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Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad‐scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental‐scale management plans for biodiversity conservation., We modeled EU habitat richness at continental scale as a function of geographic, climatic, and anthropogenic variables. We found geographical variables were by far the most strongly correlated with habitat richness, followed by climate. However, anthropogenic variables gained importance when considering their interactions, with important implications for conservation planning.

Forest fires are drivers of spatial patterns and temporal dynamics of vegetation and biodiversity. On the Canary Islands, large areas of pine forest exist, dominated by the endemic Canary Island pine, Pinus canariensis C. Sm. These mostly natural forests experience wildfires frequently. P. canariensis is well-adapted to such impacts and has the ability to re-sprout from both stems and branches. In recent decades, however, anthropogenically caused fires have increased, and climate change further enhances the likelihood of large forest fires. Through its dense, long needles, P. canariensis promotes cloud precipitation, which is an important ecosystem service for the freshwater supply of islands such as La Palma. Thus, it is important to understand the regeneration and vegetation dynamics of these ecosystems after fire. Here, we investigated species diversity patterns in the understory vegetation of P. canariensis forests after the large 2016 fire on the southern slopes of La Palma. We analyzed the effect of fire intensity, derived from Sentinel-2 NDVI differences, and of environmental variables, on species richness (alpha diversity) and compositional dissimilarity (beta diversity). We used redundancy analysis (dbRDA), Bray–Curtis dissimilarity, and variance partitioning for this analysis. Fire intensity accounted for a relatively small proportion of variation in alpha and beta diversity, while elevation was the most important predictor. Our results also reveal the important role of the endemic Lotus campylocladus ssp. hillebrandii (Christ) Sandral & D.D.Sokoloff for understory diversity after fire. Its dominance likely reduces the ability of other species to establish by taking up nutrients and water and by shading the ground. The mid-to long-term effects are unclear since Lotus is an important nitrogen fixer in P. canariensis forests and can reduce post-fire soil erosion on steep slopes.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. T. Biological invasions are a major global threat to biodiversity and often affect ecosystem services negatively. They are particularly problematic on oceanic islands where there are many narrow-ranged endemic species, and the biota may be very susceptible to invasion. Quantifying and mapping invasion processes are important steps for management and control but are challenging with the limited resources typically available and particularly difficult to implement on oceanic islands with very steep terrain. Remote sensing may provide an excellent solution in circumstances where the invading species can be reliably detected from imagery. We here develop a method to map the distribution of the alien chestnut (Castanea sativa Mill.) on the island of La Palma (Canary Islands, Spain), using freely available satellite images. On La Palma, the chestnut invasion threatens the iconic laurel forest, which has survived since the Tertiary period in the favourable climatic conditions of mountainous islands in the trade wind zone. We detect chestnut presence by taking advantage of the distinctive phenology of this alien tree, which retains its deciduousness while the native vegetation is evergreen. Using both Landsat 8 and Sentinel-2 (parallel analyses), we obtained images in two seasons (chestnuts leafless and in-leaf, respectively) and performed image regression to detect pixels changing from leafless to in-leaf chestnuts. We then applied supervised classification using Random Forest to map the present-day occurrence of the chestnut. Finally, we performed species distribution modelling to map the habitat suitability for chestnut on La Palma, to estimate which areas are prone to further invasion. Our results indicate that chestnuts occupy 1.2% of the total area of natural ecosystems on La Palma, with a further 12–17% representing suitable habitat that is not yet occupied. This enables targeted control measures with potential to successfully manage the invasion, given the relatively long generation time of the chestnut. Our method also enables research on the spread of the species since the earliest Landsat images.

