Search

Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three‐dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large‐scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps.Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km2).We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land‐cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait‐specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition.Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition.Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches. [ABSTRACT FROM AUTHOR]

The exploration of factors and processes affecting biodiversity loss is central to nature management and wildlife conservation, but only recently has knowledge about the absence of species been recognized as a valuable asset to understand the current biodiversity crisis. In this paper, we explore the dark diversity (species that belong to a site-specific species pool but that are not locally present) of breeding birds in Denmark assessed through species co-occurrence patterns. We apply a nation-wide atlas survey of breeding birds (with a 5 × 5 km resolution), to investigate how landscape characteristics may influence avian diversity, and whether threatened and near threatened species are more likely to occur in dark diversity than least concern (LC) species. On average, the dark diversity constituted 41% of all species belonging to the site-specific species pools and threatened and near-threatened species had a higher probability of belonging to the dark diversity than least concern species. Habitat heterogeneity was negatively related to dark diversity and the proportional cover of intensive agriculture positively related, implying that homogeneous landscapes dominated by agricultural interests led to more absent avian species. Finally, we found significant effects of human disturbance and distance to the coast, indicating that more breeding bird species were missing when human disturbance was high and in near-coastal areas. Our study provides the first attempt to investigate dark diversity among birds and highlights how important landscape characteristics may shape breeding bird diversity and reveal areas of considerable species impoverishment. [ABSTRACT FROM AUTHOR]

Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as light detection and ranging (lidar). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote sensing knowledge. We processed Denmark's publicly available national airborne laser scanning (ALS) data set acquired in 2014/15, together with the accompanying elevation model, to compute 70 rasterised descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than 40 000 km 2 covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (∼94 GB, compressed 16.8 GB), and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark's national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterised data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond. The full data set is available on Zenodo: 10.5281/zenodo.4756556 (Assmann et al., 2021); a 5 MB teaser subset is also available: 10.5281/zenodo.6035188 (Assmann et al., 2022a). [ABSTRACT FROM AUTHOR]

This study offers a first-of-its-kind investigation into the spatial and temporal transformation of agricultural land use and expansion in crops and livestock at national scale during the middle and latter half of the 19th century. We introduce an innovative methodological framework that combines historical data with advanced spatial analysis to trace and map the evolution of frontiers of agricultural land use changes, illustrating Denmark's agricultural evolution towards the modern era. Our research uncovers critical shifts in cropland, grazing land, and livestock density offering unprecedented insights into the mechanisms driving agricultural expansion and intensification. The mechanisms driving this expansion and their potential impact on contemporary agroecological challenges linked to land use intensification are explored. Our results point to a significant broadening and shifting of land use frontiers offering a historical perspective on agricultural land use. This sets the stage for promoting the analysis of drivers of change and gaining insights into how landscape development could be steered into an environmentally and societally more desirable and sustainable direction tackling present-day agroecological challenges. • We studied spatial and temporal patterns of agricultural frontiers. • Significant trends shed light on the evolving landscape of agricultural production. • Two distinct frontiers of agricultural land use are identified. • Over time, land use categories shift towards higher homogeneity. [ABSTRACT FROM AUTHOR]

