Divergent driving mechanisms of community temporal stability in China's drylands.

Climate change and anthropogenic activities are reshaping dryland ecosystems globally at an unprecedented pace, jeopardizing their stability. The stability of these ecosystems is crucial for maintaining ecological balance and supporting local communities. Yet, the mechanisms governing their stability are poorly understood, largely due to the scarcity of comprehensive field data. Here we show the patterns of community temporal stability and its determinants across an aridity spectrum by integrating a transect survey across China's drylands with remote sensing. Our results revealed a U-shaped relationship between community temporal stability and aridity, with a pivotal shift occurring around an aridity level of 0.88. In less arid areas (aridity level below 0.88), enhanced precipitation and biodiversity were associated with increased community productivity and stability. Conversely, in more arid zones (aridity level above 0.88), elevated soil organic carbon and biodiversity were linked to greater fluctuations in community productivity and reduced stability. Our study identifies a critical aridity threshold that precipitates significant changes in community stability in China's drylands, underscoring the importance of distinct mechanisms driving ecosystem stability in varying aridity contexts. These insights are pivotal for developing informed ecosystem management and policy strategies tailored to the unique challenges of dryland conservation.

Multiple scale assessment of habitat, landscape, and geographic-specific attributes driving decapod assemblages in Posidonia oceanica seagrass meadows.

Seagrass meadows are biodiversity hotspots for invertebrate species including decapods. Understanding the drivers of species abundance, richness and diversity of decapod assemblages is crucial for the conservation of such hotspots, but how drivers act across multiple spatial scales remains unexplored. Here we describe the decapod assemblages of Posidonia oceanica seagrass meadows and assess the influence of attributes from three increasing spatial scales (habitat, landscape, and geographical levels) on the assemblages' structure and composition, as well as the variability partitioning among each one of these levels. Overall, geographical level attributes (i.e., inlet aperture, confinement) affected the most the decapod assemblages, while we only found a modest contribution from habitat (e.g., detritus biomass, sediment organic matter) and landscape attributes (e.g., fragmentation). We suggest that decapod assemblages are driven by the interaction of multiple processes occurring at different scales and other highly stochastic phenomena such as larval dispersion and recruitment.

Effect of aerobic exercise and particulate matter exposure duration on the diversity of gut microbiota.

Inhalation of ambient particulate matter (PM) can disrupt the gut microbiome, while exercise independently influences the gut microbiome by promoting beneficial bacteria. In this study, we analyzed changes in gut microbial diversity and composition in response to combined interventions of PM exposure and aerobic exercise, extending up to 12 weeks. This investigation was conducted using mice, categorized into five groups: control group (Con), exercise group (EXE), exercise group followed by 3-day exposure to PM (EXE + 3-day PM), particulate matter exposure (PM), and PM exposure with concurrent treadmill exercise (PME). Notably, the PM group exhibited markedly lower alpha diversity and richness compared to the Con group and our analysis of beta diversity revealed significant variations among the intervention groups. Members of the Lachnospiraceae family showed significant enhancement in the exercise intervention groups (EXE and PME) compared to the Con and PM groups. The biomarker Lactobacillus, Coriobacteraceae, and Anaerofustis were enriched in the EXE group, while Desulfovibrionaceae, Mucispirillum schaedleri, Lactococcus and Anaeroplasma were highly enriched in the PM group. Differential abundance analysis revealed that Paraprevotella, Bacteroides, and Blautia were less abundant in the 12-week PM exposure group than in the 3-day PM exposure group. Moreover, both the 3-day and 12-week PM exposure groups exhibited a reduced relative abundance of Bacteroides uniformis, SMB53, and Staphylococcus compared to non-PM exposure groups. These findings will help delineate the possible roles and associations of altered microbiota resulting from the studied interventions, paving the way for future mechanistic research.

Shifting mammal communities and declining species richness along an elevational gradient on Mount Kenya.

