Loading...
103 results
Search Results
Now showing 1 - 10 of 103
- Influence of macrohabitat preferences on the distribution of European brook and river lampreys: implications for conservation and managementPublication . Ferreira, A.F.; Quintella, B.R.; Maia, C.; Mateus, C.S.; Alexandre, C.M.; Capinha, César; Almeida, P.R.The European river lamprey, Lampetra fluviatilis (L.), and the European brook lamprey, Lampetra planeri (Bloch, 1784), are considered highly threatened in Portugal. However, the lack of information about the ecology and distribution of these species poses difficulties to the identification of concrete actions directed to their conservation. A total of 401 sampling sites, randomly distributed throughout the entire Portuguese mainland territory were selected, and Lampetra sp. ammocoetes presence or absence checked with electrofishing. These data, together with 11 macrohabitat predictors, were analyzed using Boosted Regression Trees (BRTs). The BRT models consistently identified five environmental variables as the most important for predicting the distribution of European brook and river lamprey ammocoetes: altitude, distance to coast, sand, maximum temperature of the warmest month and precipitation of the driest month. The relationships of these variables with the species probability of occurrence suggest that lampreys occur in low altitude river stretches (<170 m), relatively close to the coast (<150 km) and with a sandy substrate (>70% sand). In addition, intermediate values of temperature and precipitation were also found to have a positive correlation with the species occurrence. A map with the probability of occurrence of Lampetra sp. in Portugal was generated and stretches of rivers were delimited with different conservation priorities. Rivers classified with the highest level of conservation priority were considered to be proposed as Special Areas of Conservation, under the Natura 2000 Networking Programme.
- Modelo do padrão espaciotemporal e predição da Covid-19 em Portugal continentalPublication . Silva, Melissa; Roquette, Rita; Rocha, Jorge; Capinha, CésarA COVID-19 foi declarada pela OMS como doença pandémica em março de 2020, constituindo atualmente um dos maiores problemas de saúde pública a nível global. Deste modo, é fundamental a aplicação de métodos que possibilitem um melhor conhecimento sobre os processos de difusão do vírus a nível espacial e espaciotemporal. Neste sentido, procurou-se compreender a distribuição espacial e a influência da mobilidade nos processos de difusão da patologia COVID-19 em Portugal Continental a nível municipal; identificar os padrões espaciotemporais de propagação do vírus; efetuar uma análise de risco por setor de atividade e determinar o possível comportamento futuro da incidência de casos. Assim, verificou-se que a maioria dos hotspots de casos ocorrem nas Áreas Metropolitanas. A análise espaciotemporal identificou a maioria dos municípios como oscillating hotspots. A probabilidade de densidade de casos apresenta um padrão de distribuição semelhante à exceção do setor dos Estudantes que apresentam uma maior probabilidade nos municípios do interior do país. O modelo preditivo apresentou um erro reduzido, e prevê que o número de casos continue a oscilar.
- Sustainability of large language models: user perspectivePublication . Pipek, Pavel; Canavan, Shane; Canavan, Susan; Capinha, César; Gippet, Jérôme MW; Novoa, Ana; Pyšek, Petr; Souza, Allan T; Wang, Shengyu; Jarić, IvanLarge language models (LLMs) are becoming an integral part of our daily work. In the field of ecology, LLMs are already being applied to a wide range of tasks, such as extracting georeferenced data or taxonomic entities from unstructured texts, information synthesis, coding, and teaching (Methods Ecol Evol 2024; Npj Biodivers 2024). Further development and increased use of LLMs in ecology, as in science in general, is likely to intensify and accelerate the process of research and increase publication output—thus pressuring scientists to keep up with the elevated pace, which in turn creates a feedback loop by promoting even greater LLM use. However, this all comes at a cost. While not directly borne by end users, aside from occasional response delays, LLMs require considerable computational power and are energy-demanding during both their initial training phase and their subsequent operational use (Nature 2025). Furthermore, partly externalized energy costs are linked to intensive searching and processing of discovered sources as part of Deep Research. Currently, it remains challenging to estimate the total energy costs of LLMs, largely due to limited transparency from their companies of origin.