Biological invasions are a major global threat to biodiversity and often affect ecosystem services negatively. They are particularly problematic on oceanic islands where there are many narrow-ranged endemic species, and the biota may be very susceptible to invasion. Quantifying and mapping invasion processes are important steps for management and control but are challenging with the limited resources typically available and particularly difficult to implement on oceanic islands with very steep terrain. Remote sensing may provide an excellent solution in circumstances where the invading species can be reliably detected from imagery. We here develop a method to map the distribution of the alien chestnut (Castanea sativa Mill.) on the island of La Palma (Canary Islands, Spain), using freely available satellite images. On La Palma, the chestnut invasion threatens the iconic laurel forest, which has survived since the Tertiary period in the favourable climatic conditions of mountainous islands in the trade wind zone. We detect chestnut presence by taking advantage of the distinctive phenology of this alien tree, which retains its deciduousness while the native vegetation is evergreen. Using both Landsat 8 and Sentinel-2 (parallel analyses), we obtained images in two seasons (chestnuts leafless and in-leaf, respectively) and performed image regression to detect pixels changing from leafless to in-leaf chestnuts. We then applied supervised classification using Random Forest to map the present-day occurrence of the chestnut. Finally, we performed species distribution modelling to map the habitat suitability for chestnut on La Palma, to estimate which areas are prone to further invasion. Our results indicate that chestnuts occupy 1.2% of the total area of natural ecosystems on La Palma, with a further 12–17% representing suitable habitat that is not yet occupied. This enables targeted control measures with potential to successfully manage the invasion, given the relatively long generation time of the chestnut. Our method also enables research on the spread of the species since the earliest Landsat images., This work was supported by the European H2020 Project ECOPOTENTIAL, grant agreement No. 641762. We thank Reinhold Stahlmann for his support in all questions related to spatial data.

© Pensoft Publishers. Background Biogeographical units are widely adopted in ecological research and nature conservation management, even though biogeographical regionalisation is still under scientific debate. The European Environment Agency provided an official map of the European Biogeographical Regions (EBRs), which contains the official boundaries used in the Habitats and Birds Directives. However, these boundaries bisect cells in the official EU 10 km x 10 km grid used for many purposes, including reporting species and habitat data, meaning that 6881 cells overlap two or more regions. Therefore, superimposing the EBRs vector map over the grid creates ambiguities in associating some cells with European Biogeographical Regions. New information To provide an operational tool to unambiguously define the boundaries of the eleven European Biogeographical Regions, we provide a specifically developed raster map of Grid-Based European Biogeographical Regions (GB-EBRs). In this new map, the borders of the EBRs are reshaped to coherently match the standard European 10 km x 10 km grid imposed for reporting tasks by Article 17 of the Habitats Directive and used for many other datasets. We assign each cell to the EBR with the largest area within the cell.

