Gustavo Andrés Zurita

The expansion and intensification of agriculture are widely recognized as major drivers of biodiversity loss. While research has primarily focused on deforestation frontiers, few studies have linked spatial-temporal land-cover dynamics to the organizational arrangements of agro-industrial supply chains. This study addresses this gap by analyzing land-use systems in the Upper Parana Atlantic Forest in Argentina, a priority biodiversity hotspot. We identify trends and patterns of agricultural and forest land-use change over the past two decades. We interpret these patterns in relation to the territorial integration of agro-industrial supply chains, using secondary data sources. We divided the study area into hexagonal cells of approximately 100 km². Interannual trends in native forest cover and dominant land uses were analyzed from 2000 to 2019. Trends were estimated by regressing the proportional area of land-cover classes derived from the MapBiomas Trinational Atlantic Forest against calendar year. To explore landscape homogenization, we regressed Shannon land-cover diversity indices over time. Our results reveal two contrasting spatial configurations. Some landscapes are dominated by a single land use, showing increasing homogenization. Others maintain a diversity of land uses and remain heterogeneous. These configurations seem closely associated with transaction modalities between primary producers and agro-industrial actors. In turn, these arrangements influence their impacts on native forest cover and habitat conservation outside protected areas. Understanding how agro-industrial supply chains are territorially embedded is critical for identifying incentives to foster more sustainable land-use trajectories and support biodiversity conservation, like the design of effective governance systems for Other Effective Area-Based Conservation Measures (OECMs).

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost‐effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision‐makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time‐consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species‐level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species‐based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

BirdNET is a popular machine learning tool for automated recognition of bird sounds. However, evidence on how to optimize its settings for accurate bird monitoring remains limited. Here, we evaluate how BirdNET settings influence model performance in identifying bird vocalizations and characterizing bird communities, using 4224 1‐min recordings from 67 recording locations worldwide. Giving equal importance to recall and precision, a low confidence score threshold (0.1–0.3) appears optimal for detecting bird vocalizations, whereas higher thresholds (around 0.5) are more suitable for characterizing bird communities. Based on our findings, we recommend increasing the Overlap parameter from its default value of 0 to 2 s, as this consistently improves BirdNET performance in detecting both bird vocalizations and species presence. The effect of the Sensitivity parameter varied across regions. However, a value of 0.5 maximizes global performance for community‐level analyses across all confidence thresholds, and a value of 1.5 generally yields better results for vocalization‐level studies, particularly at low confidence thresholds. Our findings offer practical guidance for selecting BirdNET settings in passive acoustic bird surveys, enhancing both the identification of bird vocalizations and the characterization of bird communities.

Passive acoustic monitoring (PAM) using autonomous recording units (ARUs) has become a key tool in long-term, low-cost ecological studies. However, one of the main challenges lies in storing and analyzing the large volume of data it generates, which requires significant processing effort and species annotation. In this context, it is crucial to establish a sampling and acoustic data analysis protocol that maximizes the efficiency of ecological information retrieval. This study proposes the application of the species–area relationship (SAR) mathematical model to optimize the use of ARUs and reduce the effort required for acoustic data analysis, aiming to predict the number of detected species in 3 Neotropical ecoregions: Amazonia, Caatinga, and Campos y Malezales. Our results suggest that increasing the number of ARUs (12 in this study) while reducing the post-recording listening effort (12 min per ARU) enhances sampling efficiency, allowing for a more accurate representation of biodiversity in the study sites. The SAR model was first applied to estimate both alpha and beta diversity in relation to sampling effort. In addition, beta diversity increased by 20% between ARUs spaced 500–1,000 m apart in Campos y Malezales; whereas in Amazonia and Caatinga, where distances between recorders were shorter (200–250 m), the increase was much smaller (0.8–5%). This highlights the importance of spatial configuration among recorders when interpreting species turnover patterns. Our findings support the design of sampling strategies adapted to different ecological contexts and levels of sampling effort. These insights provide a solid foundation for improving the management and optimization of biodiversity monitoring protocols in Neotropical environments. Similarly, they may be applied in other ecoregions using PAM, contributing to the development of more efficient methodologies for large-scale assessment of biological communities.

Ectotherms with lower maintenance costs and broader environmental tolerances are generally more resilient in human‐altered landscapes and under current climate change, enhancing their chances of survival and colonization. In this study, we explored how habitat use and foraging strategy are associated with the resting metabolic rate ( RMR ) of spiders from habitats with significant temperature variability due to anthropogenic disturbance: native forests and young pine plantations, both in the Southern Atlantic Forest. Using open‐flow respirometry at 25°C, we measured CO ₂ production in immobile spiders to calculate their RMR . Key findings include: (1) all spiders showed 22%–57% lower RMR than predicted by standard metabolic equations; (2) continuous gas exchange patterns, typical of mesic‐adapted species, were observed in all cases; (3) the metabolic rate scaling exponent was 0.65; (4) there were no significant RMR differences between habitats, but a negative correlation between RMR and microhabitat thermal amplitude was noted; and (5) active foragers had higher RMRs than passive foragers. These findings enhance our understanding of spider biology, physiology, and ecology, particularly in their responses to anthropogenic stressors.

Cattle ranching is an economic activity responsible for the loss of large extensions of tropical dry forest around the world. Several studies have demonstrated that the use of inadequate practices of this activity in tropical forests (e.g., fire, agrochemicals, and lack of rotational grazing systems of cattle in pastures) have negative consequences on dung beetle diversity and their ecological functions. In the present study, the influence of the cattle ranching duration gradient on the diversity of dung beetles and seed removal was evaluated. This study was carried out in pastures with different times of establishment of cattle ranching (between 4 and 40 years) in a tropical dry forest of Mexico. Overall, the species richness of dung beetles was similar along the gradient of grazing ages. However, the diversity of common (q1) and dominant (q2) species decreased and was associated with an increasing abundance of exotic species and a decreasing abundance of native species. Seed removal was mainly carried out by four beetle species, among which the exotic species Digitonthophagus gazella was the most important. The results establish that the duration of cattle ranching primarily influences the composition of dung beetle communities, as reflected in changes in the structure and function of their assemblages in the pastures. Although native dung beetles persist at low abundances along this gradient, the consequences of land use changes are undeniable in other similar ecosystems where these species could definitively disappear.

Functional diversity has been defined as the value, range, distribution, and relative abundance of the functional traits of individuals that belong to an ecosystem. Thus, the functional response of organisms to environmental disturbances depends largely on their functional traits. Here, we evaluated dung beetle functional diversity associated to the Atlantic Forest replacement using a matrix with 25 functional traits (10 morphological, four ethological, and 11 physiological). We compared functional diversity among native and disturbed habitats with a multi and single trait approach. Contrary to previous studies, habitats with higher disturbance (open pasture) exhibited higher functional diversity compared to native forests, which could be explained by the incorporation of physiological response traits. Species of open disturbed habitats showed extreme values of such traits, explaining the observed pattern. The inclusion of several traits that represent both species ecology and morphology, and their physiology, generates different results to those observed in previous functional studies. This highlights the importance of including a large variety of functional traits in future functional diversity studies. We propose that functional traits must (1) be carefully chosen according to their biological and functional basis; (2) represent species ecology and physiology; and (3) include both effect and response traits. In addition, we consider it is extremely relevant to include a multi and single trait approach in functional diversity studies. A combination of all these considerations will provide a more realistic and complete overview of functional diversity patterns and the potential consequences of human disturbance on ecosystem functioning.