Conservation areas encompassing elevation gradients are biodiversity hotspots because they contain a wide range of habitat types in a relatively small space. Studies of biodiversity patterns along elevation gradients, mostly on small mammal or bird species, have documented a peak in diversity at mid elevations. Here, we report on a field study of medium and large mammals to examine the impact of elevation, habitat type, and gross primary productivity on community structure. Species richness was observed using a camera trap transect with 219 sites situated across different habitat types from 2329 to 4657 m above the sea level on the western slope of Mt Kenya, the second highest mountain in Africa. We found that the lowest elevation natural habitats had the highest species richness and relative abundance and that both metrics decreased steadily as elevation increased, paralleling changes in gross primary productivity, and supporting the energy richness hypothesis. We found no evidence for the mid-domain effect on species diversity. The lowest elevation degraded Agro-Forestry lands adjacent to the National Park had high activity of domestic animals and reduced diversity and abundance of native species. The biggest difference in community structure was between protected and unprotected areas, followed by more subtle stepwise differences between habitats at different elevations. Large carnivore species remained relatively consistent but dominant herbivore species shifted along the elevation gradient. There was some habitat specialization and turnover in species, such that the elevation gradient predicts a high diversity of species, demonstrating the high conservation return for protecting mountain ecosystems for biodiversity conservation.

The relationship between remotely-sensed spectral heterogeneity and bird diversity is modulated by landscape type.

To identify areas of high biodiversity and prioritize conservation efforts, it is crucial to understand the drivers of species richness patterns and their scale dependence. While classified land cover products are commonly used to explain bird species richness, recent studies suggest that unclassified remote-sensed images can provide equally good or better results. In our study, we aimed to investigate whether unclassified multispectral data from Landsat 8 can replace image classification for bird diversity modeling. Moreover, we also tested the Spectral Variability Hypothesis. Using the Atlas of Breeding Birds in the Czech Republic 2014-2017, we modeled species richness at two spatial resolutions of approx. 131 km2 (large squares) and 8 km2 (small squares). As predictors of the richness, we assessed 1) classified land cover data (Corine Land Cover 2018 database), 2) spectral heterogeneity (computed in three ways) and landscape composition derived from unclassified remote-sensed reflectance and vegetation indices. Furthermore, we integrated information about the landscape types (expressed by the most prevalent land cover class) into models based on unclassified remote-sensed data to investigate whether the landscape type plays a role in explaining bird species richness. We found that unclassified remote-sensed data, particularly spectral heterogeneity metrics, were better predictors of bird species richness than classified land cover data. The best results were achieved by models that included interactions between the unclassified data and landscape types, indicating that relationships between bird diversity and spectral heterogeneity vary across landscape types. Our findings demonstrate that spectral heterogeneity derived from unclassified multispectral data is effective for assessing bird diversity across the Czech Republic. When explaining bird species richness, it is important to account for the type of landscape and carefully consider the significance of the chosen spatial scale.

Urban greening with shrubs can supercharge invertebrate abundance and diversity.

In urban areas, diverse and complex habitats for biodiversity are often lacking. This lack of diversity not only compromises essential ecological processes, such as pollination and nutrient cycling, but also diminishes the resilience of urban ecosystems to pests and diseases. To enhance urban biodiversity, a possible solution is to integrate shrubs alongside trees, thereby increasing the overall amount of vegetation, structural complexity and the associated resource diversity. Here, using a common garden experiment involving a variety of trees and shrubs planted alone and in combination, we evaluate how canopy-associated invertebrate assemblages are influenced by vegetation type. In particular, we test whether the presence of shrubs, alone or with trees, results in increased abundance and taxonomic richness of invertebrates, compared to trees on their own. We found that the overall abundance of invertebrates, and that of specific functional groups (e.g., herbivores, pollinators, detritivores), was higher on shrubs, compared to trees, and when trees and shrubs were planted in combination (relative to trees on their own). Our results suggest that planting shrub and tree species with wide and dense crowns can increase the associated abundance and taxonomic and functional group richness of invertebrate communities. Overall, our findings indicate that urban planning would benefit from incorporating shrubs alongside urban trees to maximise invertebrate abundance, diversity and function in urban landscapes.