The Anthropocene is characterised by unprecedented declines in nature causing the sixth mass extinction event in earth history. The main drivers of these immense deteriorations are human land use and anthropogenic climate change. A dilemma evolves because human welfare depends on the conservation of nature’s integrity. We profit from ecosystem functioning, goods and services, which are based on biodiversity. Moreover, species have the right to exist independent of their use for us. The use and existence values of nature motivate nature conservation. Global biodiversity hotspots are in focus of international conservation as they contain a rich inventory of species. Inventory diversity is, nevertheless, only one of three broad categories classifying diversity indices. Other diversity metrics that offer complementary information refer to differentiation or proportional diversity, and account for the dissimilarity between species assemblages. Effective biodiversity conservation contemplates multiple measures of species diversity as well as threats to biodiversity. Anthropogenic climate change is a major threat to biodiversity that inevitably affects the entire global land in multiple ways, not only hotspots of species diversity. The change in the magnitude, timing, position and availability of climate conditions exerts influence on the demography, phenology and range of species, with unknown consequences for ecosystems worldwide. Therefore, biodiversity conservation must be applied to large geographical extents, which is the foundation of conservation biogeography. Conservation biogeographers investigate protected areas as major tools to protect biodiversity because a high degree of biodiversity can hardly exist in unprotected landscapes that are intensively used by humans. Approximately 15% of global land is covered by protected areas. To overcome the many challenges emerging from anthropogenic pressures, protected areas need efficient and effective planning and management. Such planning and management often lacks the continuous availability of data on current states and trends of nature and threats, which can be delivered by in-situ monitoring, remote sensing and open data infrastructures. Since resources for planning and management are limited, conservationists prioritise conservation targets. Given the rising importance of protected areas owing to expanding human land use and increasing climate change, I address the effectiveness and efficiency of terrestrial protected areas in conserving biodiversity under anthropogenic threats through the six manuscripts of this thesis. I assign each manuscript to the scientific modules of an adaptive protected area management cycle. Adaptive protected area management is an auspicious concept to ensure the enduring effectiveness of protected areas under uncertain future developments. My manuscripts provide missing scientific foundations of adaptive protected area management. In Manuscript 1, I present a comprehensive quantification of the diversity of the European Union’s priority species within major protected areas in the European Union. This quantification of inventory, differentiation and proportional diversity informs protected area management of manifold metrics of species diversity to increase protected area management effectiveness from the local to the European extent. In Manuscript 2, I prove to what degree remote sensing signals (i.e. airborne Light Detection and Ranging data, and a time series of multispectral Sentinel-2 data) reflect the compositional dissimilarity of perennial plant communities on the protected island of La Palma, Canary Islands. This study fosters efficient monitoring of differentiation diversity by remote sensing techniques. Monitoring of the biotic and abiotic environment is a scientific prerequisite of adaptive protected area management. In Manuscript 3, I developed a method to optimise in-situ surveys of biodiversity, i.e. to maximise information content and minimise sampling effort. This approach enhances the efficiency of in-situ surveys, which is required under limited management resources, such as time and funds. As a case study, I analysed the inventory diversity of alpine grassland in the Gran Paradiso National Park, Italy. I supply the data on this threatened vegetation type in an open data paper (Manuscript 4). Moreover, I show predicted changes in the availability of climate conditions (Manuscript 5) and the predicted magnitude of climate change (Manuscript 6) within the global terrestrial protected area estate for two alternative climate change scenarios in the year 2070. These two studies inform protected area management worldwide of the climate change impacts on biodiversity, to sustain protected area management effectiveness from the local to global extent. In addition, I aim at spreading this conservation-minded knowledge and data by providing open-source software and open data, and by open-access publishing. Consequently, this thesis advances the effectiveness and efficiency of protected areas in biodiversity conservation, mediated through adaptive protected area management. Filling biogeographical knowledge gaps, improving biogeographical forecasts and promoting biodiversity conservation by communicating research are permanent tasks for conservation biogeographers. The global biodiversity crisis can be solved by local conservation strategies worldwide that are internationally coordinated. Eventually, I consider the development of a global adaptive protected area management system the most favourable future perspective in conservation biogeography to stop nature’s declines and guarantee a sustainable future for the welfare of generations to come.

Protected areas (PAs) constitute major tools in nature conservation. In the European Union (EU), the Birds and Habitats Directives are the most important policies for conservation strategy, legally preserving Europe’s characteristic, rare, endemic and threatened biota. We used occurrence data for species listed in the directives’ Annexes to assess the uniqueness of major PAs in the EU (National Parks, Biosphere Reserves); this is important for preserving the EU’s focal species. We developed a novel, multifunctional approach to calculate different metrics of conservation value that represent different components of species diversity within the PAs, involving inventory diversity, deviation from the species–area relationship, species rarity and differentiation diversity. Applying it, we found that individual PAs frequently vary considerably in their scores on different components, which are often disconnected from PA size. PAs around the EU periphery, often containing few species, are key to conserving species that are rare in the EU. Because our analysis focuses on EU priority species and includes different components of diversity, it allows more appropriate estimation of conservation value inside PAs in context of the EU than recent, high-profile, global-level research. We offer tools to evaluate, and information to regulate, the representativeness, persistence and efficiency of PAs.

The diversity of alpine grassland species and their functional traits constitute alpine ecosystem functioning and services that support human-wellbeing. However, alpine grassland diversity is threatened by land use and climate change. Field surveys and monitoring are necessary to understand and preserve such endangered ecosystems. Here we describe data on abundances (percentage cover) of 247 alpine plant species (including mosses and lichens) inside nine 20 m by 20 m plots that were subdivided into 2 m by 2 m subplots. The nine plots are located in Gran Paradiso National Park, Italy. They cover three distinct alpine vegetation subtypes (‘pure’ natural grassland, sparsely vegetated ‘rocky’ grassland, and wetland) in each of three valleys (Bardoney, Colle de Nivolet and Levionaz) between 2200 and 2700 m a.s.l., i.e. above the treeline. The vegetation survey was conducted in 2015 at the peak of vegetation development during August. The dataset is provided as supplementary material and associated with the research article “Optimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland” [1]. See [1] for data interpretation. Keywords: Alpine grassland, Species diversity, Plot data, Cover, Abundance, Vegetation survey, Vegetation monitoring