How to improve the distribution maps of habitat types at national scale

Annex I habitat types are a key factor for biodiversity conservation in Europe and distribution maps are essential for assessing their conservation status. We aim to increase the responsiveness to habitat knowledge needs and to propose the use of data collected at local scale for assessing a key indicator such as the Area of Occupancy (AOO) of habitats. In this paper, starting from the 4th Report of Habitats Directive data, we present a multi-source approach that allows national habitat distribution maps to be refined and their AOO estimated, by combining certified available information on habitat maps and vegetation databases. For the first time a comprehensive up-to-date knowledge on habitat distribution at national scale is now available; our approach will be an essential tool for the implementation of the Habitats Directive and to achieve the goals of EU biodiversity strategy in Italy

Temporal changes of vascular plant diversity in response to tree dieback in a mediterranean lowland forest

Palo Laziale wood is a small biotope of about 129 ha situated along the north coast of Rome. It is one of the last remaining patches of an ancient lowland floodplain forest that once covered the coastal area of the Lazio region. It contains several habitats and species of high conservation interest which has been included in the Natura2000 network. The forest suffered an impressive dieback event in 2003, coinciding with a particularly hot and dry summer. In the framework of an ecological restoration project (LIFE PRIMED LIFE17 NAT/GR/000511), a preliminary assessment of the biotic and abiotic components of the ecosystem was carried out, including a floristic analysis. This analysis was compared with that conducted in 1990 to assess whether there was any change in the species composition also following the forest dieback. Comparisons between biological forms, chorotypes and the Ellenberg indicators were also made in the analysis. The total flora of the site increased from 462 to 490 species. Moreover, there has been a turnover of species with the disappearance of some grassland and halophytic species and the appearance of allochthonous/ruderal and freshwater habitat species. Despite this, the flora remained unchanged in ecological terms, demonstrating a certain resilience of the plant species, confirming this approach to identify declining processes and support ecosystem-based restoration actions elsewhere

Investigating the effect of selective logging on tree biodiversity and structure of the tropical forests of Papua New Guinea

Abstract: Unsustainable exploitation of tropical forest resources is raising worldwide concern. In Papua New Guinea (PNG) timber harvesting has been identified as a major contributor to deforestation and forest degradation but its impact on biodiversity is still poorly understood. In this study we investigated the effect of selective logging on tree taxonomic composition, structure and diversity of PNG forests. We used data from 101 one-hectare permanent sample plots (PSPs) belonging to two vegetation types: low altitude forests on plains and fans (type P) and low altitude forests on uplands (type H). We used multivariate techniques to test for significant differences in species composition between plots of different vegetation types and disturbance regimes, identifying the tree taxa to which these differences could be ascribed. ANOVA was used to test for differences between logged-over and unlogged forest PSPs with respect to biodiversity (richness, Shannon's diversity, Pielou's evenness) and stand structure (stem density, basal area - BA). Temporal trends of forest features were analyzed using linear regression. Significant differences in taxonomic composition were found between logged-over and unlogged plots of the H type (p = 0.04). No differences were found in richness, diversity and evenness between logged-over and unlogged forest plots, while stem density was higher in the latter (421 ± 153 stems ha-1). Greater BA was found in unlogged forests (30.28 ± 4.45 m2 ha-1) of the H type when compared to the logged-over stands (15.52 ± 4.04 m2 ha-1). We detected positive trends in richness (0.55 ± 0.19 taxa ha-1 yr-1) and diversity after logging. Furthermore, H type forest exhibited positive trends in stem density (9 ± 1 stems ha-1 yr-1) and BA (0.42 ± 0.06 m2 ha-1 yr-1) with elapsed time since harvesting. Our analysis highlights some significant effects of logging activities on biodiversity and structure of PNG forests. Additionally, forests exhibited a significant recovery with respect to richness, diversity and stand structure. These preliminary results will be compared with data collected by the forthcoming National Forest Inventory in order to assess and monitor the effects of human activities and ecological factors on PNG forest biodiversity and develop appropriate conservation measures and sustainable management strategies

