enhancing-an-avian-sound-recognition-model-s-detection-precision-via

Enhancing an Avian Sound Recognition Model&#39;s Detection Precision via Logistic Regression of Large Acoustic Datasets: A Case Study of the European Robin (<em>Erithacus rubecula</em>)

Passive acoustic monitoring (PAM) has become an invaluable tool for biodiversity research, enabling the non-invasive collection of vast datasets. However, ...

Liverpool John Moores University

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations.

Predicting population change from models based on habitat availability and utilization.

Widespread and ever-increasing anthropogenic impacts in the marine environment are driving a need to develop more efficient survey methods for monitoring changes in marine biodiversity. There is a particular urgent need for survey methods that could more rapidly and effectively detect change in species richness, abundance and community composition. Here, test the suitability of the Mackinnon Lists Technique for use in the marine environment by testing its effectiveness for rapid assessment of fish communities. The MacKinnon Lists Technique is a time-efficient and cost-effective sampling method developed for studying avian tropical biodiversity, in which several list samples of species can be collected from a single survey. Using the well-established MaxN approach on data from deployments of a Baited Remote Underwater Video Systems for comparison, we tested the suitability of the MacKinnon Lists Technique for use in marine environments by analysing tropical reef fish communities. Using both methods for each data set, differences in community composition between depths and levels of protection were assessed. Both methods were comparable for diversity and evenness indices with similar ranks for species. Multivariate analysis showed that the MacKinnon Lists Technique and MaxN detected similar differences in community composition at different depths and protection status. However, the MacKinnon Lists Technique detected significant differences between factors when fewer videos (representing reduced survey effort) were used. We conclude that the MacKinnon Lists Technique is at least as effective as the widely used MaxN method for detecting differences between communities in the marine environment and suggest can do so with lower survey effort. The MacKinnon Lists Technique has the potential to be widely used as an effective new tool for rapid conservation monitoring in marine ecosystems.

The MacKinnon Lists Technique: An efficient new method for rapidly assessing biodiversity and species abundance ranks in the marine environment.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small "many analyst" study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology.

Urbanization and human population growth have significantly increased the presence of anthropogenic materials in natural environments, prompting growing interest in how wildlife may be adapting to these changes. One such behavioral response is the incorporation of anthropogenic materials into animal nests, a phenomenon that has raised concerns due to its potential harmful effects, such as entanglement or ingestion. While this behavior has been documented widely in birds, it remains underreported in other taxa, partly due to the difficulty of locating nests. In this study, we describe multiple instances of anthropogenic materials (including plastic) being incorporated into the hibernation nests of European hedgehogs, . Four nests were dissected, of which two nests contained anthropogenic materials, including a plastic bag, foil and expanded polystyrene. These findings suggest that hedgehogs may opportunistically use available anthropogenic materials in nest construction, potentially as a response to urban environments. Our findings help broaden the understanding of mammalian responses to urbanization and emphasize the need to investigate whether the incorporation of these materials is likely to be harmful or adaptive to hedgehogs and for mammals generally.

Article	Year
Predicting population change from models based on habitat availability and utilization. Proceedings. Biological sciences\| PubMed ID: 30991925	2019
The MacKinnon Lists Technique: An efficient new method for rapidly assessing biodiversity and species abundance ranks in the marine environment. PloS one\| PubMed ID: 32320414	2020
Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. BMC biology\| PubMed ID: 39915771	2025
From Leaves to Litter: Use of Anthropogenic Nesting Materials in Hibernation Nests of the European Hedgehog. Ecology and evolution\| PubMed ID: 41488793	2026

Ross Macleod

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