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Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel‐density hypervolumes), each with their own strengths and limits. Frameworks based on dissimilarity matrices either do not enable the measurement of all components of FD (i.e. richness, divergence, and regularity), or result in the distortion of the functional space. Frameworks based on multidimensional spaces do not allow for comparisons with phylogenetic diversity (PD) measures and can be sensitive to outliers. We propose the use of neighbor‐joining trees (NJ) to represent and quantify FD in a way that combines the strengths of current frameworks without many of their weaknesses. Importantly, our approach is uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles. We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel‐density hypervolumes using both simulated and empirical datasets. Using NJ, we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree‐based representations. Moreover, the method is directly comparable with taxonomic diversity (TD) and PD measures, and enables quantification of the richness, divergence and regularity of the functional space. [ABSTRACT FROM AUTHOR]

Aim: Quantifying the relative contribution of environmental filtering versus limiting similarity in shaping communities is challenging because these processes often act simultaneously and their effect is scale‐dependent. Focusing on caves, island‐like natural laboratories with limited environmental variability and species diversity, we tested: (i) the relative contribution of environmental filtering and limiting similarity in determining community assembly in caves; (ii) how the relative contribution of these driving forces changes along environmental gradients. Location: Europe. Time period: Present. Major taxa studied: Subterranean spiders. Methods: We used data on distribution and traits for European cave spiders (n = 475 communities). We estimated the trait space of each community using probabilistic hypervolumes, and obtained estimations of functional richness independent of the species richness of each community via null modelling. We model functional diversity change along environmental gradients using generalized dissimilarity modelling. Results: Sixty‐three percent of subterranean spider communities exhibited a prevalence of trait underdispersion. However, most communities displayed trait dispersion that did not depart significantly from random, suggesting that environmental filtering and limiting similarity were both exerting equally weak or strong, yet opposing influences. Overdispersed communities were primarily concentrated in southern latitudes, particularly in the Dinaric karst, where there is greater subterranean habitat availability. Pairwise comparisons of functional richness across caves revealed these effects to be strongly scale‐dependent, largely varying across gradients of cave development, elevation, precipitation, entrance size and annual temperature range. Conversely, geographical distance weakly affected trait composition, suggesting convergence in traits among communities that are far apart. Main conclusions: Even systems with stringent environmental conditions maintain the potential for trait differentiation, especially in areas of greater habitat availability. Yet, the relative influence of environmental filtering and limiting similarity change with scale, along clear environmental gradients. The interplay of these processes may explain the assembly of species‐poor subterranean communities displaying high functional specialization. [ABSTRACT FROM AUTHOR]

Background: Transfusion‐transmitted malaria (TTM) is a public health problem in endemic and nonendemic areas. The Brazilian Ministry of Health (MH) requested the development of a nucleic acid amplification test (NAT) for the detection of Plasmodium spp. in public blood centers to increase blood safety. Study Design and Methods: The new Brazilian NAT kit named NAT PLUS HIV/HBV/HCV/Malaria Bio‐Manguinhos was first implemented in HEMORIO, a public blood center in the city of Rio de Janeiro. Since October 1, 2022, this blood center has been testing all its blood donations for malaria in a pool of six plasma samples to detect Plasmodium spp. by real‐time polymerase chain reaction (PCR). Results: Since the implementation of the NAT PLUS platform until February 2023, HEMORIO has successfully received and tested 200,277 donations. The platform detected two asymptomatic donors in the city of Rio de Janeiro, which is a nonendemic region for malaria. Our analyses suggested a malaria from the Amazon region caused by Plasmodium vivax, in the first case, while an autochthonous transmission case by Plasmodium malariae was identified in the rural area of Rio de Janeiro state. Discussion: The NAT PLUS platform detects Plasmodium spp. in plasma samples with sensitivity capable of detecting subpatent infections. This is the first time worldwide that a group developed and implemented molecular diagnosis for Plasmodium spp. to be used by public blood centers to avoid TTM. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Stachytarpheta is mainly distributed in Brazil, where the knowledge of species richness is still in progress. Here, we describe S. meninii, a new micro‐endemic species from the Diamantina Plateau, Espinhaço Range. It is a shrub that can reach up to 1.8 meters in height, with abundant pedicellate glandular trichomes, viscous, aromatic leaves, inflorescences with oblong‐triangular bracts, and blue corollas, with a tube that is barely exserted from the calyx. The new species has been recorded from two gatherings from the same locality in the municipality of Serro, Minas Gerais state, and can be considered Critically Endangered (CR). Illustrations and a distribution map are provided for the recognition of S. meninii, along with an identification key for species of the genus found in Diamantina Plateau. [ABSTRACT FROM AUTHOR]

Comparative extinction risk analysis—which predicts species extinction risk from correlation with traits or geographical characteristics—has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion‐specific models and compared it with the typical criterion‐blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion‐specific models were better at identifying threatened species compared to a criterion‐blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria‐specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re‐evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long‐standing research‐implementation gap. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Time Period Major Taxa Studied Methods Results Main Conclusions We map global patterns of taxonomic and functional change between past (pre‐human impacts) and present (after anthropogenic extinctions and introductions) in large oceanic island bird assemblages and investigate if these patterns can be explained by island characteristics and anthropogenic factors.Sixty‐four oceanic islands (>100 km2).Late Holocene.Terrestrial and freshwater bird species.We compiled information on extinct, extant native and introduced bird species for all islands and used a probabilistic hypervolume approach to build a multi‐dimensional trait space and calculate several functional diversity metrics before and after extinctions and introductions. We identified which islands are global hotspots of human‐induced transformation by mapping multiple facets of biotic change and investigated intrinsic island characteristics and anthropogenic factors as drivers for these observed patterns.The Hawaiian and Mascarene islands stand out as hotspots of taxonomic and functional change, but all islands changed taxonomically and functionally, mostly gaining species but losing functional richness. Taxonomic and functional changes vary across islands but are often consistent within the same archipelago. Island isolation and surface can explain some of the observed variations, but anthropogenic factors, namely human occupation, also shaped both taxonomic and functional changes. Islands with higher human pressure, as well as larger islands with high elevation ranges, tended to have greater losses in functional richness.Most biodiversity change assessments are still largely based exclusively on taxonomic diversity, which is particularly worrying in the case of oceanic islands given that the magnitude of functional diversity change is often considerably larger. We call for comprehensive assessments of changes in both taxonomic and functional diversity across oceanic islands in order to better understand the drivers of these changes and, in turn, predict future trends. [ABSTRACT FROM AUTHOR]