Mycorrhizal type and tree diversity affect foliar elemental pools and stoichiometry.

Species-specific differences in nutrient acquisition strategies allow for complementary use of resources among plants in mixtures, which may be further shaped by mycorrhizal associations. However, empirical evidence of this potential role of mycorrhizae is scarce, particularly for tree communities. We investigated the impact of tree species richness and mycorrhizal types, arbuscular mycorrhizal fungi (AM) and ectomycorrhizal fungi (EM), on above- and belowground carbon (C), nitrogen (N), and phosphorus (P) dynamics. Soil and soil microbial biomass elemental dynamics showed weak responses to tree species richness and none to mycorrhizal type. However, foliar elemental concentrations, stoichiometry, and pools were significantly affected by both treatments. Tree species richness increased foliar C and P pools but not N pools. Additive partitioning analyses showed that net biodiversity effects of foliar C, N, P pools in EM tree communities were driven by selection effects, but in mixtures of both mycorrhizal types by complementarity effects. Furthermore, increased tree species richness reduced soil nitrate availability, over 2 yr. Our results indicate that positive effects of tree diversity on aboveground nutrient storage are mediated by complementary mycorrhizal strategies and highlight the importance of using mixtures composed of tree species with different types of mycorrhizae to achieve more multifunctional afforestation.

Diversity, richness, and evenness of birds in Rana Resort Forest, District Kasur, Punjab, Pakistan.

This research was carried out to determine avian diversity in the Rana Resort Forest from June to August 2023. A total of 655 birds were observed; these birds belonged to 36 different species from 11 orders; 27 families and 36 genera were found in the forest. The observed avian species that belong to the Muscicapidae family had the highest number of species, while Strigidae had the lowest number of species. The highest numbers of the order Passeriformes were recorded. Among the bird species observed, 33 were residents, 1 was a winter visitor, and 2 were summer breeders. The species diversity, richness, and evenness indices are 3.5238, 5.3973, and 0.10492, respectively. According to the index results, the Rana Resort Forest is a diverse area, but the species are not evenly distributed due to some of the threats observed during the study, such as habitat destruction, poverty, and unawareness.

Precipitation variation: a key factor regulating plant diversity in semi-arid livestock grazing lands.

Livestock presence impacts plant biodiversity (species richness) in grassland ecosystems, yet extent and direction of grazing impacts on biodiversity vary greatly across inter-annual periods. In this study, an 8-year (2014-2021) grazing gradient experiment with sheep was conducted in a semi-arid grassland to investigate the impact of grazing under different precipitation variability on biodiversity. The results suggest no direct impact of grazing on species richness in semi-arid Stipa grassland. However, increased grazing indirectly enhanced species richness by elevating community dominance (increasing the sheltering effect of Stipa grass). Importantly, intensified grazing also regulates excessive community biomass resulting from increased inter-annual wetness (SPEI), amplifying the positive influence of annual humidity index on species richness. Lastly, we emphasize that, in water-constrained grassland ecosystems, intra-annual precipitation variability (PCI) was the most crucial factor driving species richness. Therefore, the water-heat synchrony during the growing season may alleviate physiological constraints on plants, significantly enhancing species richness as a result of multifactorial interactions. Our study provides strong evidence for how to regulate grazing intensity to increase biodiversity under future variable climate patterns. We suggest adapting grazing intensity according to local climate variability to achieve grassland biodiversity conservation.

Camera trap surveys of Atlantic Forest mammals: A data set for analyses considering imperfect detection (2004-2020).

