Land productivity refers to spatial distribution and change of the vegetation cover - a key characteristic of ecosystem condition. By measuring vegetation productivity trends, the indicator is addressing one of the topics requested by the Land Degradation Neutrality target of the United Nations Development Goals (SDG 15.3).
Although further improvements are still necessary, the analysis of long time series shows clear and important signs of improvement in the North-East Atlantic Ocean and Baltic Sea ( 62.5 - 87.5 % of stocks meet at least one of the good environmental status criteria in these regions). Since the early 2000s, better management of fish and shellfish stocks has contributed to a clear decrease in fishing pressure in these two regional seas, with average fishing mortality dropping below the maximum rate of fishing mortality in 2017. This has led to signs of recovery in the reproductive capacity of several fish and shellfish stocks. If these efforts continue, fishing mortality in the region should remain on average near the maximum rate of fishing mortality and reproductive capacity should continue to improve, accomplishing the 2020 objective for healthy fish and shellfish stocks in the North-East Atlantic Ocean and Baltic Sea.
In contrast, the situation remains critical in the Mediterranean and Black Seas. Only 2 out of 33 stocks (6 %) in the Mediterranean Sea and 1 out of 7 stocks (14.3 %) in the Black Sea meet at least one of the good environmental status criteria. This is mainly due to the prevalence of overfishing and a significant lack of knowledge of the status of fish and shellfish stocks. Given this scenario, i t is unlikely that the 2020 policy objective will be met in the Mediterranean or Black Sea.
Overall, the 2020 objective of having healthy fish and shellfish populations is unlikely to be met in Europe’s seas without further collective action.
The indicator tracks both the status of commercial fish stocks in European regional seas and the pressure exerted by fisheries on those stocks, as well as the quality of the information available. To that end, the following is reported:
the status of marine fish and shellfish stocks based on the current level of exploitation and reproductive capacity;
the importance of the (sub-)region, reflected by the total landings (as a proxy of catch) of fish from commercial fisheries in European seas per MSFD (sub-)region;
the availability of appropriate information for the status assessment, as reflected by the proportion of those landings covered by quantitative stock assessments (i.e. the proportion providing the required indicators and their reference levels).
Status of marine fish and shellfish stocks
The MSFD requires GES to be achieved by 2020 (EC, 2008). According to the MSFD (Descriptor 3), three criteria are relevant to determining if a fish or shellfish stock has achieved GES: (1) it should be exploited sustainably, consistent with high long-term yields; (2) it should have full reproductive capacity, to maintain stock biomass; and (3) a certain proportion of older and larger fish/shellfish should be maintained (or increased), as this is an indicator of a healthy stock.
Sustainable exploitation: sustainably exploited stocks are stocks for which F is at or below levels that deliver MSY, i.e. F ≤ F MSY . Thus, a stock is considered to have been assessed against this criterion only if values for F and F MSY are available, and the stock is considered to have achieved GES only if F ≤ F MSY .
Reproductive capacity: in areas assessed by the International Council for the Exploration of the Seas (ICES), the criterion for sustainable reproductive capacity (SSB > SSB MSY ) has been changed, for pragmatic reasons, to SSB > MSY B trigger . SSB is consistently provided as part of ICES stock assessments, i.e. of the North-East Atlantic Ocean and Baltic Sea, but not, for the most part, by assessments of the Scientific, Technical and Economic Committee for Fisheries (STECF), i.e. of the Mediterranean and Black Sea stocks. Similarly to the above, a stock is considered to have been assessed against this criterion if values for SSB and a good proxy for SSB MSY (i.e. MSY B trigger ) are available, and the stock is considered to have achieved GES only if SSB > SSB MSY (or an appropriate proxy).
Healthy age and size structure: in this case, the assumption is that a stock with sufficient numbers of old and large fish is healthy. However, this criterion is not sufficiently developed and no threshold for GES is known for this criterion. Therefore, it is not included.
This has resulted in four assessment categories:
not assessed: no sufficient information available to assess status;
F: status assessed based only on F and F MSY;
SSB: status assessed based only on SSB and SSB MSY (or some proxy, i.e. MSY B trigger );
F and SSB: status assessed based on both F and SSB.
Because of ongoing discussions about the criteria integration rules for descriptor 3, the stocks are classified as:
assessed stocks for which adequate information is available to determine GES based on F and SSB;
assessed stocks for which insufficient information is available to determine GES based on F or SSB;
assessed stocks for which insufficient information is available to determine GES according to both reference points F and SSB.
For those stocks for which adequate information is available to determine GES based on fishing mortality (F) and/or reproductive capacity (SSB), a second distinction is made between (1) stocks in good status based on both fishing mortality and reproductive capacity; (2) stocks in good status based on only one criteria (either because one of the two criteria is in good status or data are available for only one criteria and it is in good status); and (3) stocks not in good status (either because one of the two criteria is not in good status or data are available for only one criteria and it is not in good status).
