birds tagged in eastern Canada completed multi-day transoceanic flights covering distances of >4,000 km across the Atlantic between North and South America. Upon reaching their non-breeding locations, Lesser Yellowlegs populations overlapped, resulting in weak migratory connectivity. Lastly, freshwater and agricultural habitats of the Prairie Pothole region supported the highest proportion of Lesser Yellowlegs during southbound migration. Our findings suggest that while Lesser Yellowlegs travel long distances and traverse numerous political boundaries each year, the breeding population from which an individual originates likely has the greatest influence on which threats birds experience during migration. Further, the species’ dependence on wetlands in agricultural landscapes during migration may make them vulnerable to threats related to agricultural practices, such as pesticide exposure.
Abstract Questions: Most clustering methods assume data are structured as discrete hyper-spheroidal clusters to be evaluated by measures of central-tendency. If vegetation data do not conform to this model, then vegetation data may be clustered incorrectly. What are the implications for cluster stability and evaluation if clusters are of irregular shape or density? Location: Southeast Australia Methods: We define misplacement as the placement of a sample in a cluster other than (distinct from) its nearest neighbour and hypothesise that optimising homogeneity incurs the cost of higher rates of misplacement. The Chameleon algorithm emphasises interconnectivity and thus is sensitive to the shape and distribution of clusters. We contrasted its solutions with those of traditional non-hierarchical and hierarchical (agglomerative and divisive) approaches. Results: Chameleon-derived solutions had lower rates of misplacement and only marginally higher heterogeneity than those of k-means in the range 15–60 clusters, but their metrics converged with larger numbers of clusters. Solutions derived by agglomerative clustering had the best metrics (and divisive clustering the worst) but both produced inferior high-level solutions clusters to those of Chameleon by merging distantly-related clusters. Conclusions: Our results suggest that Chameleon may have an advantage over traditional algorithms at when data exhibit discontinuities and variable structure, potentially producing more stable solutions (due to lower rates of misplacement), but scoring lower on traditional metrics of central-tendency. Chameleon’s advantages are less obvious in the partitioning of data from continuous gradients, however its graph-based partitioning protocol facilitates hierarchical integration of solutions.
Birds of prey frequently feature in reintroductions and the hacking technique is typically used. Hacking involves removing large nestlings from donor populations, transferring them to captivity, feeding them ad libitum. Potentially, via the hacking method, stress of captivity and disruption of parental feeding may be detrimental. Alternatively, provision of ad libitum food may be advantageous. Although hacking has underpinned reintroduction project successes there has been no research on how the method may affect the health and nutritional status of translocated birds during captivity. We compared blood chemistry data from 55 young White-tailed Eagles, translocated from Norway as part of the species’ reintroduction to Scotland, from sampling soon after arriving in captivity and again (≈ 42 d later) before their release. Numerous significant differences between first and second samples were found, but no significant interactions showed that sexes responded similarly to captivity. According to hematological and biochemical metrics, individuals showed several changes during captivity, including in red blood cell parameters, plasma proteins and white cellular parameters related to the immune system, that indicated improved health status. Captivity with ad libitum food was associated with decreased urea and uric acid values: high values can indicate nutritional stress. Urea values became more normally distributed before release, indicating that ad libitum food had reduced nutritional differences between early nestlings in the season and later ones. Despite plentiful food, both sexes lost body mass before release, suggesting an inherent physiological mechanism to improve flight performance in fledglings. We conclude that hacking improved the health and nutritional status of released eagles which is likely to enable birds to cope with greater costs of exploratory behavior which they may require in reintroduction projects. In this context, we note the absence of survival differences between hacked and wild raptors in previous research.
An individual’s size in early stages of life may be an important source of individual variation in lifetime reproductive performance, as size effects on ontogenetic development can have cascading physiological and behavioral consequences throughout life. Here, we explored how natal size influences subsequent reproductive performance in grey seals (Halichoerus grypus) using repeated encounter and reproductive data on a marked sample of 363 females that were measured for length at ~4 weeks of age and eventually recruited to the Sable Island breeding colony. Two reproductive traits were considered: provisioning performance (mass of weaned offspring), modeled using linear mixed effects models; and reproductive frequency (rate at which a female returns to breed), modeled using mixed-effects multistate mark-recapture models. Mothers with the longest natal lengths produced pups 8 kg heavier and were 20% more likely to breed in a given year than mothers with the shortest lengths. Correlation in body lengths between natal and adult life stages, however, is weak: longer pups do not grow to be longer than average adults. Thus covariation between natal length and future reproductive performance appears to be a carry-over effect, where the size advantages afforded in early juvenile stages may allow enhanced long-term performance in adulthood.
Wolves (Canis lupus) can exert top-down pressure and shape ecological communities through selective predation of ungulates and beavers (Castor Canadensis). Considering their ability to shape communities through predation, understanding wolf foraging decisions is critical to predicting their ecosystem level effects. Specifically, if wolves are optimal foragers, consumers that optimize tradeoffs between cost and benefits of prey acquisition, changes in these factors may lead to prey switching or negative-density dependent selection with potential consequences for community stability. For wolves, factors affecting cost and benefits include prey vulnerability, risk, reward, and availability which can vary temporally. We described wolf diet in by frequency of occurrence and percent biomass and characterized diet in relation to optimal foraging using prey remains found in wolf scats on Isle Royale National Park, Michigan, USA during May–October 2019–2020. We used logistic regression to estimate prey consumption over time. We predicted prey with temporal variation in cost (vulnerability and/or availability) such as adult and calf moose (Alces alces) and beaver to vary in wolves’ diet. We analyzed 206 scats and identified 62% of remains as beaver, 26% as and moose, and 12% as other (birds, smaller mammals, and wolves). Adult moose were more likely to occur in wolf scat in May, when moose are in poor condition following winter. Similarly, the occurrence of moose calves peaked June–mid July following parturition but before their vulnerability declined as they matured. In contrast, beaver occurrence in wolf scat did not change over time, possibly reflecting the importance of low handling cost prey items for recently introduced lone or paired wolves. Our results demonstrate that wolf diet is plastic and responsive to temporal changes in prey acquisition cost as predicted by optimal foraging theory. Temporal fluctuation in diet may influence wolves’ ecological role if prey respond to increased predation risk by altering their foraging or breeding behavior.
1. Given the sharp increase in agricultural and infrastructure development and the paucity of widespread data available for making conservation management decisions, a more rapid and accurate tool for identifying fish fauna in the world’s largest freshwater ecosystem, the Amazon, is needed. 2. Current strategies for identification of freshwater fishes require high levels of training and taxonomic expertise for morphological identification or genetic testing for species recognition at a molecular level. 3. To overcome these challenges, we built an image masking model (U-Net) and a convolutional neural net (CNN) to classify Amazonian fish in photographs. Fish used as training data were collected and photographed in tributaries in seasonally flooded forests of the upper Morona River valley in Loreto, Peru in 2018 and 2019. 4. Species identifications in the training images (n = 3,068) were verified by expert ichthyologists. These images were supplemented with photographs taken of additional Amazonian fish specimens housed in the ichthyological collection of the Smithsonian’s National Museum of Natural History. 5. We generated a CNN model that identified 33 genera of fishes with a mean accuracy of 97.9%. Wider availability of accurate freshwater fish image recognition tools, such as the one described here, will enable fishermen, local communities and community scientists to more effectively participate in collecting and sharing data from their territories to inform policy and management decisions that impact them directly.