Background A large scale semi-quantitative biodiversity assessment was conducted in white oak woodlands in areas included in the Spanish Network of National Parks, as part of a project aimed at revealing biogeographic patterns and identify biodiversity drivers. The semi-quantitative COBRA sampling protocol was conducted in sixteen 1-ha plots across six national parks using a nested design. All adult specimens were identified to species level based on morphology. Uncertain delimitations and identifications due to either limited information of diagnostic characters or conflicting taxonomy were further investigated using DNA barcode information. New information We identified 376 species belonging to 190 genera in 39 families, from the 8,521 adults found amongst the 20,539 collected specimens. Faunistic results include the discovery of 7 new species to the Iberian Peninsula, 3 new species to Spain and 11 putative new species to science. As largely expected by environmental features, the southern parks showed a higher proportion of Iberian and Mediterranean species than the northern parks, where the Palearctic elements were largely dominant. The analysis of approximately 3,200 DNA barcodes generated in the present study, corroborated and provided finer resolution to the morphologically based delimitation and identification of specimens in some taxonomically challenging families. Specifically, molecular data confirmed putative new species with diagnosable morphology, identified overlooked lineages that may constitute new species, confirmed assignment of specimens of unknown sexes to species and identified cases of misidentifications and phenotypic polymorphisms.

A major objective in the exploration of Mars is to test the hypothesis that the planet hosted life. Even in the absence of life, the mapping of habitable and uninhabitable environments is an essential task in developing a complete understanding of the geological and aqueous history of Mars and, as a consequence, understanding what factors caused Earth to take a different trajectory of biological potential. We carried out the aseptic collection of samples and comparison of the bacterial and archaeal communities associated with basaltic fumaroles and rocks of varying weathering states in Hawai'i to test four hypotheses concerning the diversity of life in these environments. Using high-throughput sequencing, we found that all these materials are inhabited by a low-diversity biota. Multivariate analyses of bacterial community data showed a clear separation between sites that have active fumaroles and other sites that comprised relict fumaroles, unaltered, and syn-emplacement basalts. Contrary to our hypothesis that high water flow environments, such as fumaroles with active mineral leaching, would be sites of high biological diversity, alpha diversity was lower in active fumaroles compared to relict or nonfumarolic sites, potentially due to high-temperature constraints on microbial diversity in fumarolic sites. A comparison of these data with communities inhabiting unaltered and weathered basaltic rocks in Idaho suggests that bacterial taxon composition of basaltic materials varies between sites, although the archaeal communities were similar in Hawai'i and Idaho. The taxa present in both sites suggest that most of them obtain organic carbon compounds from the atmosphere and from phototrophs and that some of them, including archaeal taxa, cycle fixed nitrogen. The low diversity shows that, on Earth, extreme basaltic terrains are environments on the edge of sustaining life with implications for the biological potential of similar environments on Mars and their exploration by robots and humans.

To tackle urban heterogeneity and complexity, several indices have been proposed, commonly aiming to provide information for decision-makers. In this study, we propose a novel and customizable procedure for quantifying urban ecosystem integrity. Based on a citywide approach, we developed an easy-to-use index that contrasts physical and biological variables of urban ecosystems with a given reference system. The Urban Ecosystem Integrity Index (UEII) is the sum of the averages from the variables that make up its intensity of urbanization and biological components. We applied the UEII in a Mexican tropical city using land surface temperature, built cover, and the richness of native plants and birds. The overall ecosystem integrity of the city, having montane cloud, tropical dry, and temperate forests as reference systems, was low (-0.34 +/- SD 0.32), showing that, beyond its biodiverse greenspace network, the built-up structure highly differs from the ecosystems of reference. The UEII showed to be a flexible and easy-to-calculate tool to evaluate ecosystem integrity for cities, allowing for comparisons between or among cities, as well as the sectors/regions within cities. If used properly, the index could become a useful tool for decision making and resource allocation at a city level.

Species traits are an essential currency in ecology, evolution, biogeography, and conservation biology. However, trait databases are unavailable for most organisms, especially those living in difficult-to-access habitats such as caves and other subterranean ecosystems. We compiled an expert-curated trait database for subterranean spiders in Europe using both literature data (including grey literature published in many different languages) and direct morphological measurements whenever specimens were available to us. We started by updating the checklist of European subterranean spiders, now including 512 species across 20 families, of which at least 192 have been found uniquely in subterranean habitats. For each of these species, we compiled 64 traits. The trait database encompasses morphological measures, including several traits related to subterranean adaptation, and ecological traits referring to habitat preference, dispersal, and feeding strategies. By making these data freely available, we open up opportunities for exploring different research questions, from the quantification of functional dimensions of subterranean adaptation to the study of spatial patterns in functional diversity across European caves.

Maintaining enough green areas and ensuring fair access to them is a common planning challenge in growing and densifying cities. Evaluations of green area access typically use metrics like population around green areas (within a certain buffer), but these do not fully ensure equitable access. We propose that using systematic and complementarity-driven spatial prioritization, often used in nature conservation planning, could assist in the complex planning challenge. Here, we demonstrate the use of spatial prioritization to identify green areas with highest recreational potential based on their type and their accessibility for the residents of the Helsinki Metropolitan area, the capital district of Finland. We calculated travel times from each city district to each green area. Travel times were calculated separately to local green areas using active travel modes (walking and biking), and to large forests (attracting people from near and far) using public transport. We prioritized the green areas using these multimodal travel times from each district and weighting the prioritization with population data with Zonation, conservation prioritization software. Compared to a typical buffer analysis (population within a 500 m buffer from green areas), our approach identified areas of high recreational potential in different parts of the study area. This approach allows systematic integration of travel-time-based accessibility measures into equitable spatial prioritization of recreational green areas. It can help urban planners to identify sets of green areas that best support the recreational needs of the residents across the city.