Camera traps became the main observational method of a myriad of species over large areas. Data sets from camera traps can be used to describe the patterns and monitor the occupancy, abundance, and richness of wildlife, essential information for conservation in times of rapid climate and land-cover changes. Habitat loss and poaching are responsible for historical population losses of mammals in the Atlantic Forest biodiversity hotspot, especially for medium to large-sized species. Here we present a data set from camera trap surveys of medium to large-sized native mammals (>1 kg) across the Atlantic Forest. We compiled data from 5380 ground-level camera trap deployments in 3046 locations, from 2004 to 2020, resulting in 43,068 records of 58 species. These data add to existing data sets of mammals in the Atlantic Forest by including dates of camera operation needed for analyses dealing with imperfect detection. We also included, when available, information on important predictors of detection, namely the camera brand and model, use of bait, and obstruction of camera viewshed that can be measured from example pictures at each camera location. Besides its application in studies on the patterns and mechanisms behind occupancy, relative abundance, richness, and detection, the data set presented here can be used to study species' daily activity patterns, activity levels, and spatiotemporal interactions between species. Moreover, data can be used combined with other data sources in the multiple and expanding uses of integrated population modeling. An R script is available to view summaries of the data set. We expect that this data set will be used to advance the knowledge of mammal assemblages and to inform evidence-based solutions for the conservation of the Atlantic Forest. The data are not copyright restricted; please cite this paper when using the data.

As armadilhas fotográficas tornaram­se o principal método de observação de muitas espécies em grandes áreas. Os dados obtidos com armadilhas fotográficas podem ser usados para descrever os padrões e monitorar a ocupação, abundância e riqueza da vida selvagem, informação essencial para a conservação em tempos de rápidas mudanças climáticas e de cobertura do solo. A perda de habitat e a caça furtiva são responsáveis pelas perdas populacionais históricas de mamíferos no hotspot de biodiversidade da Mata Atlântica, especialmente para espécies de médio e grande porte. Aqui apresentamos um conjunto de dados de levantamentos com armadilhas fotográficas de mamíferos de médio e grande porte (>1 kg) em toda a Mata Atlântica. Compilamos dados de 5.380 armadilhas fotográficas instaladas no nível do chão em 3.046 locais, de 2004 a 2020, resultando em 43.068 registros de 58 espécies. Esses dados acrescentam aos conjuntos de dados existentes de mamíferos na Mata Atlântica por incluir as datas de operação das câmeras, que são necessárias para análises que lidam com detecção imperfeita. Também incluímos, quando disponíveis, informações sobre importantes preditores de detecção, como marca e modelo da câmera, uso de isca e obstrução do visor da câmera que pode ser medido a partir de imagens de exemplo em cada local da câmera. Além de estudos sobre os padrões e mecanismos por trás da ocupação, abundância relativa, riqueza e detecção, o conjunto de dados aqui apresentado pode ser usado para estudar os padrões de atividade diária das espécies, nível de atividade e interações espaço­temporais entre as espécies. Além disso, os dados podem ser usados em combinação com outras fontes de dados em diversas análises com modelagem populacional integrada. Um script R está disponível para visualizar um resumo do conjunto de dados. Esperamos que este conjunto de dados seja usado para aumentar o conhecimento sobre as assembleias de mamíferos e usado para informar soluções baseadas em evidências para a conservação da Mata Atlântica. Os dados não são restritos por direitos autorais e, por favor, cite este documento ao usar os dados.

Adaptive monitoring in action-what drives arthropod diversity and composition in central European beech forests?

Recent studies suggest that arthropod diversity in German forests is declining. Currently, different national programs are being developed to monitor arthropod trends and to unravel the effects of forest management on biodiversity in forests. To establish effective long-term monitoring programs, a set of drivers of arthropod diversity and composition as well as suitable species groups have to be identified. To aid in answering these questions, we investigated arthropod data collected in four Hessian forest reserves (FR) in the 1990s. To fully utilize this data set, we combined it with results from a retrospective structural sampling design applied at the original trap locations in central European beech (Fagus sylvatica) forests. As expected, the importance of the different forest structural, vegetation, and site attributes differed largely between the investigated arthropod groups: beetles, spiders, Aculeata, and true bugs. Measures related to light availability and temperature such as canopy cover or potential radiation were important to all groups affecting either richness, composition, or both. Spiders and true bugs were affected by the broadest range of explanatory variables, which makes them a good choice for monitoring general trends. For targeted monitoring focused on forestry-related effects on biodiversity, rove and ground beetles seem more suitable. Both groups were driven by a narrower, more management-related set of variables. Most importantly, our study approach shows that it is possible to utilize older biodiversity survey data. Although, in our case, there are strong restrictions due to the long time between species and structural attribute sampling.

