Biodiversity Patterns Research Articles

Improving Online Citizen Science Platforms for Biodiversity Monitoring

ABSTRACTBackgroundMonitoring biodiversity is crucial in biogeography. Citizen science and biodiversity platforms have revolutionized data access across taxa, but they struggle to provide robust raw data essential for conservation decisions.AimsThis study addresses data gaps for under‐represented species and locations, observer expertise variability, and the lack of absence data and sampling effort information to improve data representation and suitability for statistical analyses.Materials & MethodsWe collected, compared to IUCN‐recognized taxonomic groups, all worldwide living being (animal, plant and fungi) observations held by four major biodiversity platforms: eBird, GBIF, iNaturalist, and Observation.org. We also organized such observations by country of origin and based on their Human Development Index (HDI).ResultsWe found that, while GBIF, iNaturalist, and Observation.org cover all life forms, birds are the most observed (eBird is a bird‐specific platform), whereas fish, other marine organisms, arthropods, and invertebrates are dramatically underrepresented. Moreover, none of the above‐mentioned biodiversity platforms considered or directly analysed expertise variability among observers and, apart from eBird, the other three biodiversity platforms do not accommodate data on species absence and sampling effort.Discussion and ConclusionFinally, we found that species observations on biodiversity platforms considered in this study are skewed towards high HDI countries, primarily North America and Europe. By enhancing the effectiveness of biodiversity platforms, this study has the potential to significantly advance the field of biogeography, paving the way for more informed and effective conservation strategies. Overall, our findings underscore the untapped potential of these platforms in contributing to our understanding of the spatial and temporal patterns of biodiversity.

Declining planetary health as a driver of camera-trap studies: Insights from the web of science database

Planetary health is crucial to human well-being, ecosystem sustainability, and biodiversity preservation. In this context, camera traps are an effective remote sensing tool for monitoring biodiversity. Given the rising importance of understanding biodiversity patterns and trends, this study examines possible factors influencing camera-trap studies and provides bibliometric insights from 2377 publications indexed in the Web of Science (WoS). To explore the potential drivers of camera-trap research growth, we used a logistic model based on specific variables, including global gross domestic product, temperature growth, a planetary health measure the declining living planet index, and human population growth. The living planet index was identified as a statistically significant driver of camera-trap research growth (p-value <0.01), suggesting that curiosity regarding other living beings influences studies. Through the bibliometric analysis, we observed that camera-trap studies are predominantly conducted in the United States, followed by England and Australia, with a notable upward trend over recent years. These studies align with sustainable development goal 15 (Life on Land) and are primarily classified under the ecology category in WoS. Further, we have visualized the network of co-occurrence of authors and authors' affilation regions, keywords, and keywords plus documents. Overall, this study assesses ecological and conservation informatics and provides a reference to scholars, policymakers, and decision-makers.

Beyond species richness: Forest structure and edaphic conditions have similar importance but different effects on multi-taxon biodiversity

Managed forests represent a major fraction of the global forest area and are known to host impoverished biodiversity compared to natural forests. The effect of forest management has focused mainly on aggregated community metrics such as species richness of single taxa and on simplistic managed vs. unmanaged comparisons. However, the effect of forest management is expected to vary among species and taxa and to be contingent on site-specific conditions. In this study, we focus on fine-scale multi-taxon biodiversity patterns to disentangle the impact of forest management on the forest structure and the abiotic soil conditions of the stands. We base our comparisons on carefully selected pairs of managed and unmanaged stands to minimize regional differences that could confound the effects of management. We found that the total effect of forest management on alpha diversity was positive on plants and rove beetles, neutral on ground beetles and mosses, and negative on crane flies, fungi, and lichens. However, using joint species distribution modeling we show that individual species’ responses to the local underlying soil conditions can be as important as the forest structural changes induced by management, but this varied among the different taxa. Based on these responses we disclose synergies and trade-offs among some of the taxa. Our results indicate that the balance between forest management and abiotic conditions can shape the patterns of forest multi-taxon biodiversity. Considering these conditions can be important in predicting the response of biodiversity to forest management and act as key criteria when prioritizing areas for the conservation of biodiversity.

Ecosystem Service and Biodiversity Patterns Observed across Co-Developed Land Use Scenarios in the Piedmont: Lessons Learned for Scale and Framing

Ecosystem Service and Biodiversity Patterns Observed across Co-Developed Land Use Scenarios in the Piedmont: Lessons Learned for Scale and Framing

Long-distance Southern Ocean environmental DNA (eDNA) transect provides insights into spatial marine biota and invasion pathways for non-native species

The Southern Ocean surrounding Antarctica harbours some of the most pristine marine environments remaining, but is increasingly vulnerable to anthropogenic pressures, climate change, and invasion by non-native species. Monitoring biotic responses to cumulative impacts requires temporal and spatial baselines and ongoing monitoring - traditionally, this has been obtained by continuous plankton recorder (CPR) surveys. Here, we conduct one of the longest environmental DNA (eDNA) transects yet, spanning over 3000 nautical miles from Hobart (Australia) to Davis Station (Antarctica). We evaluate eDNA sampling strategies for long-term open ocean biomonitoring by comparing two water volume and filter pore size combinations: large (12 l with 20 μm) and small (2 l with 0.45 μm). Employing a broad COI metabarcoding assay, we found the large sample/pore combination was better suited to open ocean monitoring, detecting more target DNA and rare or low abundance species. Comparisons with four simultaneously conducted CPR transects revealed that eDNA detections were more diverse than CPR, with 7 (4 unique) and 4 (1 unique) phyla detections respectively. While both methods effectively delineated biodiversity patterns across the Southern Ocean, eDNA enables surveys in the presence of sea-ice where CPR cannot be conducted. Accordingly, 16 species of concern were detected along the transect using eDNA, notably in the Antarctic region (south of 60°S). These were largely attributed to hull biofouling, a recognized pathway for marine introductions into Antarctica. Given the vulnerability of Antarctic environments to potential introductions in a warming Southern Ocean, this work underscores the importance of continued biosecurity vigilance. We advocate integrating eDNA metabarcoding with long-term CPR surveys in the Southern Ocean, emphasising the urgency of its implementation. We anticipate temporal and spatial interweaving of CPR, eDNA, and biophysical data will generate a more nuanced picture of Southern Ocean ecosystems, with significant implications for the conservation and preservation of Antarctic ecosystems.

Integrative approach to monitoring metazoan diversity and distribution in two Mediterranean coastal sites through morphology and organismal eDNA

Marine and coastal ecosystems respond to climate change in various ways, such as the type of ecosystem, the species composition, interactions, and distribution, and the effect of local stressors. Metazoan organisms, particularly zooplankton, are important indicators for monitoring the effects climate-driven warming in marine coastal ecosystems over the long term. In this study, the diversity and distribution of zooplankton communities in the Mediterranean Sea (Canyon Dohrn and LTER-MareChiara, Gulf of Naples), a known biodiversity and climate changes hotspot, have been assessed using the integration of morphological-based identification and organismal eDNA. Our findings showed that the multi-locus strategy including the mitochondrial cytochrome c oxidase I (COI) gene and the hypervariable region V9 of the 18S rDNA (18S V9) as targets, improved the taxonomic overview, with the COI gene being more effective than the 18S V9 region for metazoans at the species level. However, appendicularians were detected only with the 18S V9 region. Overall, organismal eDNA is a powerful approach for revealing hidden biodiversity, especially for gelatinous and meroplankton components, and provided new insights into biodiversity patterns. The ecological importance of calanoid copepods in coastal ecosystems has been confirmed. In contrast, the discovery of 13 new metazoan records in the Mediterranean Sea, including two non-indigenous copepod species, suggested that local stressors affect zooplankton community structure and resilience, highlighting the importance of biomonitoring and protecting marine coastal ecosystems.

Coupled space-time scale analysis for obtaining enhanced accuracy in species dynamics

Scale effects significantly affect the rationality and accuracy of ecological models, so temporal and spatial scales are included in the construction and application of ecological studies. However, few ecological pattern analyses focus on both of these scales simultaneously, which is especially important in terms of synchrony. In this study, based on fishery catch data and simulated data, we propose a framework for coupled space-time scale analysis and reveal possible deficiencies in conventional scale studies. We verified the feasibility and reliability of the scheme using simulated data with different combinations of temporal and spatial scales. The results showed that our scheme can simultaneously identify and localize scale features in the variation in species spatial-temporal patterns, specifically regarding the synchrony and amplitude of temporal dynamics (or spatial patterns) of multiple sites (or times). Our scheme revealed that spatial scales had an important effect on the intrinsic 13-year scale features, which significantly improved our understanding of global Rajiformes fishery dynamics. This showed that the spatial-temporal patterns and scale features obtained based on the coupled space-time scale analysis were complete and more accurate. At the same time, our scheme correctly identified complex pattern structures, such as data stratification and multiple combinations of time and space scales, which can reduce possible errors in practical applications. This scheme can be applied to the identification and prediction of the spatial-temporal patterns in biodiversity in the future and will help in formulating effective policies promoting sustainable fishery resources management and comprehensive conservation of endangered marine species.

Linking watershed formation with the phylogenetic distribution of a soil microscopic fungus in Yunnan Province, China

BackgroundPhylogeographic studies have gained prominence in linking past geological events to the distribution patterns of biodiversity, primarily in mountainous regions. However, such studies often focus on plant taxa, neglecting the intricate biogeographical patterns of microbes, particularly soil microbial communities. This article explores the spatial distribution of the nematode-trapping fungus Arthrobotrys oligospora, a widespread microorganism, in a tectonically active region at the southeastern edge of the Qinghai-Tibetan Plateau. By analysing the genetic variation of this fungus alongside the historical structure of major river watersheds, we sought to uncover potential connections between the two. Our study involved sampling 149 strains from 116 sites across six major watersheds in the region.ResultsThe resulting haplotype network revealed five distinct clusters, each corresponding closely to a specific watershed. These clusters exhibited high haplotype diversity and low nucleotide diversity, supporting the notion of watershed-based segregation. Further analysis of haplotypes shared across watersheds provided evidence for three proposed past river connections. In particular, we found numerous shared haplotypes between the Yangtze and Mekong basins, as well as between the Yangtze and the Red basins. Evidence for a Irrawaddy-Salween-Red and a Yangtze-Pearl-Red river connections were also portrayed in our mapping exercise.ConclusionsThese findings emphasize the crucial role of historical geomorphological events in shaping the biogeography of microbial biodiversity, alongside contemporary biotic and abiotic factors. Watershed perimeters emerged as effective predictors of such patterns, suggesting their suitability as analytical units for regional-scale studies. Our study also demonstrates the potential of microorganisms and phylogeographic approaches to complement traditional geological analyses, providing a more comprehensive understanding of past landscape structure and its evolution.

Effects of the main media of wind and water on the biodiversity pattern of grassland and its driving mechanism in Poyang Lake

AbstractAs important media for species diffusion, water and wind are two important factors for grassland biodiversity conservation in lake areas. Exploring their driving mechanism on grassland biodiversity is crucial for maintaining the lake ecosystem's equilibrium. Our study utilizes the data of wind velocity and water level, which are significant performance factors for wind and water respectively in Poyang Lake from 2000 to 2020 to reveal their interannual time‐series fluctuation characteristics and their influence mechanism on the grassland biodiversity pattern. Landscape pattern indices and biodiversity indicators, such as the number of patches (NP), patch density (PD), landscape spreading index (CI), landscape fragmentation index (LSD), landscape aggregation index (AI), Simpson diversity index (MSIDI) and Simpson evenness index (MSIEI) were analysed, trend analysis, redundancy analysis and structural equation modelling were applied in this study. The main results were: (1) From 2000 to 2020, Poyang Lake's wind velocity decreased gradually, and the water level first decreased and then rose. NP in Poyang Lake fluctuated substantially, LSD fluctuated frequently and obvious temporal heterogeneity existed. (2) CI and AI increased from low to high value, facilitating species dispersal and migration. The dominant species with high aggregation gradually established stronger connectivity. Moderate spreading degree and aggregation degree maintained high biodiversity and evenness, whereas excessive spreading degree and aggregation degree led to homogenization of species, decrease in biodiversity, reduction in species evenness, and increase in dominance. (3) As the landscape transformed from having no obvious dominant species to being dominated by several dominant species, MSIEI and landscape dominance changed from high to low and low to high respectively. Moreover, the biodiversity shifted from high to low, and species distribution in the landscape shifted from balanced to unbalanced. (4) The effect of water level on PD, AI, LSD, MSIDI and MSIET was significantly higher than that of wind velocity. LSD was mainly regulated by the minimum wind velocity affecting the maximum and average water levels. MSIDI and MSIET were primarily governed by the minimum wind velocity affecting the minimum water level. The minimum water level decreased as the minimum wind velocity increased, and MSIDI and MSIET weakened as the minimum water level decreased.

Grime’s ecological strategies reveal contrasting patterns in alkaline and loess grasslands

Studying the relationship between biodiversity patterns and processes in vegetation has been at the centre of interest in vegetation ecology for several decades. By studying the biomass of loess and alkaline grasslands along a water and salinity gradient, we aimed to analyse species diversity and Grime’s competitor-stress tolerator-ruderal (CSR) functional strategy patterns. We aimed to test the following hypotheses: i) The biomass and species richness scores and the species composition are significantly different between the sampled grassland community types. ii) The sampled communities are well separated based on the CSR strategy spectrum. iii) The amount of green biomass and litter are positively correlated with competitiveness and negatively with stress tolerance. The biomass and species richness scores and the species composition of the sampled communities along the sampled gradients were significantly different; the highest species richness, evenness and Shannon diversity values were found in loess grasslands. The highest level of litter accumulation was found in alkaline meadows. The communities were well separated in the ordinations but surprisingly, calculation of coordinates for CSR strategy types have not shown clear separation of the grassland community types. All the communities were proven to be characterised by a high level of stress (located in the right corner of the CSR ternary diagram), but they markedly differed in the magnitude of competition and levels of disturbance expressed in the differences of ruderality. These results might suggest that even in highly stressed communities the community composition is strongly dependent on the differences in disturbance intensity (e.g., intensity and duration of grazing) and it is also strongly influenced by the competitive ability of constituting species.

Untangling island biogeography of terrestrial vertebrates in protected areas of America

Island Biogeography Theory (IBT) is a foundational framework in conservation science, yet its application to large-scale protected area (PA) design remains relatively understudied. This research investigates the influence of IBT-derived variables on terrestrial vertebrate richness and threatened species abundance within 4990 PAs across continental America. By examining the effects of area, shape, isolation, elevation, latitude, and human influence, we assessed the relative importance of these factors in shaping vertebrate diversity patterns. Our findings reveal that while IBT principles, such as the positive relationship between area and species richness, are evident, the influence of human activities is pervasive. Specifically, latitude and elevation significantly influenced species richness for most taxonomic groups, while area positively affected amphibians, birds, reptiles, and threatened mammals and reptiles. Shape and isolation exhibited varying degrees of impact across different taxa. Critically, human influence emerged as a dominant factor, particularly for birds, including threatened species. These results underscore the complex interplay between natural and anthropogenic processes in shaping biodiversity patterns. To effectively conserve terrestrial vertebrates, and overall biodiversity, PA managers and policy-makers must integrate IBT principles with strategies that address the impacts of human activities, such as habitat loss, fragmentation, and climate change.

