Identifying Critical Vegetation Types for Biodiversity Conservation in the Americas / Identificación de tipos de vegetación críticos para la conservación de la biodiversidad en las Américas / Identificação de Tipos de Vegetação Críticos para a Conservação da Biodiversidade nas Américas

The Americas contain highly biodiverse yet vulnerable ecosystems, with many threatened species inadequately protected. Finer-scale, localized habitat assessments are crucial for effective conservation planning, but continental-scale high-resolution vegetation maps remain limited. This study addresses this gap by identifying critical vegetation types across the Americas using the standardized framework of the International Vegetation Classification (IVC) system at the macrogroup level, representing the finest vegetation classification available across the region, as well as the highest-resolution Area of Habitat (AOH) maps currently available. By combining these high-resolution IVC macrogroup maps with detailed AOH maps, we highlight at-risk vegetation types based on 1) threatened and macrogroup-associated species (species that have at least 50% of their AOH in one macrogroup), 2) current protection levels, and 3) projected threats from land use changes, and 4) develop a conservation value index (CVI) that accounts for all these factors. The results highlighted the remarkable diversity of high conservation value macrogroups across the Americas, emphasizing their significance in regions such as the Andes, montane Mesoamerica, the Caribbean, Brazil's Cerrado, and the Atlantic Forest. Among the highest-scoring macrogroups, the Northern Andean Montane & Upper Montane Humid Forest emerged as critically important, harboring a high number of threatened and macrogroup-associated species. Other macrogroups of immediate conservation concern include the Brazilian Atlantic Montane Humid Forest, Pacific Mesoamerican Seasonal Dry Forest, Caribbean Lowland Humid Forest, and Central Midwest Oak Forest, Woodland and Savanna. However, the study revealed that nearly three-quarters of the over 300 macrogroups in the Americas fall below the global target of 30% protection. Notably, a fifth of all species were macrogroup-associated species, including over 40% of threatened species. Our findings emphasize the need for targeted conservation strategies that consider finer-scale habitat classifications and paired with high-quality species distribution data to guide conservation strategies for biodiversity across the Americas.

Las Américas contienen ecosistemas altamente biodiversos pero vulnerables, con muchas especies amenazadas insuficientemente protegidas. Las evaluaciones de hábitat hechas a escala más detallada son cruciales para una planificación eficaz de la conservación, pero los mapas de vegetación de alta resolución a escala continental siguen siendo limitados. Este estudio aborda esta brecha, identificando tipos de vegetación críticos en las Américas utilizando el marco estandarizado del sistema de Clasificación Internacional de Vegetación (IVC) a nivel de macrogrupo, que representa la clasificación de vegetación más detallada disponible en toda la región, así como los mapas de Área de Hábitat (AOH) de mayor resolución disponibles en la actualidad Al combinar estos mapas de IVC de alta resolución con mapas de AOH, determinamos los tipos de vegetación en riesgo basados ​​en 1) especies amenazadas y asociadas a macrogrupos (especies que tienen al menos el 50% de su AOH en un macrogrupo), 2) niveles de protección de las especies, y 3) amenazas proyectadas por cambios en el uso del suelo , y 4) desarrollar un índice de valor de conservación (CVI) que tenga en cuenta los tres factores anteriores. Los resultados demuestran la notable diversidad de macrogrupos de alto valor de conservación en las Américas, enfatizando su importancia en regiones como los Andes, la Mesoamérica montañosa, el Caribe, el Cerrado de Brasil y el Bosque Atlántico. Entre los macrogrupos con mayor puntuación, el Bosque Húmedo Montano Norte Andino y Alto Montano emergieron como de importancia crítica, ya que albergan un gran número de especies amenazadas y asociadas a macrogrupos. Otros macrogrupos de interés para la conservación incluyen el Bosque Húmedo Montano Atlántico de Brasil, el Bosque Seco Estacional Mesoamericano del Pacífico, el Bosque Húmedo de Tierras Bajas del Caribe y el Bosque de Robles, Bosques y Sabanas del Medio Oeste Central. Sin embargo, el estudio reveló que casi tres cuartas partes de los más de 300 macrogrupos en las Américas se encuentran por debajo del objetivo global del 30% de protección. En particular, una quinta parte de todas las especies estaban asociadas a un único   macrogrupo, incluidas más del 40% de especies amenazadas. Nuestros hallazgos enfatizan la necesidad de estrategias de conservación específicas que consideren clasificaciones de hábitats a escala detallada y se combinen con datos de distribución de especies de alta resolución para guiar las estrategias de conservación de la biodiversidad en las Américas.