Research on the prediction of English topic richness in the context of multimedia data.

With the evolution of the Internet and multimedia technologies, delving deep into multimedia data for predicting topic richness holds significant practical implications in public opinion monitoring and data discourse power competition. This study introduces an algorithm for predicting English topic richness based on the Transformer model, applied specifically to the Twitter platform. Initially, relevant data is organized and extracted following an analysis of Twitter's characteristics. Subsequently, a feature fusion approach is employed to mine, extract, and construct features from Twitter blogs and users, encompassing blog features, topic features, and user features, which are amalgamated into multimodal features. Lastly, the combined features undergo training and learning using the Transformer model. Through experimentation on the Twitter topic richness dataset, our algorithm achieves an accuracy of 82.3%, affirming the efficacy and superior performance of the proposed approach.

The Neural Basis of a Cognitive Function That Suppresses the Generation of Mental Imagery: Evidence from a Functional Magnetic Resonance Imaging Study.

This study elucidated the brain regions associated with the perception-driven suppression of mental imagery generation by comparing brain activation in a picture observation condition with that in a positive imagery generation condition. The assumption was that mental imagery generation would be suppressed in the former condition but not in the latter. The results show significant activation of the left posterior cingulate gyrus (PCgG) in the former condition compared to in the latter condition. This finding is generally consistent with a previous study showing that the left PCgG suppresses mental imagery generation. Furthermore, correlational analyses showed a significant correlation between the activation of the left PCgG and participants' subjective richness ratings, which are a measure of the clarity of a presented picture. Increased activity in the PCgG makes it more difficult to generate mental imagery. As visual perceptual processing and visual imagery generation are in competition, the suppression of mental imagery generation leads to enhanced visual perceptual processing. In other words, the greater the suppression of mental imagery, the clearer the presented pictures are perceived. The significant correlation found is consistent with this idea. The current results and previous studies suggest that the left PCgG plays a role in suppressing the generation of mental imagery.

Citizen science initiatives document biodiversity baselines at an urban lake.

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies.

Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as "defaunation." This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.

Higher trophic levels and species with poorer dispersal traits are more susceptible to habitat loss on island fragments.

Ongoing habitat loss and fragmentation caused by human activities represent one of the greatest causes of biodiversity loss. However, the effects of habitat loss and fragmentation are not felt equally among species. Here, we examined how habitat loss influenced the diversity and abundance of species from different trophic levels, with different traits, by taking advantage of an inadvertent experiment that created habitat islands from a once continuous forest via the creation of the Thousand Island Lake, a large reservoir in China. On 28 of these islands with more than a 9000-fold difference in their area (0.12-1154 ha), we sampled plants, herbivorous insects, and predatory insects using effort-controlled sampling and analyses. This allowed us to discern whether any observed differences in species diversity were due to passive sampling alone or to demographic effects that disproportionately influenced some species relative to others. We found that while most metrics of sampling effort-controlled diversity increased with island area, the strength of the effect was exacerbated for species in higher trophic levels. When we more explicitly examined differences in species composition among islands, we found that the pairwise difference in species composition among islands was dominated by species turnover but that nestedness increased with differences in island area, indicating that some species are more likely to be absent from smaller islands. Furthermore, by examining trends of several dispersal-related traits of species, we found that species with lower dispersal propensity tended to be those that were lost from smaller islands, which was observed for herbivorous and predatory insects. Our results emphasize the importance of incorporating within-patch demographic effects, as well as the taxa and traits of species when understanding the influence of habitat loss on biodiversity.