Shrub encroachment in seminatural grasslands threatens local biodiversity unless management is applied to reduce shrub density. Dense vegetation of Cytisus scoparius homogenizes the landscape negatively affecting local plant diversity. Detecting structural change (e.g., biomass) is essential for assessing negative impacts of encroachment. Hence, exploring new monitoring tools to achieve this task is important for effectively capturing change and evaluating management activities.This study combines traditional field‐based measurements with novel Light Detection and Ranging (LiDAR) observations from an Unmanned Aircraft System (UAS). We investigate the accuracy of mapping C. scoparius in three dimensions (3D) and of structural change metrics (i.e., biomass) derived from ultrahigh‐density point cloud data (>1,000 pts/m2). Presence–absence of 12 shrub or tree genera was recorded across a 6.7 ha seminatural grassland area in Denmark. Furthermore, 10 individuals of C. scoparius were harvested for biomass measurements. With a UAS LiDAR system, we collected ultrahigh‐density spatial data across the area in October 2017 (leaf‐on) and April 2018 (leaf‐off). We utilized a 3D point‐based classification to distinguish shrub genera based on their structural appearance (i.e., density, light penetration, and surface roughness).From the identified C. scoparius individuals, we related different volume metrics (mean, max, and range) to measured biomass and quantified spatial variation in biomass change from 2017 to 2018. We obtained overall classification accuracies above 86% from point clouds of both seasons. Maximum volume explained 77.4% of the variation in biomass.The spatial patterns revealed landscape‐scale variation in biomass change between autumn 2017 and spring 2018, with a notable decrease in some areas. Further studies are needed to disentangle the causes of the observed decrease, for example, recent winter grazing and/or frost events.Synthesis and applications: We present a workflow for processing ultrahigh‐density spatial data obtained from a UAS LiDAR system to detect change in C. scoparius. We demonstrate that UAS LiDAR is a promising tool to map and monitor grassland shrub dynamics at the landscape scale with the accuracy needed for effective nature management. It is a new tool for standardized and nonbiased evaluation of management activities initiated to prevent shrub encroachment. [ABSTRACT FROM AUTHOR]

Summary: The main goal of the Habitats Directive, a key document for European conservation, is to maintain a ‘favourable’ conservation status of selected species and habitats. In the face of near-future climatic change this goal may become difficult to achieve. Here, we evaluate the sensitivity to climate change of 84 plant species that characterise the Danish habitat types included in the Habitats Directive. A fuzzy bioclimatic envelope model, linking European and Northwest African species’ distribution data with climate, was used to predict climatically suitable areas for these species in year 2100 under two-climate change scenarios. Climate sensitivity was evaluated at both Danish and European scales to provide an explicit European perspective on the impacts predicted for Denmark. In all 69–99% of the species were predicted to become negatively affected by climate change at either scale. Application of international Red List criteria showed that 43–55% and 17–69% would become vulnerable in Denmark and Europe, respectively. Northwest African atlas data were used to improve the ecological accuracy of the future predictions. For comparison, using only European data added 0–7% to these numbers. No species were predicted to become extinct in Europe, but 4–7% could be lost from Denmark. Some species were predicted to become positively affected in Denmark, but negatively affected in Europe. In addition to nationally endangered species, this group would be an important focus for a Danish conservation strategy. A geographically differentiated Danish conservation strategy is suggested as the eastern part of Denmark was predicted to be more negatively affected than the western part. No differences in the sensitivity of the Habitats Directive habitats were found. We conclude that the conservation strategy of the Habitats Directive needs to integrate the expected shifts in species’ distributions due to climate change. [Copyright &y& Elsevier]

Based on current evidence and established critical thresholds for soil degradation indicators, it is concerning that over 60-70% of European soils are unhealthy due to unsustainable management and the impact of climate change. Despite European and national efforts to improve soil health, significant gaps remain. The proposal for a Soil Monitoring and Resilience Law, to be implemented by the European Union, seeks to establish a framework for soil monitoring and promote sustainable management practices to achieve healthy soils by 2050. This requires extensive data collection and soil monitoring systems to accurately estimate soil health across Europe, considering the diversity of soil types, climates, and land uses. To establish a framework for soil monitoring, we must understand the site-specific status of soil and the ranges of soil health indicators across specific pedoclimatic regions. In our study, we evaluated the soil status in agricultural areas in Denmark using soil health indicators and a site-specific benchmarking approach. We compiled nationally representative datasets, combining point and model-informed data of soil parameters such as organic carbon content, bulk density, pH, electrical conductivity, clay-to-soil organiccarbon ratio, water erosion, and nitrogen leaching. By categorizing Danish agricultural soils into monitoring units based on textural classes, landscape elements, and wetland types, we calculated benchmarks for these indicators, considering different cropping systems. Our approach provided detailed point-based results and a spatially explicit overview of the status of soil health indicators in Denmark. We identified areas where soil deviates from the benchmarks of different indicators. Such deviations might indicate soil functions operating outside the normal range, posing potential threats to soil health. This proposed framework could support the establishment of a baseline for assessing the directionality of future changes in soil health. Moreover, it is adaptable for implementation by other countries to support assessments of soil health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)