Agent-based simulations improve abundance estimation.

Abundance is a fundamental characteristic of every biological population and is the focus of many research programs in ecology and conservation. In this paper I give an overview of the challenges of estimating abundance. I argue that truly understanding, validating, and refining the field techniques and quantitative methods used to estimate abundance can largely benefit from agent-based simulations. I illustrate this through the example of bird point counts and introduce the software bSims to test statistical and biological assumptions for estimating abundance and to aid survey design.

Domains of scale in cumulative effects of energy sector development on boreal birds.

Context: Industrial development in Canada's boreal forest creates cumulative environmental effects on biodiversity. Some effects may be scale-dependent, creating uncertainty in understanding and hindering effective management. Objectives: We estimated cumulative effects of energy sector development on distributions of sixteen migratory songbird species at multiple spatial scales within the boreal region of Alberta, Canada, and evaluated evidence for scale domains in species responses. Methods: We used a hierarchical, multi-scale sampling and modelling framework to compare effects of oil and gas footprint on songbirds at five spatial scales. We used Bayesian Lasso to facilitate direct comparison of parameter estimates across scales, and tested for differences in grouped parameter estimates among species. Results: We found consistent scale-dependent patterns across species, showing variable responses to development occurring at the smallest scale, little effect at intermediate scales, and stronger, mainly positive effects at the largest scales. Differences in grouped parameter estimates across scales showed strong evidence for scale domains in the response of songbirds to energy sector development. Conclusions: We concluded that variable effects at the smallest scale represented individual habitat selection, while larger scale positive effects reflected expanding distributions of open habitat- and disturbance-associated species in areas of high oil and gas footprint. Our results show that single-scale analyses do not reflect population processes occurring at other scales. Future research on linking patterns at different scales is required to fully understand cumulative effects of land use change on wildlife populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-023-01779-8.

Validation prediction: a flexible protocol to increase efficiency of automated acoustic processing for wildlife research.

Automated recognition is increasingly used to extract species detections from audio recordings; however, the time required to manually review each detection can be prohibitive. We developed a flexible protocol called "validation prediction" that uses machine learning to predict whether recognizer detections are true or false positives and can be applied to any recognizer type, ecological application, or analytical approach. Validation prediction uses a predictable relationship between recognizer score and the energy of an acoustic signal but can also incorporate any other ecological or spectral predictors (e.g., time of day, dominant frequency) that will help separate true from false-positive recognizer detections. First, we documented the relationship between recognizer score and the energy of an acoustic signal for two different recognizer algorithm types (hidden Markov models and convolutional neural networks). Next, we demonstrated our protocol using a case study of two species, the Common Nighthawk (Chordeiles minor) and Ovenbird (Seiurus aurocapilla). We reduced the number of detections that required validation by 75.7% and 42.9%, respectively, while retaining at least 98% of the true-positive detections. Validation prediction substantially improves the efficiency of using automated recognition on acoustic data sets. Our method can be of use to wildlife monitoring and research programs and will facilitate using automated recognition to mine bioacoustic data sets.

Range-constrained co-occurrence simulation reveals little niche partitioning among rock-dwelling Montenegrina land snails (Gastropoda: Clausiliidae).

AIM: Taxon co-occurrence analysis is commonly used in ecology, but it has not been applied to range-wide distribution data of partly allopatric taxa because existing methods cannot differentiate between distribution-related effects and taxon interactions. Our first aim was to develop a taxon co-occurrence analysis method that is also capable of taking into account the effect of species ranges and can handle faunistic records from museum databases or biodiversity inventories. Our second aim was to test the independence of taxon co-occurrences of rock-dwelling gastropods at different taxonomic levels, with a special focus on the Clausiliidae subfamily Alopiinae, and in particular the genus Montenegrina. LOCATION: Balkan Peninsula in south-eastern Europe (46N-36N, 13.5E-28E). METHODS: We introduced a taxon-specific metric that characterizes the occurrence probability at a given location. This probability was calculated as a distance-weighted mean of the taxon's presence and absence records at all sites. We applied corrections to account for the biases introduced by varying sampling intensity in our dataset. Then we used probabilistic null-models to simulate taxon distributions under the null hypothesis of no taxon interactions and calculated pairwise and cumulated co-occurrences. Independence of taxon occurrences was tested by comparing observed co-occurrences to simulated values. RESULTS: We observed significantly fewer co-occurrences among species and intra-generic lineages of Montenegrina than expected under the assumption of no taxon interaction. MAIN CONCLUSIONS: Fewer than expected co-occurrences among species and intrageneric clades indicate that species divergence preceded niche partitioning. This suggests a primary role of non-adaptive processes in the speciation of rock-dwelling gastropods. The method can account for the effects of distributional constraints in range-wide datasets, making it suitable for testing ecological, biogeographical, or evolutionary hypotheses where interactions of partly allopatric taxa are in question.

Correction: Within-Site Variation in Feather Stable Hydrogen Isotope (δ2Hf) Values of Boreal Songbirds: Implications for Assignment to Molt Origin.

[This corrects the article DOI: 10.1371/journal.pone.0163957.].

Within-Site Variation in Feather Stable Hydrogen Isotope (δ2Hf) Values of Boreal Songbirds: Implications for Assignment to Molt Origin.

Understanding bird migration and dispersal is important to inform full life-cycle conservation planning. Stable hydrogen isotope ratios from feathers (δ2Hf) can be linked to amount-weighted long-term, growing season precipitation δ2H (δ2Hp) surfaces to create δ2Hf isoscapes for assignment to molt origin. However, transfer functions linking δ2Hp with δ2Hf are influenced by physiological and environmental processes. A better understanding of the causes and consequences of variation in δ2Hf values among individuals and species will improve the predictive ability of geographic assignment tests. We tested for effects of species, land cover, forage substrate, nest substrate, diet composition, body mass, sex, and phylogenetic relatedness on δ2Hf from individuals at least two years old of 21 songbird species captured during the same breeding season at a site in northeastern Alberta, Canada. For four species, we also tested for a year × species interaction effect on δ2Hf. A model including species as single predictor received the most support (AIC weight = 0.74) in explaining variation in δ2Hf. A species-specific variance parameter was part of all best-ranked models, suggesting variation in δ2Hf was not consistent among species. The second best-ranked model included a forage substrate × diet interaction term (AIC weight = 0.16). There was a significant year × species interaction effect on δ2Hf suggesting that interspecific differences in δ2Hf can differ among years. Our results suggest that within- and among-year interspecific variation in δ2Hf is the most important source of variance typically not being explicitly quantified in geographic assignment tests using non-specific transfer functions to convert δ2Hp into δ2Hf. However, this source of variation is consistent with the range of variation from the transfer functions most commonly being propagated in assignment tests of geographic origins for passerines breeding in North America.

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity.

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors - thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance - or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human "footprint" and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.

Citizen science reveals unexpected continental-scale evolutionary change in a model organism.

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate.