Ecospace:a unified framework for understanding variation in terrestrial biodiversity

AbstractUnderstanding patterns in biodiversity is a core ambition in ecological research. Existing ecological theories focusing on individual species, populations, communities, or niches aid in understanding the determinants of biodiversity patterns, yet very few general models for biodiversity have emerged from simplistic approaches. We propose that a systematic, low-dimensional representation of environmental space with building blocks adopted from gradient, niche, metapopulation and assembly theory may unite old and new aspects of biodiversity theory and improve our understanding of variation in terrestrial biodiversity.We propose the term ecospace to cover the local conditions and resources underlying diversity. Our definition of ecospace encompasses abiotic position, biotic expansion and spatiotemporal continuity, which all affect the biodiversity of a biotope (α-diversity). Position refers to placement along abiotic gradients such as temperature, soil pH and fertility, leading to environmental filtering known from classical community theory. Expansion represents the build-up and diversification of organic matter that are not strictly given by position. Continuity refers to the spatiotemporal extension of position and expansion.Biodiversity is scale dependent. The contribution of one biotope to large scale diversity must be estimated by considering its unique contribution to the species richness of the surrounding landscape or region or to the biodiversity of the entire planet. In addition to the relationship between ecospace and biotope richness (α-diversity), we also propose a relation between the uniqueness of the biotope ecospace and the unique contribution of species to the surrounding larger-scale richness.Whereas the impacts of ecospace position and continuity on biodiversity have been studied in isolation, studies comparing or combining them are rare. Furthermore, biotic expansion has never been fully developed as a determinant of biodiversity, ignoring the megadiverse carbon-depending groups of insects and fungi. Precursors of the ecospace concept have been presented over the last 70 years, but they were never fully developed conceptually for terrestrial biodiversity or applied to prediction of biodiversity.Ecospace unites classical and – at times – contradicting theories such as niche theory, island biogeography theory and a suite of community assembly theories into one framework for further development of a general theory of terrestrial biodiversity

Predicting provenance of forensic soil samples:linking soil to ecological habitats by metabarcoding and supervised classification

Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA metabarcoding in predicting provenance in terms of environmental conditions, habitat type and geographic regions. We used linear regression for predicting environmental gradients of light, soil moisture, pH and nutrient status (represented by Ellenberg Indicator Values, EIVs) and Quadratic Discriminant Analysis (QDA) to predict habitat type and geographic region. eDNA data performed relatively well as a predictor of environmental gradients (R2 > 0.81). Its ability to discriminate between habitat types was variable, with high accuracy for certain forest types and low accuracy for heathland, which was poorly predicted. Geographic region was also less accurately predicted by eDNA. We demonstrated the application of provenance prediction in forensic science by evaluating and discussing two mock crime scenes. Here, we listed the plant species from annotated sequences, which can further aid in identifying the likely habitat or, in case of rare species, a geographic region. Predictions of environmental gradients and habitat types together give an overall accurate description of a crime scene, but care should be taken when interpreting annotated sequences, e.g. due to erroneous assignments in GenBank. Our approach demonstrates that important habitat properties can be derived from soil eDNA, and exemplifies a range of potential applications of eDNA in forensic ecology

Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants

Aim: A fundamental question in macroecology centres around understanding the relationship between species' local abundance and their distribution in geographical and climatic space (i.e. the multi‐dimensional climatic space or climatic niche). Here, we tested three macroecological hypotheses that link local abundance to the following range properties: (a) the abundance-range size relationship, (b) the abundance-range centre relationship and (c) the abundance-suitability relationship. Location: Europe. Taxon: Vascular plants. Methods: Distribution range maps were extracted from the Chorological Database Halle to derive information on the range and niche sizes of 517 European vascular plant species. To estimate local abundance, we assessed samples from 744,513 vegetation plots in the European Vegetation Archive, where local species' abundance is available as plant cover per plot. We then calculated the 'centrality', that is, the distance between the location of the abundance observation and each species' range centre in geographical and climatic space. The climatic suitability of plot locations was estimated using coarse‐grain species distribution models (SDMs). The relationships between centrality or climatic suitability with abundance was tested using linear models and quantile regression. We summarized the overall trend across species' regression slopes from linear models and quantile regression using a meta‐analytical approach. Results: We did not detect any positive relationships between a species' mean local abundance and the size of its geographical range or climatic niche. Contrasting yet significant correlations were detected between abundance and centrality or climatic suitability among species. Main conclusions: Our results do not provide unequivocal support for any of the relationships tested, demonstrating that determining properties of species' distributions at large grains and extents might be of limited use for predicting local abundance, including current SDM approaches. We conclude that environmental factors influencing individual performance and local abundance are likely to differ from those factors driving plant species' distribution at coarse resolution and broad geographical extents

Modern Approaches to the Monitoring of Biоdiversity (MAMBO)

EU policies, such as the EU biodiversity strategy 2030 and the Birds and Habitats Directives, demand unbiased, integrated and regularly updated biodiversity and ecosystem service data. However, efforts to monitor wildlife and other species groups are spatially and temporally fragmented, taxonomically biased, and lack integration in Europe. To bridge this gap, the MAMBO project will develop, test and implement enabling tools for monitoring conservation status and ecological requirements of species and habitats for which knowledge gaps still exist. MAMBO brings together the technical expertise of computer science, remote sensing, social science expertise on human-technology interactions, environmental economy, and citizen science, with the biological expertise on species, ecology, and conservation biology. MAMBO is built around stakeholder engagement and knowledge exchange (WP1) and the integration of new technology with existing research infrastructures (WP2). MAMBO will develop, test, and demonstrate new tools for monitoring species (WP3) and habitats (WP4) in a co-design process to create novel standards for species and habitat monitoring across the EU and beyond. MAMBO will work with stakeholders to identify user and policy needs for biodiversity monitoring and investigate the requirements for setting up a virtual lab to automate workflow deployment and efficient computing of the vast data streams (from on the ground sensors, and remote sensing) required to improve monitoring activities across Europe (WP4). Together with stakeholders, MAMBO will assess these new tools at demonstration sites distributed across Europe (WP5) to identify bottlenecks, analyze the cost-effectiveness of different tools, integrate data streams and upscale results (WP6). This will feed into the co-design of future, improved and more cost-effective monitoring schemes for species and habitats using novel technologies (WP7), and thus lead to a better management of protected sites and species