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The EU Biodiversity Strategy for 2020 was a driving force behind spatially explicit quantifications of Ecosystem Services (ES) in Europe. In Portugal, the MAES initiative (ptMAES–Mapping and Assessment of Ecosystem and their Services) was conducted in 2014 to address Target 2 (Action 5) of the Strategy, namely mapping and assessing ecosystems, ecos...
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... specific land-use classification adopted in the NIR (Kyoto Protocol land-use classes, Table 3) was translated into land-use typologies (COS07) for harmonization of legends and further use in our study. This harmonization (Supplementary Material Table S4) was later evaluated and approved by NIR authors in a meeting. ...Context 2
... birds are usually referred to as an "indicator" group for several environmental parameters [22], including biodiversity and the condition of ecosystems, bird diversity was also chosen to assess EC. We performed a multiple logistic regression with presence/absence records of farmland and forest bird species and a set of explanatory variables (land-use typology, topography, temperature, and rainfall) ( Table 4). See Supplemetary Material Table S1. ...Context 3
... Production was estimated as mean annual increments of forests trees as presented in the NIR (reported for KP forest classes, see carbon sequestration above), deducing biomass losses due to natural mortality. Spatialization of ES supply was possible after harmonization of legends between KP classes and COS07 (see Supplementary Material Table S4.) ...Similar publications
Increasing climate change has led to an increase in urban flood events. Events with a return period of twenty years become events with a period of two to three years. The primary objectives of this study are to evaluate the performance of flood regulation models using different input data and compare their performance for flood regulation supply (F...
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... This study was developed in an agricultural landscape in the South of Mainland Portugal, using a previously constructed FS typology based on data from the IACS for 2017, coupled with the LPIS . The majority of the analysed EC and ES indicators resulted from a pilot project carried out in Portugal in 2014, driven by the Action 5 of the EU Biodiversity Strategy for 2020, which called on EU member states to carry out the Mapping and Assessment of Ecosystems Services (MAES) (Laporta et al., 2021). ...
... The information about farming systems (FS) was developed by Ribeiro et al. (2021), which we complemented with data from the LULC map for 2015 (Direcção Geral do Território, 2018). Information regarding ES and EC was developed in the scope of a pilot project carried out in Portugal in 2014 (Laporta et al., 2021). We complemented the information on EC and ES with data from the Atlas of Breeding Birds in Portugal (1999-2005 (Equipa Atlas, 2008) and from the Portuguese National Fire Database (ICNF, 2019). ...
... The farmland birds, forest specialist birds, and fire protection indicators were developed as part of this study. The remaining indicators (plant diversity, soil Organic matter and control of soil erosion) were spatially modelled as part of a pilot project carried out in Portugal in 2014 that was driven by the Action 5 of the EU Biodiversity Strategy for 2020, which called on EU member states the Mapping and Assessment of Ecosystems Services (MAES) (Laporta et al., 2021). ...
Agricultural landscapes are linked to many functions that benefit human well-being, with a focus on food production. These functions are intrinsically linked with the management choices made by farmers, which are reflected in different farming systems (FS) and their shares in the landscape. However, there is a mismatch between the level where these decisions are taken-farm level-and the landscape level, where many ecosystem processes and interactions take place. The FS approach is one way to bridge the gap between both levels since it enables the joint assessment of multiple management decisions from adjacent farmers using farmlevel data and combining them at the landscape level through clustering techniques. The result is a spatial composition of different FS that enables us to capture landscape gradients and spatially relate them with biodiversity and ecosystem services, thus helping to inform and design policies to affect farming system choice. In Europe, the use of the Integrated Administration and Control System (IACS) database, coupled with the Land Parcel Information System (LPIS), a high-resolution spatially-explicit identification system for agricultural plots, provides a potentially rich source of information on agricultural management (e.g., type of crop, livestock stocking, land use). In this study, we investigated the spatial associations between ecosystem condition and ecosystem services indicators; and explored relationships between landscape gradients and these indicators using a FS approach based on IACS and LPIS data. Agroforestry systems were shown to be linked to a greater ecosystem condition and ecosystem services delivery. In contrast, LG dominated by very intensive and specialized FS revealed the most pronounced negative effects on ecosystems.
... Of these measures, the GAEC requirement for Crop Rotation or Soil Carbon (C) Content involved from the beginning the farmer in the installation of cover crops and organic manuring, never requiring specific tillage, which became, by contrast, a prevalent practice in carbon farming. An ample body of literature addresses the beneficial effects of the installation of cover crops in good agricultural practice [21][22][23][24]. Conventional soil management associated with farm subsidies implies that all farmers comply with GAEC measures at the farm level and the landscape scale, whereas carbon farming has the farm-level remit determined by voluntary markets. ...