UPF1 regulates mRNA stability by sensing poorly translated coding sequences.

Post-transcriptional mRNA regulation shapes gene expression, yet how cis-elements and mRNA translation interface to regulate mRNA stability is poorly understood. We find that the strength of translation initiation, upstream open reading frame (uORF) content, codon optimality, AU-rich elements, microRNA binding sites, and open reading frame (ORF) length function combinatorially to regulate mRNA stability. Machine-learning analysis identifies ORF length as the most important conserved feature regulating mRNA decay. We find that Upf1 binds poorly translated and untranslated ORFs, which are associated with a higher decay rate, including mRNAs with uORFs and those with exposed ORFs after stop codons. Our study emphasizes Upf1's converging role in surveilling mRNAs with exposed ORFs that are poorly translated, such as mRNAs with long ORFs, ORF-like 3' UTRs, and mRNAs containing uORFs. We propose that Upf1 regulation of poorly/untranslated ORFs provides a unifying mechanism of surveillance in regulating mRNA stability and homeostasis in an exon-junction complex (EJC)-independent nonsense-mediated decay (NMD) pathway that we term ORF-mediated decay (OMD).

Microclimate modulation: An overlooked mechanism influencing the impact of plant diversity on ecosystem functioning.

Changes in climate and biodiversity are widely recognized as primary global change drivers of ecosystem structure and functioning, also affecting ecosystem services provided to human populations. Increasing plant diversity not only enhances ecosystem functioning and stability but also mitigates climate change effects and buffers extreme weather conditions, yet the underlying mechanisms remain largely unclear. Recent studies have shown that plant diversity can mitigate climate change (e.g. reduce temperature fluctuations or drought through microclimatic effects) in different compartments of the focal ecosystem, which as such may contribute to the effect of plant diversity on ecosystem properties and functioning. However, these potential plant diversity-induced microclimate effects are not sufficiently understood. Here, we explored the consequences of climate modulation through microclimate modification by plant diversity for ecosystem functioning as a potential mechanism contributing to the widely documented biodiversity-ecosystem functioning (BEF) relationships, using a combination of theoretical and simulation approaches. We focused on a diverse set of response variables at various levels of integration ranging from ecosystem-level carbon exchange to soil enzyme activity, including population dynamics and the activity of specific organisms. Here, we demonstrated that a vegetation layer composed of many plant species has the potential to influence ecosystem functioning and stability through the modification of microclimatic conditions, thus mitigating the negative impacts of climate extremes on ecosystem functioning. Integrating microclimatic processes (e.g. temperature, humidity and light modulation) as a mechanism contributing to the BEF relationships is a promising avenue to improve our understanding of the effects of climate change on ecosystem functioning and to better predict future ecosystem structure, functioning and services. In addition, microclimate management and monitoring should be seen as a potential tool by practitioners to adapt ecosystems to climate change.

Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic.

The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models, and maps the geographic patterns of community-level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing toward conservation efforts for Arctic plant diversity in the Western Siberian Arctic. Western Siberian Arctic, Russia. We investigated the relative importance of environmental and anthropogenic predictors of community-level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non-vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. We found that the mean community-level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South-West to North-East, which can be well explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate predictors, potentially indicating a lasting impact of ancient climate on tundra plant species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. We suggest that while community-level plant species richness is mostly driven by environmental factors, an improved spatial sampling will be needed to robustly and more precisely assess the impact of human activities on community-level species richness patterns. Our approach and results can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions.

Testing for concordance between predicted species richness, past prioritization, and marine protected area designations in the western Indian Ocean.