- Niche modelling to guide conservation actions in France for the endangered crayfish Austropotamobius pallipes in relation to the invasive Pacifastacus leniusculusPublication . Préau, Clémentine; Nadeau, Iris; Sellier, Yann; Isselin‐Nondedeu, Francis; Bertrand, Romain; Collas, Marc; Capinha, César; Grandjean, FrédéricThe white‐clawed crayfish (Austropotamobius pallipes) is globally endangered due to the impacts of habitat modification and fragmentation, water pollution, climate change, and invasive species, particularly the signal crayfish (Pacifastacus leniusculus). These pressures have caused the decline of A. pallipes populations in Europe, demonstrating the importance of predicting the species' potential distribution under current and future conditions. Focusing on the watercourses of mainland France, we aimed to identify suitable areas for A. pallipes to guide the conservation of current populations and future introduction actions or protection measures. 2. We applied ecological niche modelling to model the potential distribution of both A. pallipes and P. leniusculus and identified locations suitable for A. pallipes only. We also assessed the potential distribution of the species under two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5, respectively describing low‐warming and high‐warming conditions. 3. We found that A. pallipes and P. leniusculus exploit equivalent niches in France. Despite this, under current conditions, about 5% of the study area simultaneously records a high suitability for A. pallipes and a low suitability for P. leniusculus and is therefore of significant conservation interest. This percentage remains relatively stable under RCP 2.6 for 2050 and 2100, but decreases to 2% under RCP 8.5 for 2100. 4. Ecological niche modelling can supply crucial guidance for conservation actions aimed at protecting endangered species at a national scale by identifying sites most suitable for protection and sites where climate change and invasive species constitute a threat.
- Forecasting the abundance of disease vectors with deep learningPublication . Ceia-Hasse, Ana; Sousa, Carla A.; Gouveia, Bruna R.; Capinha, CésarArboviral diseases such as dengue, Zika, chikungunya or yellow fever are a worldwide concern. The abundance of vector species plays a key role in the emergence of outbreaks of these diseases, so forecasting these numbers is fundamental in preventive risk assessment. Here we describe and demonstrate a novel approach that uses state-of-the-art deep learning algorithms to forecast disease vector abundances. Unlike classical statistical and machine learning methods, deep learning models use time series data directly as predictors and identify the features that are most relevant from a predictive perspective. We demonstrate for the first time the application of this approach to predict short-term temporal trends in the number of Aedes aegypti mosquito eggs across Madeira Island for the period 2013 to 2019. Specifically, we apply the deep learning models to predict whether, in the following week, the number of Ae. aegypti eggs will remain unchanged, or whether it will increase or decrease, considering different percentages of change. We obtained high predictive performance for all years considered (mean AUC = 0.92 ± 0.05 SD). Our approach performed better than classical machine learning methods. We also found that the preceding numbers of eggs is a highly informative predictor of future trends. Linking our approach to disease transmission or importation models will contribute to operational, early warning systems of arboviral disease risk.
- Assessing the current and future suitability to the Asian Tiger mosquito, a dengue and Zika vector, in major cities in EuropePublication . Oliveira, Sandra; Rocha, Jorge; Capinha, César; Sousa, CarlaThe Asian tiger mosquito (Aedes albopictus) is a competent vector of numerous diseases, including the dengue and Zika viruses, and public health concerns have encouraged extensive research to model the environmental suitability to the mosquito. We evaluated the level of consensus between published predictions for the European continent and for a set of 65 major cities. We identified consensus hotspots of high and low suitability and the potential variations of suitability levels between present-day and future climatic conditions. A strong inter-model agreement was found regarding the future expansion of the mosquito to northern and eastern Europe. About 83% of cities are predicted as suitable to the establishment of the mosquito in the future, including in northern Europe, and no decrease in suitability is expected. These results show the importance of planning for vector surveillance and control, even in areas where the risk of establishment of Ae. albopictus is currently low.