Seed viability and potential germination rate of nine endemic Boswellia taxa (Burseraceae) from Socotra Island (Yemen)

The endemic Boswellia species (Burseraceae) on Socotra Island (Yemen) are of great local significance due to their various local ethnobotanical uses. However, despite the fact that these trees are endangered, little is known about their biology. We tested seed germination rates in controlled experiments (trials of 21 days) for two subsequent years and for nine endemic taxa of Boswellia occurring on Socotra Island. For this, seeds were collected island-wide from a wide range of localities and for several populations per species. We observed differences in germination among Boswellia species, among species and localities and among both years, which indicates that the development of seeds is strongly affected by external ecological factors. Although we noted a large variation in seed germination (relatively high in Boswellia socotrana), and half of the species showed relatively low mean daily germination, our study indicated that all endangered endemic Frankincense Tree taxa of Socotra harbor the potential for in situ conservation through recruitment, given that known impacts can be reduced in local replantation areas (e.g., grazing)

Plant species richness hotspots and related drivers across spatial scales in small Mediterranean islands

Small islands represent a common feature in the Mediterranean and host a significant fraction of its biodiversity. However, the distribution of plant species richness across spatial scales—from local communities (alpha) to whole islands (gamma)—is largely unknown, and so is the influence of environmental, geographical, and topographical factors. By building upon classic biogeographic theory, we used the species–area relationship and about 4500 vegetation plots in 54 Central Mediterranean small islands to identify hotspots of plant species richness and the underlying spatial determinants across scales. To do so, we fitted and averaged eight species–area models on gamma and alpha richness against island area and plot size, respectively. Based on positive deviations from the fitted curves, we identified 12 islands as cross-scale hotspots. These islands encompassed around 70% of species and habitat richness, as well as almost 50% of the rarest species in the data set, while occupying less than 40% of the total island surface. By fitting generalized linear mixed models, we found that gamma richness was mainly explained by island area and was weakly related to mean annual temperature (positively) and annual precipitation (negatively). As for alpha richness, after accounting for the idiosyncratic effect of habitats and islands, plot size and gamma richness remained the only significant predictors, showing a positive relationship. This work contributes to the understanding of the patterns and drivers of plant diversity in Central Mediterranean small islands and outlines a useful methodology for the prioritization of conservation efforts

Mapping and assessment of ecosystems and their services. Urban ecosystems

Action 5 of the EU Biodiversity Strategy to 2020 requires member states to Map and Assess the state of Ecosystems and their Services (MAES). This report provides guidance for mapping and assessment of urban ecosystems. The MAES urban pilot is a collaboration between the European Commission, the European Environment Agency, volunteering Member States and cities, and stakeholders. Its ultimate goal is to deliver a knowledge base for policy and management of urban ecosystems by analysing urban green infrastructure, condition of urban ecosystems and ecosystem services. This report presents guidance for mapping urban ecosystems and includes an indicator framework to assess the condition of urban ecosystems and urban ecosystem services. The scientific framework of mapping and assessment is designed to support in particular urban planning policy and policy on green infrastructure at urban, metropolitan and regional scales. The results are based on the following different sources of information: a literature survey of 54 scientific articles, an online-survey (on urban ecosystems, related policies and planning instruments and with participation of 42 cities), ten case studies (Portugal: Cascais, Oeiras, Lisbon; Italy: Padua, Trento, Rome; The Netherlands: Utrecht; Poland: Poznań; Spain: Barcelona; Norway: Oslo), and a two-day expert workshop. The case studies constituted the core of the MAES urban pilot. They provided real examples and applications of how mapping and assessment can be organized to support policy; on top, they provided the necessary expertise to select a set of final indicators for condition and ecosystem services. Urban ecosystems or cities are defined here as socio-ecological systems which are composed of green infrastructure and built infrastructure. Urban green infrastructure (GI) is understood in this report as the multi-functional network of urban green spaces situated within the boundary of the urban ecosystem. Urban green spaces are the structural components of urban GI. This study has shown that there is a large scope for urban ecosystem assessments. Firstly, urban policies increasingly use urban green infrastructure and nature-based solutions in their planning process. Secondly, an increasing amount of data at multiple spatial scales is becoming available to support these policies, to provide a baseline, and to compare or benchmark cities with respect to the extent and management of the urban ecosystem. Concrete examples are given on how to delineate urban ecosystems, how to choose an appropriate spatial scale, and how to map urban ecosystems based on a combination of national or European datasets (including Urban Atlas) and locally collected information (e.g., location of trees). Also examples of typologies for urban green spaces are presented. This report presents an indicator framework which is composed of indicators to assess for urban ecosystem condition and for urban ecosystem services. These are the result of a rigorous selection process and ensure consistent mapping and assessment across Europe. The MAES urban pilot will continue with work on the interface between research and policy. The framework presented in this report needs to be tested and validated across Europe, e.g. on its applicability at city scale, on how far the methodology for measuring ecosystem condition and ecosystem service delivery in urban areas can be used to assess urban green infrastructure and nature-based solutions