As Américas abrigam ecossistemas altamente biodiversos, porém vulneráveis, com muitas espécies ameaçadas insuficientemente protegidas. Avaliações de habitat em escalas mais detalhadas são cruciais para um planejamento eficaz de conservação, mas mapas de vegetação de alta resolução em escala continental ainda são limitados. Este estudo aborda essa lacuna, identificando tipos críticos de vegetação nas Américas usando o quadro padronizado do sistema de Classificação Internacional de Vegetação (IVC) no nível de macrogrupo, que representa a classificação de vegetação mais detalhada disponível em toda a região, bem como os mapas de Área de Hábitat (AOH) de maior resolução disponíveis atualmente. Ao combinar esses mapas de IVC de alta resolução com mapas de AOH, determinamos os tipos de vegetação em risco com base em 1) espécies ameaçadas e associadas a macrogrupos (espécies que têm pelo menos 50% de sua AOH em um macrogrupo), 2) níveis de proteção das espécies, e 3) ameaças projetadas por mudanças no uso do solo, e 4) desenvolvemos um índice de valor de conservação (CVI) que leva em consideração os três fatores anteriores. Os resultados demonstram a notável diversidade de macrogrupos de alto valor de conservação nas Américas, enfatizando sua importância em regiões como os Andes, a Mesoamérica montanhosa, o Caribe, o Cerrado do Brasil e a Mata Atlântica. Entre os macrogrupos com maior pontuação, o Bosque Úmido Montano Norte Andino e Alto Montano emergiram como de importância crítica, abrigando um grande número de espécies ameaçadas e associadas a macrogrupos. Outros macrogrupos de interesse para a conservação incluem o Bosque Úmido Montano Atlântico do Brasil, o Bosque Seco Estacional Mesoamericano do Pacífico, o Bosque Úmido de Terras Baixas do Caribe e o Bosque de Carvalhos, Florestas e Savanas do Centro-Oeste Central. No entanto, o estudo revelou que quase três quartos dos mais de 300 macrogrupos nas Américas estão abaixo da meta global de 30% de proteção. Em particular, um quinto de todas as espécies estava associado a um único macrogrupo, incluindo mais de 40% das espécies ameaçadas. Nossas descobertas enfatizam a necessidade de estratégias de conservação específicas que considerem classificações de habitats em escala detalhada e se combinem com dados de distribuição de espécies de alta resolução para orientar as estratégias de conservação da biodiversidade nas Américas.

Drivers of habitat availability for terrestrial mammals: Unravelling the role of livestock, land conversion and intrinsic traits in the past 50 years.

The global decline of terrestrial species is largely due to the degradation, loss and fragmentation of their habitats. The conversion of natural ecosystems for cropland, rangeland, forest products and human infrastructure are the primary causes of habitat deterioration. Due to the paucity of data on the past distribution of species and the scarcity of fine-scale habitat conversion maps, however, accurate assessment of the recent effects of habitat degradation, loss and fragmentation on the range of mammals has been near impossible. We aim to assess the proportions of available habitat within the lost and retained parts of mammals' distribution ranges, and to identify the drivers of habitat availability. We produced distribution maps for 475 terrestrial mammals for the range they occupied 50 years ago and compared them to current range maps. We then calculated the differences in the percentage of 'area of habitat' (habitat available to a species within its range) between the lost and retained range areas. Finally, we ran generalized linear mixed models to identify which variables were more influential in determining habitat availability in the lost and retained parts of the distribution ranges. We found that 59% of species had a lower proportion of available habitat in the lost range compared to the retained range, thus hypothesizing that habitat loss could have contributed to range declines. The most important factors negatively affecting habitat availability were the conversion of land to rangeland and high density of livestock. Significant intrinsic traits were those related to reproductive timing and output, habitat breadth and medium body size. Our findings emphasize the importance of implementing conservation strategies to mitigate the impacts caused by human activities on the habitats of mammals, and offer evidence indicating which species have the potential to reoccupy portions of their former range if other threats cease to occur.