Soil-water practice is essential for farm sustainability, thereby establishing the reference level for agricultural policy of the European Union (EU). This paper focuses on the critical gap in the knowledge surrounding comparison of soil-water effects of Good Agricultural and Environmental Conditions (GAEC) and carbon farming. We aim to interrogate the tasks assigned to soil-water standards during the 2005–2020 timeframe and identify soil-water effects under selected soil-water GAEC topics. The farm-level and landscape-scale effects were weighed for each standard. The investigation included an extensive meta-review of documents that featured scientific work on sustainable practice. In each GAEC document, soil-water sustainability was weighed vis-a-vis carbon farming. Our main finding was that the identification of soil-water effects within GAEC was addressed both at farm-enterprise level (E) and landscape scale (L). This identification was very similar among the sampled Member States (Czech Republic, Hungary, Poland, and Slovakia). A small differentiation was detected in how exact the guidance under each standard was in each of these Member States, and hence how the prioritization was scored, ranging from 1, most influential, to 5, least influential. The scores that prevailed were 2.5–5 on the part of the scoring instrument. Carbon farming is a welcome addition to the corpus of good farming practice and is complementary to GAEC.
... Indeed, many countries have started to identify ecosystems' extent and condition, and assess biodiversity, ecosystems, and ecosystem services at the national scale [48,49]. In some cases, these activities are aimed at improving the degree of thematic detail in ecosystem mapping, supporting the achievement of EU legislative frameworks [50,51]. The assessments require spatially explicit data and information to identify ecosystems and to delimit the LC/LU classes to be considered for the calculation of ecosystem services. ...
Developing appropriate tools to understand and protect ecosystems and the services they provide is of unprecedented importance. This work describes the activity performed by ISPRA for the mapping of the types of ecosystems and the evaluation of their related ecosystem services, to meet the needs of the "ecosystem extent account" and "ecosystem services physical account" activities envisaged by the SEEA-EA framework. A map of the types of ecosystems is proposed, obtained by integrating the main Copernicus data with the ISPRA National Land Consumption Map, according to the MAES (Mapping and Assessment of Ecosystems and their Services) classification system. The crop production and carbon stock values for 2018 were then calculated and aggregated with respect to each ecosystem. The ecosystem accounting was based on the land cover map produced by ISPRA integrating, according to an EAGLE compliant classification system, the same Copernicus and National input data used for mapping the types of ecosystems. The analysis shows the importance of an integrated reading of the main monitoring tools and the advantages in terms of compatibility and comparability, with a view to enhancing the potential of Copernicus land monitoring instruments also in the context of ecosystem accounting activities.
... Selection of ES is often completed as desk research, as it is strongly dependent on data availability (e.g., [19,22,59]) and does not include any participatory elements (but see [18] for Slovakia). A review of several European national-level ES processes [12] showed that the most common stakeholder groups identified and considered were ministries, environmental administration and academic institutions in all cases, as well as NGOs and private sector institutions in most cases. ...
... Ecosystem mappings within Europe often rely on Corine Land Cover and are thus of much coarser spatial resolution [20,22,62]. As the less detailed spatial and thematic resolution limit their usability for management and planning, many of the member states have recently created new ecosystem maps to serve as a basis for ES assessments (e.g., [63][64][65]). ...
... Defining the level of "actual use" is relatively straightforward for most provisioning services, as the use itself is extractive, material and, in many cases, it is even already quantified by national statistics/accountings [22,24,79]. However, some variation can be found when looking closer at the definitions, specifically in accounting for the production boundary (or the missing of this), i.e., accounting for the amount of human input in the final ES [80,85]. ...
Mapping and assessing ecosystem services (ES) projects at the national level have been implemented recently in the European Union in order to comply with the targets set out in the EU’s Biodiversity Strategy for 2020 and later in the Strategy for 2030. In Hungary this work has just been accomplished in a large-scale six-year project. The Hungarian assessment was structured along the ES cascade with each level described by a set of indicators. We present the selected and quantified indicators for 12 ES. For the assessment of cascade level 4, human well-being, a set of relevant well-being dimensions were selected. The whole process was supported by several forms of involvement, interviews, consultations and workshops and in thematic working groups performing the ES quantifications, followed by building scenarios and synthesizing maps and results. Here we give an overview of the main steps and results of the assessment, discuss related conceptual issues and recommend solutions that may be of international relevance. We refine some definitions of the cascade levels and suggest theoretical extensions to the cascade model. By finding a common basis for ES assessments and especially for national ones, we can ensure better comparability of results and better adoption in decision making.
