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Tropical dry forests host essential mutualistic interactions between bats and plants, yet the intense fragmentation of these ecosystems threatens the persistence and structure of floral visitation networks. In Neotropical landscapes, these interactions exhibit high spatial and temporal variability driven by resource availability, plant turnover, and the mobility of bat pollinators. Despite substantial advances, community-level assessments that integrate β-diversity, modularity, and functional traits remain scarce, limiting our understanding of how bat–flower networks respond to habitat fragmentation. Here we show, using interaction-network and β-diversity analyses across eight fragments of Tropical Dry Forest in southwestern Colombia, that the bat–flower network is strongly modular and specialized, with modules primarily shaped by local plant composition. We found that species turnover, especially among plants, is the dominant component of β-diversity in interactions, whereas rewiring among co-occurring species is low and unrelated to geographic distance between fragments. We also demonstrate that four bat species form the cohesive core of the network and that morphological attributes such as body condition and face-skull ratio negatively predict their capacity to connect modules. These findings reveal how plant heterogeneity and bat mobility jointly determine network cohesion and functional redundancy in fragmented landscapes. Understanding these mechanisms is crucial for forecasting the resilience of bat–plant mutualisms under increasing anthropogenic pressures in tropical dry forests.
This study addresses the challenge of measuring multidimensional social exclusion in cities, since it cannot be adequately captured by isolated indicators such as income or education. Although the operational framework of composite indicators provides the means to synthesize multiple sub-indicators of social exclusion into a single measure, the scores generated for dozens or hundreds of urban areas hinder their interpretability. In this regard, clustering techniques, such as the k-means algorithm, use similarities in characteristics across urban areas to form smaller groups of social exclusion, thereby simplifying their interpretation and facilitating the planning of public policies. Despite these advantages, k-means has limitations. Methods for determining the ideal number of clusters yield inconsistent results and do not guarantee reliable clustering. Furthermore, the data-driven definition of the number of groups completely ignores the concept of social exclusion, which can make it difficult to interpret. This proposed Smart k-means balances reliability and interpretability by introducing two main innovations: (i) flexibility in defining the number of clusters, allowing for a range specified by the decision-maker, aligning empirical results with the conceptual construct of the multidimensional phenomenon; and (ii) an iterative procedure that identifies and excludes sub-indicators that do not contribute to the classification of social exclusion until the average silhouette width reaches a threshold of 0.50, ensuring cohesive and well-separated clusters. The method's applicability is demonstrated through an analysis of social exclusion across eight cities in the state of Paran & aacute;, Brazil, highlighting its potential to support the development of more targeted and effective public policies.
Mountain environments are critical biodiversity hotspots and understanding species responses to elevation is crucial in an era of global warming.Butterflies,as sensitive bioindicators,are altering their zonation along elevational gradients.Here we synthesized 66 studies published over the last 32 years from 28 countries to:1)systematically identify patterns and gaps in mountain butterfly studies,2)highlight methodological and geographical biases,and 3)quantify butterfly responses to elevation via a global meta-analysis.We assessed butterfly variables grouped into three categories:species diversity(e.g.,richness and abundance),functional traits(e.g.,body size and melanization)and life-history traits(e.g.,development time).Our meta-analysis revealed a significant decline in species diversity with increasing elevation worldwide.In contrast,both functional and life-history traits showed a significant increase.The negative diversity pattern was significantly stronger in tropical mountains,while the decline occurred across both high and low mountains.Critically,this diversity decline was only robustly detected when studies sampled over 70％of the mountain's elevational gradient,underscoring the crucial influence of sampling adequacy on the patterns of butterfly diversity along mountains.Our findings demonstrate that comprehensive sampling is essential to accurately detect macroecological patterns.We therefore urge expanded sampling of mountainous gradients to provide the data necessary for the conservation of butterflies and to fully understand the role of mountains as climate refuges.
This review raises awareness of the Cerrado’s value to society and serves as an informative guide for ecology professionals, policymakers, and anyone interested in biodiversity conservation. Herein, we comprehensively and critically address the ongoing degradation process of the Cerrado, highlighting its ecological complexity, biological diversity, and strategic importance for environmental sustainability and climate change mitigation in Brazil. We examine the diversity of ecosystems in the Cerrado, highlighting their specific vulnerabilities and the inadequacy of current legal instruments to guarantee their protection. Our analysis covers the main vectors of pressure on the territory, such as the advance of the agricultural frontier, the predatory use of fire, the silent water crisis, and threats to Indigenous peoples, highlighting how these factors operate in an interconnected manner to disrupt the region’s ecosystem services. The limitations of current conservation policies and the invisibility of species and ecosystems in the face of the dominant legal and economic systems are also discussed. Our review proposes ways to mitigate or even reverse this scenario, including increasing the number of Conservation Units and Indigenous lands, valuing regenerative economies, expanding protected areas, and strengthening territorial and climate governance. The defense of the Cerrado is presented here not only as an ecological imperative but as an agenda for environmental justice, water security, and intergenerational responsibility. By integrating data, references, conceptual reflections, and action strategies, we hope to contribute to repositioning the Cerrado at the center of discussions on conservation, climate, and sustainable development.
Leaf herbivory is a ubiquitous ecological interaction that varies significantly in intensity across species, habitats, and biogeographic regions. Although quantification of leaf damage is crucial for understanding many ecological processes, the accuracy and precision of various damage estimation methods used by researchers, including visual estimation, digital image analysis, and artificial intelligence, have not been evaluated and compared. We use a phylogenetically diverse group of tropical plants to compare the accuracy and precision of damage estimation methods and use the results to provide a guide to herbivory estimation that balances the advantages and disadvantages of each method. We found that visual estimation tended to overestimate herbivory levels compared to digital methods but was 15 times faster and improved in accuracy and speed with training. Conversely, deep-learning algorithms underestimated herbivory relative to image analysis with ImageJ when it was on the margin, but showed similar accuracy for damage inside of leaf margins. Our results indicate that while visual methods allow for rapid assessment of large sample sizes and are suitable for detecting broad patterns of damage, image analysis is crucial for accurate and precise quantification. The disadvantages of each method, however, can be minimized through proper training and efficient use of each tool, and we therefore provide a guide of practical approaches to herbivory estimation.