Area of Habitat maps for the world's terrestrial birds and mammals.

Area of Habitat (AOH) is "the habitat available to a species, that is, habitat within its range". It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species' associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66 ± 28% of the range maps for mammals and 64 ± 27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modelling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals and globally threatened birds.

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates.

Area of habitat (AOH) is defined as the "habitat available to a species, that is, habitat within its range" and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.

Conversión de la Categoría de Hábitat a Cobertura de Terreno para Mapear el Área de Hábitat de los Vertebrados Terrestres Resumen El área del hábitat (AOH) está definida como "el hábitat disponible para una especie, es decir, el hábitat dentro del área de distribución de la especie" y se calcula mediante la sustracción de las áreas de terreno inadecuado y la elevación del área de distribución. El Esquema de Clasificación de Hábitats de la Unión Internacional para la Conservación de la Naturaleza proporciona información sobre las asociaciones entre los hábitats de las especies y con frecuencia se utilizan las opiniones no validadas de expertos para cotejar el hábitat con los tipos de cobertura de terreno, lo que genera una fuente de incertidumbre en los mapas de AOH. Desarrollamos un método orientado por datos para convertir las categorías de hábitat que maneja la UICN en cobertura de terreno basado en los datos de localidad puntual de 6,986 especies de mamíferos terrestres, aves, anfibios y reptiles. Extrajimos la categoría de cobertura de terreno en cada localidad puntual y la cotejamos con la categoría o categorías de hábitat de UICN asignada a cada especie incidente en la localidad. Después modelamos cada categoría de cobertura de terreno como función del hábitat según la UICN usando modelos de regresión logística. Las proporciones de probabilidad resultantes fueron usadas para evaluar la solidez de la asociación entre cada categoría de hábitat y de cobertura de terreno. Después comparamos el desempeño de nuestro modelo orientado por datos con el desempeño de una tabla de conversión publicada basada en el conocimiento de expertos. Calculamos la asociación entre las categorías de hábitat y las de cobertura de terreno como una variable continua, pero para mapear el AOH como una presencia o ausencia binaria, fue necesario aplicar un umbral de asociación. Este umbral puede ser elegido por el usuario de acuerdo con el balance requerido entre los errores de omisión y comisión. Algunos hábitats (p. ej.: bosques y desiertos) fueron asignados a las categorías de cobertura de terreno con más confianza que otros (p. ej.: humedales y artificiales). El modelo de conversión orientado por los datos y el conocimiento de los expertos tuvieron un desempeño igual de eficiente, pero el modelo proporcionó una mayor estandarización, objetividad y repetitividad. Además, nuestra estrategia permitió una mayor flexibilidad en el uso de los resultados y de la incertidumbre para ser cuantificados. Nuestro modelo puede modificarse para análisis regionales y para diferentes grupos taxonómicos.

Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data.

Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with the atmospheric RTM MODTRAN5. Because of MODTRAN's computational burden and GSA's demand for many simulations, we first developed a surrogate statistical learning model, i.e., an emulator, that allows approximating RTM outputs through a machine learning algorithm with low computation time. A Gaussian process regression (GPR) emulator was used to reproduce lookup tables of TOA radiance as a function of 12 input variables with relative errors of 2.4%. GSA total sensitivity results quantified the driving variables of emulated TOA radiance along the 400-2500 nm spectral range at 15 cm-1 (between 0.3-9 nm); overall, the vegetation variables play a more dominant role than atmospheric variables. This suggests the possibility to retrieve biophysical variables directly from at-sensor TOA radiance data. Particularly promising are leaf chlorophyll content, leaf water thickness and leaf area index, as these variables are the most important drivers in governing TOA radiance outside the water absorption regions. A software framework was developed to facilitate the development of retrieval models from at-sensor TOA radiance data. As a proof of concept, maps of these biophysical variables have been generated for both TOA (L1C) and bottom-of-atmosphere (L2A) Sentinel-2 data by means of a hybrid retrieval scheme, i.e., training GPR retrieval algorithms using the RTM simulations. Obtained maps from L1C vs L2A data are consistent, suggesting that vegetation properties can be directly retrieved from TOA radiance data given a cloud-free sky, thus without the need of an atmospheric correction.

Solid-phase synthesis of lipidated peptides.

A new flexible and efficient methodology for the solid-phase synthesis of lipidated peptides has been developed. The approach is based on the use of previously synthesized building blocks and overcomes the limitations of previously reported methods, since long doubly lipidated peptides can be synthesized by using this route. Furthermore, it was thus possible to prepare a large number of N- and H-Ras peptides bearing a wide range of reporter and/or linking groups--efficient tools for the investigation of biological processes. In terms of efficiency and flexibility this solid-phase method is superior to the solution-phase synthesis. It gives pure peptides in multimilligram amounts within a much shorter time and with superior overall yield.

An acylation cycle regulates localization and activity of palmitoylated Ras isoforms.

We show that the specific subcellular distribution of H- and Nras guanosine triphosphate-binding proteins is generated by a constitutive de/reacylation cycle that operates on palmitoylated proteins, driving their rapid exchange between the plasma membrane (PM) and the Golgi apparatus. Depalmitoylation redistributes farnesylated Ras in all membranes, followed by repalmitoylation and trapping of Ras at the Golgi, from where it is redirected to the PM via the secretory pathway. This continuous cycle prevents Ras from nonspecific residence on endomembranes, thereby maintaining the specific intracellular compartmentalization. The de/reacylation cycle also initiates Ras activation at the Golgi by transport of PM-localized Ras guanosine triphosphate. Different de/repalmitoylation kinetics account for isoform-specific activation responses to growth factors.

sigma-Borane and dihydroborate complexes of ruthenium.

Room temperature reaction of the bis(dihydrogen) complex RuH(2)(H(2))(2)(PCy(3))(2) (1) with excess pinacol borane (HBpin) generates the novel complex RuH[(mu-H)(2)Bpin](sigma-HBpin)(PCy(3))(2) (2) by loss of dihydrogen. Complex 2 was characterized spectroscopically and by X-ray crystallography. It contains two pinacolborane moieties coordinated in a different fashion, one as a dihydroborate (B-H distances : 1.58(3) and 1.47(3) A) and the other as a sigma-borane (B-H distance: 1.35(3) A). In addition, reaction of 1 with one equiv of HBpin yields total conversion to a new complex tentatively formulated as RuH[(mu-H)(2)Bpin](H(2))(PCy(3))(2) (3) on the basis of NMR data. In the presence of excess HBpin, 3 is converted to 2. Furthermore, under an atmosphere of dihydrogen, a C(7)D(8) solution of 2 rapidly converts to 3 and finally regenerates 1 over a much longer period. Thus, complex 3 is an intermediate in the formation of 2 from 1. In these processes the borane is eliminated as HBpin later hydrolyzed to BpinOBpin. Selective hydroboration of ethylene (3 bar) into C(2)H(5)Bpin is achieved using 1 or 2 as catalyst precursors in toluene, whereas in THF, competitive formation of the vinylborane C(2)H(3)Bpin (56% under 20 bar of C(2)H(4)) can be favored.