http://hdl.handle.net/10174/42 2026-04-28T19:34:35Z http://hdl.handle.net/10174/41909 Title: Refined gap analysis for biodiversity conservation under climate change Authors: Ebrahimi, E; Ahmadzadeh, F; Abdoli, A; BASTOS ARAÚJO, MIGUEL; Naimi, B Abstract: In concert with climate change, our planet faces unprecedented biodiversity loss, with half of all species at risk of extinction. Despite global conservation efforts, the biodiversity crisis continues to outpace these actions. The Global Biodiversity Framework seeks to halt this trend by expanding protected areas (PAs) to cover 30 % of terrestrial and aquatic environments by 2030. Conservation gap analysis, based on species distribution models (SDMs), is vital for assessing the effectiveness of PAs under future climate scenarios. However, traditional gap analysis often relies on binary predictions, leading to critical information loss and failing to target multiple species groups simultaneously or address dynamic species distributions. To overcome these limitations, we propose a refined gap analysis method using a fuzzy approach with machine learning models. Our method incorporates multiple species groups, dispersal scenarios, and uncertainty assessments, offering improved conservation planning. We applied this approach to amphibians—a taxon highly vulnerable to climate change—and evaluated PA effectiveness and potential refugia under various future scenarios. Our findings show that while approximately 60 % of amphibians currently protected by PAs may continue to find refuge, their average habitat suitability is expected to decline significantly under future conditions, indicating potential losses in PA effectiveness. Our refined fuzzy gap analysis captures a continuous spectrum of habitat suitability, facilitates species comparability, and integrates multiple conservation targets. This approach provides a robust tool to guide biodiversity strategies, ensuring that conservation efforts are more adaptive, resilient, and precise in the face of climate change uncertainties. 2025-03-10T00:00:00Z http://hdl.handle.net/10174/41908 Title: Más depredadores de lo esperado: la pirámide de la biodiversidad es más bien un cuadrado Authors: BASTOS ARAUJO, MIGUEL Abstract: Durante décadas, la imagen que ha dominado los manuales de Ecología ha sido la de la pirámide de la biodiversidad: mucha biomasa vegetal en la base, menos herbívoros encima y todavía menos depredadores en la cúspide. Esa intuición es correcta para describir el flujo de energía, pero resulta engañosa si la convertimos en una regla sobre cómo se distribuye el número de especies. 2025-12-18T00:00:00Z http://hdl.handle.net/10174/41907 Title: Climate correlates of bluetongue incidence in southern Portugal Authors: Mestre, F; Pereira, AL; BASTOS ARAUJO, MIGUEL Abstract: Model forecasts of the spatiotemporal occurrence dynamics of diseases are necessary and can help understand and thus manage future disease outbreaks. In our study, we used ecological niche modelling to assess the impact of climate on the vector suitability for bluetongue disease, a disease affecting livestock production with important economic consequences. Specifically, we investigated the relationship between the occurrence of bluetongue outbreaks and the environmental suitability of each of the four vector species studied. We found that the main vector for bluetongue disease, Culicoides imicola, a typically tropical and subtropical species, was a strong predictor for disease outbreak occurrence in a region of southern Portugal from 2004 to 2021. The results highlight the importance of understanding the climatic factors that might influence vector presence to help manage infectious disease impacts. When diseases impact economically relevant species, the impacts go beyond mortality and have important economic consequences. 2024-06-20T23:00:00Z http://hdl.handle.net/10174/41906 Title: Coastal oceanographic connectivity at the global scale: a dataset of pairwise probabilities and travel times derived from biophysical modeling Authors: Assis, J; Fragkopoulou, E; Serão, E; BASTOS ARAÚJO, MIGUEL Abstract: Ocean currents are fundamental drivers of marine biodiversity distribution, mediating the exchange of genetic material and individuals between populations. Their effect ranges from creating barriers that foster isolation to facilitating long-distance dispersal, which is crucial for species expansion and resilience in the face of climate change. Despite the significance of oceanographic connectivity, comprehensive global estimates remain elusive, hindering our understanding of species’ dispersal ecology and limiting the development of effective conservation strategies. We present the first dataset of connectivity estimates (including probability of connectivity and travel time) along the world’s coastlines. The dataset is derived from Lagrangian simulations of passive dispersal driven by 21 years of ocean current data and can be combined with species’ biological traits, including seasonality and duration of planktonic dispersal stages. Alongside, we provide coastalNet, an R package designed to streamline access, analysis, and visualization of connectivity estimates. The dataset provides a new benchmark for research in oceanographic connectivity, enabling a deeper exploration of the complex dynamics of coastal marine ecosystems and informing more effective conservation strategies. 2025-05-02T23:00:00Z