Probabilistic and preferential sampling approaches offer integrated perspectives of Italian forest diversity

Aim: Assessing the performances of different sampling approaches for documenting community diversity may help to identify optimal sampling efforts and strategies, and to enhance conservation and monitoring planning. Here, we used two data sets based on probabilistic and preferential sampling schemes of Italian forest vegetation to analyze the multifaceted performances of the two approaches across three major forest types at a large scale. Location: Italy. Methods: We pooled 804 probabilistic and 16,259 preferential forest plots as samples of vascular plant diversity across the country. We balanced the two data sets in terms of sizes, plot size, geographical position, and vegetation types. For each of the two data sets, 1000 subsets of 201 random plots were compared by calculating the shared and exclusive indicator species, their overlap in the multivariate space, and the areas encompassed by spatially-constrained rarefaction curves. We then calculated an index of performance using the ratio between the additional and total information collected by each sampling approach. The performances were tested and evaluated across the three major forest types. Results: The probabilistic approach performed better in estimating species richness and diversity of species assemblages, but did not detect other components of the regional diversity, such as azonal forests. The preferential approach outperformed the probabilistic approach in detecting forest-specialist species and plant diversity hotspots. Conclusions: Using a novel workflow based on vegetation-plot exclusivities and commonalities, our study suggests probabilistic and preferential sampling approaches are to be used in combination for better conservation and monitor planning purposes to detect multiple aspects of plant community diversity. Our findings can assist the implementation of national conservation planning and large-scale monitoring of biodiversity

BioNoMo. The biodiversity network of Mozambique

Mozambique biodiversity richness plays a pivotal role to achieve the sustainable development of the country. However, Mozambique's flora and fauna diversity still remains broadly unknown and poorly documented. To properly address this issue, one of the strategic needs expressed by the Mozambican institutions was the development of a national biodiversity data repository to aggregate, manage and make data available online. Thus, a sustainable infrastructure for the standardisation, aggregation, organisation and sharing of primary biodiversity data was developed. Named the "Biodiversity Network of Mozambique" (BioNoMo), such a tool serves as a national repository of biodiversity data and aggregates occurrence records of plants and animals in the country obtained from floristic and faunistic observations and from specimens of biological collections. In this paper, the authors present the structure and data of BioNoMO, including software details, the process of data gathering and aggregation, the taxonomic coverage and the WebGIS development. Currently, aggregating a total of 273,172 records, including 85,092 occurrence records of plants and 188,080 occurrence records of animals (41.2% terrestrial, 58,8% aquatic), BioNoMo represents the largest aggregator of primary biodiversity data in Mozambique and it is planned to grow further by aggregating new datasets