Scientific advances in environmental data coverage and machine learning algorithms have improved the ability to make large-scale predictions where data are missing. These advances allowed us to develop a spatially resolved proxy for predicting numbers of tropical nearshore marine taxa. A diverse marine environmental spatial database was used to model numbers of taxa from ∼1000 field sites, and the predictions were applied to all 7039 6.25-km2 reef cells in 9 ecoregions and 11 nations of the western Indian Ocean. Our proxy for total numbers of taxa was based on the positive correlation (r2 = 0.24) of numbers of taxa of hard corals and 5 highly diverse reef fish families. Environmental relationships indicated that the number of fish species was largely influenced by biomass, nearness to people, governance, connectivity, and productivity and that coral taxa were influenced mostly by physicochemical environmental variability. At spatial delineations of province, ecoregion, nation, and strength of spatial clustering, we compared areas of conservation priority based on our total species proxy with those identified in 3 previous priority-setting reports and with the protected area database. Our method identified 119 locations that fit 3 numbers of taxa (hard coral, fish, and their combination) and 4 spatial delineations (nation, ecoregion, province, and reef clustering) criteria. Previous publications on priority setting identified 91 priority locations of which 6 were identified by all reports. We identified 12 locations that fit our 12 criteria and corresponded with 3 previously identified locations, 65 that aligned with at least 1 past report, and 28 that were new locations. Only 34% of the 208 marine protected areas in this province overlapped with identified locations with high numbers of predicted taxa. Differences occurred because past priorities were frequently based on unquantified perceptions of remoteness and preselected priority taxa. Our environment-species proxy and modeling approach can be considered among other important criteria for making conservation decisions.

Evaluación de la concordancia entre la riqueza de especies pronosticada, priorizaciones pasadas y la designación de áreas marinas protegidas en el oeste del Océano Índico Resumen Los avances científicos en la cobertura de datos ambientales y los algoritmos de aprendizaje automatizado han mejorado la capacidad de predecir a gran escala cuando hacen falta datos. Estos avances nos permiten desarrollar un representante con resolución espacial para predecir la cantidad de taxones marinos en las costas tropicales. Usamos una base de datos espaciales de diversos ambientes marinos para modelar la cantidad de taxones a partir de ∼1000 sitios de campo y aplicamos las predicciones a las 7039 celdas arrecifales de 6.25­km2 en nueve ecorregiones y once países del oeste del Océano Índico. Nuestro representante para la cantidad total de taxones se basó en la correlación positiva (r2=0.24) de la cantidad de taxones de corales duros y cinco familias de peces arrecifales con diversidad alta. Las relaciones ambientales indicaron que el número de especies de peces estuvo influenciado principalmente por la biomasa, la cercanía a las personas, la gestión, la conectividad y la productividad y que los taxones de coral estuvieron influenciados principalmente por la variabilidad ambiental fisicoquímica. Comparamos la prioridad de las áreas de conservación a nivel de las delimitaciones espaciales de provincia, ecorregión, nación y fuerza del agrupamiento espacial basado en nuestro total de especies representantes con aquellas especies identificadas en tres reportes previos de establecimiento de prioridades y con la base de datos de áreas protegidas. Con nuestro método identificamos 119 localidades aptas para tres cantidades de taxones (corales duros, peces y su combinación) y cuatro criterios de delimitación espacial (nación, ecorregión, provincia y grupo de arrecifes). Las publicaciones previas sobre el establecimiento de prioridades identificaron 91 localidades prioritarias de las cuales seis fueron identificadas por todos los reportes. Identificamos doce localidades que se ajustan a nuestros doce criterios y se correspondieron con tres localidades identificadas previamente, 65 que se alinearon con al menos un reporte anterior y 28 que eran nuevas localidades. Sólo 34% de las 208 áreas marinas protegidas en esta provincia se traslaparon con localidades identificadas con un gran número de taxones pronosticados. Hubo diferencias porque en el pasado se priorizaba frecuentemente con base en las percepciones no cuantificadas de lo remoto y prioritario de los taxones preseleccionados. Nuestra especie representante del ambiente y nuestra estrategia de modelo pueden considerarse entre otros criterios importantes para tomar decisiones de conservación.