- Spatial correlates of COVID-19 first wave across continental PortugalPublication . Barbosa, Bruno; Silva, Melissa; Capinha, César; Garcia, Ricardo; Rocha, JorgeThe first case of COVID-19 in continental Portugal was documented on the 2nd of March 2020 and about seven months later more than 75 thousand infections had been reported. Although several factors correlate significantly with the spatial incidence of COVID-19 worldwide, the drivers of spatial incidence of this virus remain poorly known and need further exploration. In this study, we analyse the spatiotemporal patterns of COVID-19 incidence in the at the municipality level and test for significant relationships between these patterns and environmental, socioeconomic, demographic and human mobility factors to identify the mains drivers of COVID-19 incidence across time and space. We used a generalized liner mixed model, which accounts for zero inflated cases and spatial autocorrelation to identify significant relationships between the spatiotemporal incidence and the considered set of driving factors. Some of these relationships were particularly consistent across time, including the ‘percentage of employment in services’; ‘average time of commuting using individual transportation’; ‘percentage of employment in the agricultural sector’; and ‘average family size’. Comparing the preventive measures in Portugal (e.g., restrictions on mobility and crowd around) with the model results clearly show that COVID-19 incidence fluctuates as those measures are imposed or relieved. This shows that our model can be a useful tool to help decision-makers in defining prevention and/or mitigation policies.
- Predicting the time of arrival of the Tiger mosquito (Aedes albopictus) to new countries based on trade patterns of tyres and plantsPublication . Oliveira, Sandra; Capinha, César; Rocha, JorgeThe mosquito Aedes albopictus is a highly invasive species, which continues to widen its range worldwide. International trade is a major driver of its dispersal, in particular the imports of tyres and live plants. As a competent vector of numer-ous diseases, among which Zika and dengue, the spread of this species raises public health concerns.2. Based on indicators of trade volumes and trends along 15 years, combined with climatic similarity and geographic distance between countries, we tested a model aimed at estimating the time of arrival of the species in new countries. We used partial least squares regression to model the year of first recording of the species in previously invaded countries. The fitted model was subsequently applied to predict the expected time of arrival in countries where the species is still absent.3. The model was able to estimate the year of first recording of the species with up to 2 years difference for 90% of the countries. Temperature differences among countries and the number of exporting countries where the species is present were the most important predictors. Estimates indicate that Aedes albopictusmight enter all countries assessed by 2035, earlier in Africa and South America than in Eastern and Northern Europe. However, passive transportation by ground vehicles may accelerate the dispersal of the species, whereas environmental suit-ability may have seasonal limits, factors that were not integrated in the model.4. Policy implications: Surveillance and control strategies require timely adjustments to curb the spread of this species, and public health policies must adapt to tackle the potential exposure to vector- borne diseases. Our study highlights that, in the absence of transnational strategies to contain the dispersal of the species, a large number of new countries will be colonized in the coming years, in different re-gions of the world, where the implementation of timely preventive measures is paramount.
