Biology subjects

Cavalcante, T.

Publications and source records attributed to Cavalcante, T..

4 recordsLinked to original sources

bioRxiv2026

Correcting overprediction reduces the propagation of uncertainty from species distribution models into spatial conservation prioritization

Effective conservation planning increasingly relies on species distribution models (SDMs) to guide where actions deliver the greatest biodiversity benefits through spatial conservation prioritization. However, SDMs are inherently uncertain, and this uncertainty propagates through prioritization processes, affecting the identification of priority areas and influencing conservation decisions. Here, we evaluate whether correcting SDM overprediction reduces uncertainty propagation into spatial conservation prioritization. Using two large European datasets of vertebrates and invertebrates, we compared unconstrained SDMs with models corrected for overprediction through a Bayesian integration of occurrences, expert range maps, and habitat suitability. We found that overprediction correction reduced spatial and performance uncertainty, with uncertainty strongly structured by model and algorithm choice and amplified when overprediction was not corrected. Although no single modelling adjustment fully eliminates uncertainty propagation from SDMs into prioritization, we demonstrate that overprediction correction consistently reduces it across datasets, taxa, and modelling approaches, highlighting its importance for robust conservation planning.

ecology↗

bioRxiv2026

ZonationR: An R interface to the Zonation software for reproducible spatial conservation prioritisation workflows

Systematic conservation planning provides a science-based framework for defining conservation goals and supporting transparent spatial decision-making under limited resources. Within this framework, spatial conservation prioritisation tools are widely used to identify areas of high biodiversity value by integrating information on species distributions, connectivity, costs, and other factors into spatially explicit recommendations. Zonation is one of the leading software tools in this field, producing hierarchical priority rankings of landscapes based on conservation value. However, its standard workflow typically relies on manual steps for data preparation, execution, and post-processing, which can become inefficient and difficult to reproduce when multiple scenarios are analysed, limiting accessibility and broader uptake. We introduce ZonationR, an R package that provides a streamlined interface to the Zonation software, enabling fully reproducible and automated spatial prioritisation workflows. The package integrates the entire analysis pipeline, encompassing input preparation, execution of Zonation, and post-processing, while supporting both single-variant and multi-variant workflows. ZonationR also provides tools to explore and interpret outputs, including priority maps, feature performance curves, cost summaries, feature representation metrics, and similarity assessments between prioritisation solutions. By linking directly to the original Zonation engine, the package enables users to benefit from ongoing methodological developments in Zonation and access its functionality through a transparent, script-based workflow, thereby reducing technical barriers to running and understanding spatial prioritisation analyses. Beyond these advantages, its integration within the R environment supports iterative testing of conservation scenarios and more rigorous assessment of methodological decisions, while facilitating seamless connections with wider ecological workflows (e.g., species distribution modelling). As conservation planning increasingly relies on large, complex, multi-source datasets and integrative approaches, such integration is essential for enabling robust, transparent, and reproducible decision-making across spatial scales.

bioinformatics↗

bioRxiv2025

Beyond species-level planning: The role of bioclimatic variation within species distributions

Conserving biodiversity under a changing climate is a complex challenge that requires comprehensive conservation planning approaches accounting for both current biodiversity patterns and the diverse ecological and environmental changes that species and ecosystems are likely to encounter over time. Systematic conservation planning (SCP) offers a strategic framework to meet this challenge by prioritizing areas that promote species persistence and ecological resilience. Traditionally, SCP focuses on conserving adequate amounts of species distributions to ensure their long-term persistence. More recently, partitioning species distributions into bioclimatic components has emerged to explicitly represent niche variability, enhancing adaptive capacity by preserving local adaptations and genetic diversity across environmental gradients. Despite this conceptual progress, empirical comparisons of species-level and bioclimatic component prioritization remain scarce. This study aimed to compare species-level and bioclimatic component prioritization by assessing their trade-offs and effectiveness in supporting species persistence and ecological resilience. Specifically, we aimed to (i) assess the surrogacy between species-level and bioclimatic component prioritizations, (ii) examine their spatial overlap and divergence, and (iii) quantify and compare environmental heterogeneity within priority areas identified by each approach. We found that species-level and bioclimatic component prioritizations act as reasonable surrogates for one another overall, but species-level prioritization tended to underrepresent the least-covered bioclimatic components, with failures to capture certain components in the top-ranked areas. Spatial overlap between the two approaches was generally high, though it declined with more restrictive thresholds and under future conditions. Additionally, bioclimatic component prioritizations consistently captured higher within-group multivariate dispersion in environmental heterogeneity in selected areas. Our findings highlight that bioclimatic component prioritization captures greater environmental heterogeneity and complements species-based approaches by better representing niche diversity. Integrating both strategies may offer a more robust path toward climate-resilient conservation planning that accounts for ecological requirements and environmental variation.

ecology↗

bioRxiv2025

Synergies and trade-offs between maintaining climate niche variability and preserving climate stability

The impact of climate change on biodiversity accelerates, calling for climate resilient conservation strategies such as protecting areas of high climatic stability (i.e. climate refugia) or protecting the variability of species climatic niches (to preserve adaptive potential). Developing a spatial framework that integrates both strategies, we identify priorities to protect climatic niche components of 1,207 European vertebrates. Priority areas for protecting climatic niches under low climate velocity or low magnitude were respectively found in mountainous/southern regions and in northern/eastern Europe. These synergy areas overlapped by 48-73% with single-objective prioritizations focused on either niche components or climatic stability. Trade-offs occur where climatic niches diversity is high but climate stability is low, such as eastern Europe (velocity) or the Mediterranean and North Fennoscandia (magnitude). Our results reveal spatial mismatches between climate refugia and spatial priorities to preserve adaptive potential, emphasizing the need to combine both strategies in conservation planning.

ecology↗