Soundscapes and airborne laser scanning identify vegetation density and its interaction with elevation as main driver of bird diversity and community composition

AbstractAimMountain ecosystems are hotspots of biodiversity due to their high variation in climate and habitats. Yet, above average rates of climate change and enhanced forest disturbance regimes alter local climatic conditions and vegetation structure, which should impact biodiversity. We here investigated the impact of vegetation and elevation as well as their interactions on bird communities to improve our ability to predict climate change effects on bird communities.LocationEuropean Alps, Germany.MethodsWe studied patterns and drivers of bird communities at 213 plots along gradients in vegetation density and elevation using autonomous sound recorders. Bird species were identified from soundscapes by Convolutional Neural Networks (BirdNET) and taxonomists.ResultsBird diversity and community metrics were moderately to strongly correlated for data based on either identification by BirdNET or taxonomists (Pearson's r = .47–.94), and ecological findings were overall similar for both datasets. Vegetation density 1–2 m and &gt;2 m above ground strongly affected bird diversity and community composition and mediated effects of elevation. Community composition changed with elevation more strongly in habitats with low than high vegetation density &gt;2 m. Species numbers decreased with elevation in habitats with low vegetation density 1–2 m and &gt;2 m above ground, but increased in habitats with high vegetation density. Overall, functional and phylogenetic diversity increased with elevation indicating lower habitat filtering, but patterns were also mediated by vegetation density.Main ConclusionsOur results indicate that bird communities in the German Alps are determined by strong interactive effects of elevation and vegetation, underlining the importance to consider variation in vegetation in studies of biodiversity patterns along elevational gradients and under climate change. Combining remote sensing data and biodiversity monitoring based on autonomous sampling and AI‐based species identification opens new avenues for bird monitoring and research in remote areas.

Noteworthy records of Myotis Kaup, 1829 species in northeastern Guatemala, including the first record of M. volans (H. Allen, 1866) (Chiroptera, Vespertilionidae) from the country

Myotis is the most diverse genus of bats in Central America, with 10 species currently reported for Guatemala. Here, we present the &amp;#64257;rst record of M. volans (H. Allen, 1866), and third record of M. auriculus Baker &amp; Stains, 1955 in Guatemala, both from the cloud forest of the highlands of Sierra de las Minas Biosphere Reserve. This new locality may serve as one of the southernmost habitats akin to North American ecosystems for these two species. Our record of M. volans increases the number of bats in Guatemala to 105. Our &amp;#64257;ndings underscore the importance of further research to understand patterns of biodiversity in Guatemala and Central America.

Identification of metacommunities in bioregions with historical habitat networks.

Although metacommunity theory provides many useful insights for conservation planning, the transfer of this knowledge to practice is hampered due to the difficulty of identifying metacommunities in bioregions. This study aims to identify the spatial extent of metacommunities at bioregional scales using current and historical habitat data, especially because contemporary biodiversity patterns may be a result of time-lagged responses to historical habitat configurations. Further, this estimation of the metacommunity spatial extent is based on both the habitat structure and the dispersal ability of the species. Focusing on dragonfly and damselfly (odonate) species in the eastern Swiss Plateau, the research uses wetland habitat information spanning over 110 years to create a time series of nine habitat networks between 1899 and 2010. From these networks, we identified the spatial extents of metacommunities based on the year of habitat information as well as on watershed boundaries. To identify the best metacommunity spatial extents, the study investigates whether patch pairs within a metacommunity exhibit greater similarity in species composition (i.e. lower beta-diversity) than patch pairs between metacommunities. For the different metacommunities, we further investigated correlations between gamma diversity and metacommunity size and compare them to theoretical expectations. In both analyses we found that augmenting spatial metacommunity identification with historical geographical proximity results in stronger associations with biodiversity patterns (beta and gamma diversity) than when using only current-day habitat or watershed information.

Unfolding the dynamics of ecosystems undergoing alternating wet-dry transitional states.

A significant fraction of Earth's ecosystems undergoes periodic wet-dry alternating transitional states. These globally distributed water-driven transitional ecosystems, such as intermittent rivers and coastal shorelines, have traditionally been studied as two distinct entities, whereas they constitute a single, interconnected meta-ecosystem. This has resulted in a poor conceptual and empirical understanding of water-driven transitional ecosystems. Here, we develop a conceptual framework that places the temporal availability of water as the core driver of biodiversity and functional patterns of transitional ecosystems at the global scale. Biological covers (e.g., aquatic biofilms and biocrusts) serve as an excellent model system thriving in both aquatic and terrestrial states, where their succession underscores the intricate interplay between these two states. The duration, frequency, and rate of change of wet-dry cycles impose distinct plausible scenarios where different types of biological covers can occur depending on their desiccation/hydration resistance traits. This implies that the distinct eco-evolutionary potential of biological covers, represented by their trait profiles, would support different functions while maintaining similar multifunctionality levels. By embracing multiple alternating transitional states as interconnected entities, our approach can help to better understand and manage global change impacts on biodiversity and multifunctionality in water-driven transitional ecosystems, while providing new avenues for interdisciplinary studies.

