Towards biodiversity conservation goals: remote sensing and ground-based data applied to the assessment of forest status

Forests cover approximately one-third of European land, providing several ecosystem services and hosting a large share of terrestrial biodiversity. However, direct and indirect human intervention in forests – i.e., through climate change – are the major drivers of the current biodiversity loss. In this context, the conservation and protection of forest ecosystems is one of the pivotal tasks for the protection of global biodiversity. To halter biodiversity loss, recent international policy initiatives have emphasized the need for technically sound, economically feasible, and socially acceptable approaches with clearly defined criteria and indicators for promoting biodiversity conservation at local, regional, and national levels. In this context, the combination of different sources of data could aim the process of biodiversity monitoring at different scales: ground-based and remote sensing data. On the one hand, National Forest Inventories (NFIs) are among the most important ground-based data available at the European level, being the official source of statistics on the status and trends of forests. While initially designed for wood production assessment, NFI data may be pivotal for ecological forest monitoring, thanks to their robust sampling protocols - enabling statistical inference - and regular field campaigns that ensure continuous information updates. On the other hand, satellite and remote sensing technologies generate a cost-effective, timely constant flow of data from different platforms with different resolutions, helping in the broad-scale assessment of proxies and biodiversity indicators. In this context, this thesis is aimed at proposing and testing different approaches to assess biodiversity in different environments: from old-growth forests to urban areas. Three main studies were covered in the present work. Study I involved the exploration of the potential of NFIs for estimating biodiversity, naturalness, and old-growth status indexes, aiming to establish compatible, scientifically relevant, and cost-effective indicators using existing NFI data at a European level. Based on data from the 2005 Italian NFI collected from 6,563 plots, 18 indicators were selected following previous experiences and then used to estimate biodiversity, naturalness, and old-growth status aggregated indexes. Relationships between the 18 indicators and the three indexes were investigated, along with comparisons of their relationships relative to forest type categories, management types, and protected versus non-protected areas. The method was also utilized in study II, where the assessment of the aggregated index for the old-growth status incorporated data from the Swedish National Forest Inventory and a dataset of sampled old-growth and primary forests. Using 11 diagnostic features, the index was employed on sampled plots from the Swedish NFI to identify forest stands that exhibit structural and deadwood-related attributes similar to those found in old-growth forests situated in the same environmental strata. Due to the systematic sampling approach utilized in the Swedish National Forest Inventory, the study enabled the creation of a comprehensive map encompassing all areas identified as old growth "hot spots." This map serves the purpose of further advancing the conservation of forests that possess significant biodiversity-related features that are uncommon for managed forests, such as the presence of old trees and a substantial amount and diversity of deadwood. As part of our III research study, we developed a standardized methodology for evaluating the connectivity of green urban areas in 28 European capital cities. Our analysis involved the creation of an urban vegetation map to distinguish the main types of vegetation coverage (i.e., trees, shrubs, and herbaceous) by gathering and aggregating data from the European Earth Observation programme Copernicus and its Land Monitoring Service (CLMS), for the year 2018. The map, which we validated against the ground-based surveys from the Land Use and Coverage Area Frame Survey (LUCAS), was used to assess the coverage of urban green areas within the 28 European capitals urban core areas with a 10m spatial resolution. Moreover, using the graph theory, the urban vegetation map served as the base for the network analysis and for evaluating the current landscape connectivity in European capital cities. Indeed, three global indicators were calculated for each city, along with the network features’ (i.e., nodes and links) characteristics, to provide information on the status of the main European cities’ urban vegetation. By pursuing these studies, the objective was to advance our understanding of the feasibility of utilizing regularly collected data, including both ground-based and remote sensing data, to effectively evaluate biodiversity in various settings throughout Europe. This effort sought to improve the monitoring and preservation of biodiversity across the continent.