Use of community trait-based metrics has been increasingly implemented for achieving an integrated view of biodiversity in conservation planning. We examined the extent, to which the use of community metrics based on species traits reflecting plausible sensitivity to change would contribute to our understanding of landscape characteristics of importance to the conservation of farmland birds in a poorly studied region of Northwest Russia. We collected species data on farmland from 230 transects covering a total 215 km for each year of 2008, 2010 and 2011 and analysed them using generalised linear mixed modelling. We derived community indices from species traits of habitat specialisation, trophic position, relative brain size and body mass. By relating these indices to the numbers of all species regarded farmland and Species of European Conservation Concern (SPEC), and by analysing them against the type of field and occurrence in typical non-cropped landscape elements, we showed consistent, albeit weak, congruence among the taxonomic and trait-based community descriptors. All community descriptors had their lowest estimates in arable fields. Community specialisation was the highest in open abandoned fields, which confirms the importance of such fields as refuges for regionally specialised species. Pastures were characterised by the highest community biomass, which indicates a particularly good resource base. Presence of ditches, of all non-cropped elements, had the strongest positive relationship with the community descriptors. The SPEC number strongly correlated with the overall species richness of farmland birds. A relatively weak congruence between taxonomic and trait-based community descriptors highlights their cornplementarity in understanding the underlying mechanisms of community changes. However, similarity in patterns among field types means that, under the current level of production in the region, accounting for the species richness of farmland birds seems to be sufficient to rapidly assess community sensitivity to agricultural change.

The aim of our study was to characterise and compare the richness and composition of endemic, native (non-endemic) and introduced arthropod assemblages of two Azorean Historic Gardens with contrasting plant species composition. We hypothesised that Faial Botanic Garden would hold higher arthropod diversity and abundance of native and endemic arthropod species due to its larger native plant community. Species were collected using several arthropod standardised techniques between April 2017 and June 2018. We used the alpha diversity metrics (Hill series) and the partitioning of total beta diversity (beta(total)) into its replacement (beta(repl)) and richness (beta(rich)) components, to analyse the adult and total arthropod community. The orders Araneae, Coleoptera and Hemiptera were also studied separately. Our results show that the number of exotic arthropod species exceeds the number of native and/or the endemic species in both gardens, but the arthropod community of Faial Botanic Garden exhibited a higher density of endemic and native species. Despite some minor exceptions, the geographic origins of plant communities largely influenced the arthropod species sampled in each garden. This study improves our knowledge about urban arthropod diversity in the Azores and shows how well-designed urban garden management and planning contribute to the conservation of native and endemic Azorean species.

Determining optimal forest management to provide multiple goods and services, also referred to as Ecosystem Services (ESs), requires operational-scale information on the suitability of the forest for the provisioning of various ESs. Remote sensing allows wall-to-wall assessments and provides pixel data for a flexible composition of the management units. The purpose of this study was to incorporate models of ES provisioning potential in a spatial prioritization framework and to assess the pixel-level allocation of the land use. We tessellated the forested area in a landscape of altogether 7500 ha to 27,595 pixels of 48 x 48 m(2) and modeled the potential of each pixel to provide biodiversity, timber, carbon storage, and recreational amenities as indicators of supporting, provisioning, regulating, and cultural ESs, respectively. We analyzed spatial overlaps between the individual ESs, the potential to provide multiple ESs, and tradeoffs due to production constraints in a fraction of the landscape. The pixels considered most important for the individual ESs overlapped as much as 78% between carbon storage and timber production and up to 52.5% between the other ESs. The potential for multiple ESs could be largely explained in terms of forest structure as being emphasized to sparsely populated, spruce-dominated old forests with large average tree size. Constraining the production of the ESs in the landscape based on the priority maps, however, resulted in sub-optimal choices compared to an optimized production. Even though the land-use planning cannot be completed without involving the stakeholders' preferences, we conclude that the workflow described in this paper produced valuable information on the overlaps and tradeoffs of the ESs for the related decision support. (C) 2016 Elsevier B.V. All rights reserved.

1. As resources for conservation are limited, gathering and analysing information from digital platforms can help investigate the global biodiversity crisis in a cost-efficient manner. Development and application of methods for automated content analysis of digital data sources are especially important in the context of investigating human-nature interactions. 2. In this study, we introduce novel application methods to automatically collect and analyse textual data on species of conservation concern from digital platforms. An end-to-end pipeline is constructed that begins from searching and downloading news articles about species listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) along with news articles from specific Twitter handles and proceeds with implementing natural language processing and machine learning methods to filter and retain only relevant articles. A crucial aspect here is the automatic annotation of training data, which can be challenging in many machine learning applications. A Named Entity Recognition model is then used to extract additional relevant information for each article. 3. The data collected over a 1-month period included 15,088 articles focusing on 585 species listed in Appendix I of CITES. The accuracy of the neural network to detect relevant articles was 95.91% while the Named Entity recognition model helped extract information on prices, location and quantities of traded animals and plants. A regularly updated database, which can be queried and analysed for various research purposes and to inform conservation decision making, is generated by the system. 4. The results demonstrate that natural language processing can be used successfully to extract information from digital text content. The proposed methods can be applied to multiple digital data platforms at the same time and used to investigate human-nature interactions in conservation science and practice.