Fossil pollen data can reconstruct robust spatial patterns of biodiversity in the past

Fossil pollen data are valuable for understanding past spatio-temporal variations in plant diversity. However, deducing robust patterns of fossil pollen-assemblage properties is challenging due to factors related to pollen production, dispersal, and fossilisation; sediment sampling; and nomenclature and taxonomy of the fossil pollen grains reflecting the vegetation that produced them. If the composition pattern of the most recent fossil pollen assemblage concords with those in modern or surface pollen assemblages from the same location(s), the pattern can be regarded as robust.Using recent (50–500 years) fossil pollen and surface pollen assemblages of angiosperms compiled from the same geographic area of Central Asia, we analyse spatial patterns in compositional turnover and phylogenetic dispersion. These are widely used to quantify different aspects of plant diversity.Despite differences in the data regarding spatial coverage, number of pollen records, and number of pollen taxa, the spatial pattern in the modern and fossil pollen-assemblage properties across climate zones is broadly similar. Especially, the latitudinal patterns of pollen-assemblage properties are strikingly similar between both data types. However, the degree of concordance varies according to the diversity metric being analysed, and the magnitudes of the metric may differ between both data types. When the data are compiled, processed, and standardised following consistent criteria and analysed using appropriate metrics and methods, spatial patterns in pollen-assemblage properties of fossil pollen data are as robust as those in surface pollen data (∼modern vegetation). Therefore, regional patterns of compositional turnover and phylogenetic dispersion can be confidently inferred from older fossil assemblages through the Holocene.

Context specific effects of substrate composition on the taxonomic and functional diversity of macroinvertebrate communities in temperate lowland streams.

Substrate composition has been widely recognised as a primary variable shaping lotic macroinvertebrate communities at the habitat unit level. However, fundamental understanding of how communities inhabiting mineralogical habitats (i.e., gravel, sand and silt) are structured across differing rivers is lacking. Moreover, research largely focusses on gravel beds and fine sediment in general (<2 mm) and as a result detailed field observations specifically of the sand and silt fractions are lacking. Using data from five UK streams collated from published studies, we assess taxonomic and functional biodiversity (alpha and beta diversity) at the habitat unit level (as defined by substrate composition of sand, silt and gravel). We found that the composition of taxonomic communities were clearly different in all habitat units for each individual stream (and at the landscape scale), with comparable, but less strong, distinctions between substrates for functional macroinvertebrate community composition. However, alpha diversity metrics and Local Contribution to Beta Diversity (LCBD) recorded among the different habitat units varied significantly across individual rivers, and the amount of variation explained by the habitat unit for taxonomic and functional composition demonstrated considerable differences suggesting strong context dependence. The depositional fine sediment habitats of sand and silt were found to support a discrete community composition and differing levels of alpha and beta diversity within and between rivers. We advocate that care should be taken when seeking to generalise biodiversity patterns at a landscape scale as our study highlights the high degree of context dependency when considering the role of the habitat template. Moreover, our results provide evidence that discriminating between the size fractions of fine sediment habitats (sand or silt) is important to fully elucidate the wider ecological importance of these habitats and the distinct taxonomic and functional biodiversity they support.

Distribution pattern and driving factors of mite communities in karst cave ecosystems.

