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Aim: Biodiversity monitoring at global scales has been identified as one of the priorities to halt biodiversity loss. In this context, Latin America and the Caribbean (LAC), home to 60% of the global biodiversity, play an important role in the development of an integrative biodiversity monitoring platform. In this review, we explore to what extent LAC has advanced in the adoption of remote sensing for biodiversity monitoring and what are the gaps and opportunities to integrate local monitoring into global efforts to halt biodiversity loss. Location: Latin America and the Caribbean. Time period: 1995 to 2022. Taxa studied: Terrestrial organisms. Methods: We reviewed the application of remote sensing for biodiversity monitoring in LAC aiming to identify gaps and opportunities across countries, ecosystem types and research networks. Results: Our analysis illustrates how the use of remote sensing in LAC is disproportionately low in relation to the biodiversity it supports. Main conclusions: Build upon this analysis, we present, discuss and offer perspectives regarding four gaps identified in the application of remote sensing for biodiversity monitoring in Latin America and the Caribbean, namely (1) alignment between remote sensing data resolution and ecosystem structure; (2) investment in research, institutions and capacity building within researchers and stakeholders; (3) decolonized practices that promote access to publishing outlets and pluralistic participation among countries that facilitate exchange of experiences and capacity building; and (4) development of networks within and across regions to advance in ground surveys, ensure access and to foster the use of remote sensing data. [ABSTRACT FROM AUTHOR]

Questions: Forest fragmentation affects biodiversity locally (α diversity) and beyond — at relatively larger scales (γ diversity) — by increasing dispersal and recruitment limitations. Yet, does an increase in fragmentation affect the relationship between α and γ diversity and what can we learn from it? Location: Northern France. Methods: We surveyed 116 forest patches across three fragmentation levels: none (continuous forest); intermediate (forest patches connected by hedgerows); and high (isolated forest patches). Plant species richness of both forest specialists and generalists was surveyed at five nested spatial resolutions across each forest patch: 1 m2; 10 m2; 100 m2; 1,000 m2; and total forest patch area. First, we ran log‐ratio models to quantify the α–γ relationship. We did that separately for all possible combinations of fragmentation level (none vs intermediate vs high) × spatial scale (e.g., α‐1 m2 vs γ‐10 m2) × species type (e.g., α‐specialists vs γ‐specialists). We then used linear mixed‐effects models to analyze the effect of fragmentation level, spatial scale, species type and all two‐way interaction terms on the slope coefficient extracted from all log‐ratio models. Results: We found an interaction effect between fragmentation level and species type, such that forest specialists shifted from a linear (i.e., proportional sampling) to a curvilinear plateau (i.e., community saturation) relationship at low and high fragmentation, respectively, while generalists shifted from a curvilinear to a linear pattern. Conclusions: The impact of forest fragmentation on the α–γ relationship supports generalist species persistence over forest specialists, with contrasting mechanisms for these two guilds. As fragmentation increases, forest specialists shift from proportional sampling towards community saturation, thus reducing α diversity likely due to dispersal limitation. Contrariwise, generalists shift from community saturation towards proportional sampling, thus increasing α diversity likely due to an increase in the edge:core ratio. To ensure long‐term conservation of forest specialists, one single large forest patch should be preferred over several small ones. [ABSTRACT FROM AUTHOR]

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases. [ABSTRACT FROM AUTHOR]

Ljungan virus (LV), which belongs to the Parechovirus genus in the Picornaviridae family, was first isolated from bank voles ( Myodes glareolus ) in Sweden in 1998 and proposed as a zoonotic agent. To improve knowledge of the host association and geographical distribution of LV, tissues from 1685 animals belonging to multiple rodent and insectivore species from 12 European countries were screened for LV-RNA using reverse transcriptase (RT)-PCR. In addition, we investigated how the prevalence of LV-RNA in bank voles is associated with various intrinsic and extrinsic factors. We show that LV is widespread geographically, having been detected in at least one host species in nine European countries. Twelve out of 21 species screened were LV-RNA PCR positive, including, for the first time, the red vole ( Myodes rutilus ) and the root or tundra vole ( Alexandromys formerly Microtus oeconomus ), as well as in insectivores, including the bicolored white-toothed shrew ( Crocidura leucodon ) and the Valais shrew ( Sorex antinorii ). Results indicated that bank voles are the main rodent host for this virus (overall RT-PCR prevalence: 15.2%). Linear modeling of intrinsic and extrinsic factors that could impact LV prevalence showed a concave-down relationship between body mass and LV occurrence, so that subadults had the highest LV positivity, but LV in older animals was less prevalent. Also, LV prevalence was higher in autumn and lower in spring, and the amount of precipitation recorded during the 6 months preceding the trapping date was negatively correlated with the presence of the virus. Phylogenetic analysis on the 185 base pair species-specific sequence of the 5' untranslated region identified high genetic diversity (46.5%) between 80 haplotypes, although no geographical or host-specific patterns of diversity were detected.