- Drivers of future alien species impacts: an expert‐based assessmentPublication . Essl, Franz; Lenzner, Bernd; Bacher, Sven; Bailey, Sarah; Capinha, César; Daehler, Curtis; Dullinger, Stefan; Genovesi, Piero; Hui, Cang; Hulme, Philip E.; Jeschke, Jonathan M.; Katsanevakis, Stelios; Kühn, Ingolf; Leung, Brian; Liebhold, Andrew; Liu, Chunlong; MacIsaac, Hugh J.; Meyerson, Laura A.; Nuñez, Martin A.; Pauchard, Aníbal; Pyšek, Petr; Rabitsch, Wolfgang; Richardson, David M.; Roy, Helen E.; Ruiz, Gregory M.; Russell, James C.; Sanders, Nathan J.; Sax, Dov F.; Scalera, Riccardo; Seebens, Hanno; Springborn, Michael; Turbelin, Anna; Kleunen, Mark; Holle, Betsy; Winter, Marten; Zenni, Rafael D.; Mattsson, Brady J.; Roura‐Pascual, NuriaUnderstanding the likely future impacts of biological invasions is crucial yet highly challenging given the multiple relevant environmental, socio-economic and societal contexts and drivers. In the absence of quantitative models, methods based on expert knowledge are the best option for assessing future invasion trajectories. Here, we present an expert assessment of the drivers of potential alien species impacts under contrasting scenarios and socioecological contexts through the mid-21st century. Based on responses from 36 experts in biological invasions, moderate (20%-30%) increases in invasions, compared to the current conditions, are expected to cause major impacts on biodiversity in most socioecological contexts. Three main drivers of biological invasions-transport, climate change and socio-economic change-were predicted to significantly affect future impacts of alien species on biodiversity even under a best-case scenario. Other drivers (e.g. human demography and migration in tropical and subtropical regions) were also of high importance in specific global contexts (e.g. for individual taxonomic groups or biomes). We show that some best-case scenarios can substantially reduce potential future impacts of biological invasions. However, rapid and comprehensive actions are necessary to use this potential and achieve the goals of the Post-2020 Framework of the Convention on Biological Diversity.
- Biogeography and global flows of 100 major alien fungal and fungus‐like oomycete pathogensPublication . Schertler, Anna; Lenzner, Bernd; Dullinger, Stefan; Moser, Dietmar; Bufford, Jennifer L.; Ghelardini, Luisa; Santini, Alberto; Capinha, César; Monteiro, Miguel; Reino, Luís; Wingfield, Michael J.; Seebens, Hanno; Thines, Marco; Dawson, Wayne; van Kleunen, Mark; Kreft, Holger; Pergl, Jan; Pyšek, Petr; Weigelt, Patrick; Winter, Marten; Essl, FranzAim: Spreading infectious diseases associated with introduced pathogens can have devastating effects on native biota and human livelihoods. We analyse the global distribution of 100 major alien fungal and oomycete pathogens with substantial socio-economic and environmental impacts and examine their taxonomy, ecological characteristics, temporal accumulation trajectories, regional hot- and coldspots of taxon richness and taxon flows between continents. Location: Global. Taxon: Alien/cryptogenic fungi and fungus-like oomycetes, pathogenic to plants or animals. Methods: To identify over/underrepresented classes and phyla, we performed Chi2 tests of independence. To describe spatial patterns, we calculated the region-wise richness and identified hot- and coldspots, defined as residuals after correcting taxon richness for region area and sampling effort via a quasi-Poisson regression. We examined the relationship with environmental and socio-economic drivers with a multiple linear regression and evaluated a potential island effect. Regional first records were pooled over 20-year periods, and for global flows the links between the native range to the alien regions were mapped. Results: Peronosporomycetes (Oomycota) were overrepresented among taxa and regional taxon richness was positively correlated with area and sampling effort. While no island effect was found, likely due to host limitations, hotspots were correlated with human modification of terrestrial land, per capita gross domestic product, temperate and tropical forest biomes, and orobiomes. Regional first records have increased steeply in recent decades. While Europe and Northern America were major recipients, about half of the taxa originate from Asia.Main Conclusions: We highlight the putative importance of anthropogenic drivers, such as land use providing a conducive environment, contact opportunities and susceptible hosts, as well as economic wealth likely increasing colonisation pressure. While most taxa were associated with socio-economic impacts, possibly partly due to a bias in research focus, about a third show substantial impacts to both socio-economy and the environment, underscoring the importance of maintaining a wholescale perspective across natural and managed systems.