Mites are among the most abundant invertebrates in subsurface ecosystems, and their community assemblages and distributions are often significantly influenced by the diversity of habitat resources. The cave ecosystem encompasses drastic changes in nonbiological factors, such as changes in lighting conditions from bright to extraordinarily dark and habitat gradients of surface plant resources from abundant to scarce or even disappearing, providing an ideal unique environment for evaluating the assembly mechanism of soil animal communities. Nevertheless, there still needs to be a sufficient understanding of the biodiversity patterns and drivers of mite communities across environmental gradients in karst caves. We conducted a comprehensive survey on the composition and diversity of soil mites in three photometric zones (dark, twilight, and light) of a typical karst cave and its adjoining extractive environments (forest scrub and farmland). Our research aimed to investigate the ecological relationships of mite communities between above- and below-ground habitats and the effects of abiotic factors on mite communities. We collected 49 families, 86 genera, and 1284 mites. In the external cave environment, we captured 1052 mites from 72 genera and 45 families; in the internal cave environment, we captured 232 mites from 46 genera and 29 families. The abundance, richness of genera, and diversity parameters of the mite community decreased from the cave entrance to the cave interior with decreasing light intensity. Oribatid mites dominated the mite community. Protoribates and Scheloribates were the dominant genera, along with Tectocepheus and 11 other genera, which primarily distinguished the mite communities among different habitats. Forty endemic taxa were found in the external cave environment, compared to 14 endemic taxa in the internal cave environment. The mite community showed a strong preference for the cave ecosystem habitat. Temperature, humidity, and soil nitrogen content significantly influenced the distribution pattern of mite communities (VIP > 0.8, p < 0.05).

Environmental DNA metabarcoding for whole community inventories of vertebrates in rivers of the midwestern United States

The application of environmental DNA (eDNA) methods to simultaneously study vertebrate diversity holds promise to accelerate conservation efforts, especially in freshwater systems which are among the most imperiled in the world. Here, using eDNA sampling, we identify patterns of vertebrate biodiversity across different habitats of the Kankakee River watershed, one of the most diverse lotic systems in Illinois, USA. Our eDNA metabarcoding analyses identified 147 different taxa, including 77 fishes, 38 birds, 24 mammals, five amphibians and three reptiles at 11 locations in the watershed, including tributaries and mainstem stretches upstream and within the Kankakee River State Park protected area. When compared to seining, eDNA sampling consistently detected more fish species, including non-native and imperiled species. We also found that vertebrate communities among the different habitats significantly varied in taxonomic composition, showing an upstream-downstream shift along the mainstem river as well as tributary-specific assemblages. Our study demonstrates the ability of single-marker eDNA metabarcoding to simultaneously document aquatic and terrestrial communities across large temperate lotic ecosystems and to monitor diversity patterns across protected areas.

Optimal inventorying and monitoring of taxonomic, phylogenetic and functional diversity.

Comparable data is essential to understand biodiversity patterns. While assemblage or community inventorying requires comprehensive sampling, monitoring focuses on as few components as possible to detect changes. Quantifying species, their evolutionary history, and the way they interact requires studying changes in taxonomic (TD), phylogenetic (PD) and functional diversity (FD). Here we propose a method for the optimization of sampling protocols for inventorying and monitoring assemblages or communities across these three diversity dimensions taking sampling costs into account. We used Iberian spiders and Amazonian bats as two case-studies. The optimal combination of methods for inventorying and monitoring required optimizing the accumulation curve of α-diversity and minimizing the difference between sampled and estimated β-diversity (bias), respectively. For Iberian spiders, the optimal combination for TD, PD and FD allowed sampling at least 50% of estimated diversity with 24 person-hours of fieldwork. The optimal combination of six person-hours allowed reaching a bias below 8% for all dimensions. For Amazonian bats, surveying all the 12 sites with mist-nets and 0 or 1 acoustic recorders was the optimal combination for almost all diversity types, resulting in >89% of the diversity and <10% bias with roughly a third of the cost. Only for phylogenetic α-diversity, the best solution was less clear and involved surveying both with mist nets and acoustic recorders. The widespread use of optimized and standardized sampling protocols and regular repetition in time will radically improve global inventory and monitoring of biodiversity. We strongly advocate for the global adoption of sampling protocols for both inventory and monitoring of taxonomic, phylogenetic and functional diversity.