Total landings
Landings information for the North-East Atlantic and the Baltic Sea is based on the ICES official nominal catches, 2006-2017 data set . Fisheries nominal catch statistics are reported annually by national offices. In cooperation with Eurostat and the Food and Agriculture Organization of the United Nations (FAO), the ICES prepares and publishes the official nominal catch statistics data set for the North-East Atlantic (FAO major fishing area 27). Landings information for the Mediterranean Sea and the Black Sea is based on the FAO's capture production data set. For the Mediterranean and Black Seas, the figures are based on 2016 landings data.
Only some of the species/taxa in the landings data can be considered 'commercial fish', which, for assessment purposes, may consist of several stocks. Only some of these stocks are covered by quantitative stock assessments such that their status can be assessed based on the above criteria.
Stocks
In the North-East Atlantic area, stocks are generally defined based on biological criteria and knowledge of population migration, mixing and spawning areas. For example, cod in the North-East Atlantic is currently considered to form 16 different stocks, between which mixing is generally negligible. These stocks are found over multiple MSFD ecoregions, and some individual stock distributions cover more than one ecoregion. However, in this analysis each stock has been assigned to a single ecoregion (see Methodology).
In the Mediterranean and Black Seas, on the other hand, stocks are mostly defined by management area because of a lack of biological knowledge. Because these stocks are based on a specific geographical area, most can be attributed to a specific MSFD (sub-)region.
EUROPEAN COMMISSION, 2019 Public Opinion
Using big data from Copernicus Land Monitoring Service, as well as other satellite and user data sources, Viridian Raven has developed a set of algorithms that gives a risk analysis of bark beetles in forests. This enables foresters to see which parts of their forests have a high risk of bark beetle activity and enables fieldwork to be carried out more effectively saving time and allowing for more nests to be found earlier.
Soil plays a crucial role in nature’s cycles, including the nutrient cycle, which involves how much soil organic
matter — i.e. carbon, nitrogen and phosphorus — is taken up and stored in soil. Organic compounds, such
as leaves and root tips, are broken down to simpler compounds by organisms living in soil before they can
be used by plants. Some soil bacteria convert atmospheric nitrogen into mineral nitrogen, which is essential
for plant growth. Fertilisers introduce nitrogen and phosphates to induce plant growth but not all amounts
are taken up by plants. The excess can enter rivers and lakes and affect life in these water ecosystems.
This data viewer provides information about the land cover and land cover change within the Natura 2000 network.
This interactive data viewer provides an easy and comprehensive access to land cover accounts for Europe (EEA39 and EU28) derived from the CORINE land cover data series. Statistics are derived for every 6 years of the acquisition period, as well as for the entire period (2000-2018). The viewer facilitates the assessment of land cover consumed or created over a specific period and the reason for the observed change (e.g. urban sprawl or arable land loss), which can be analyzed within user defined spatial units such as administrative regions, biogeographical regions or land cover classes.
Article 12 dashboards providing summary of results for each Member State (national summaries)
This interactive data viewer provides a set of dashboards giving an overview of the land take and net land take processes for Europe (EEA39 and EU28) derived from the CORINE land cover data series. Statistics are derived for every 6 years of the acquisition period, as well as for the entire period (2000-2018). The viewer facilitates the assessment of land take over a specific period as well as the land use drivers of the observed changes, which can be analyzed within user defined spatial units such as administrative regions, biogeographical regions or land cover classes.
This dataset refers to the Richness index of Species and Habitats of Conservation Concern indicator. This indicator has been developed to be used as a sub-indicator for contributing to the identification of the High Nature Value (HNV) Forest Areas as it will be integrated with other sub-indicators of horizontal structure, management and naturalness to generate the final composite indicator. It is composed itself of three sub-indicators: “Forest Non-bird species”, “Forest bird species” and “Forest habitats”. All the three sub-indicators build on distribution data from the reporting of habitat and species conservation status under Article 17 of the Habitats Directive and Article 12 of the Birds directive which describe their distribution at 10km grid resolution. The forest species and the forest habitats proposed to be used for the HNV forest area identification were selected based on expert judgement (ETC/BD) and raster files reporting the count of forest species and habitats were created. At this stage, no weight is applied based on Habitat and Species prioritization, conservation status or endemism. The sub-indicators were then normalized for each European forest type and successively combined not assigning any specific weight to a particular sub-indicator.
The values for this indicator, present in this dataset, ranges between 0 and 1. The values close to 1 mean high presence of habitats and species related to forest, whereas the lower richness are closer to 0. It covers the forested areas of the EU27 Member States except for Cyprus (data from Croatia will be reported starting from the next update regarding the period 2013-2018).
Forest management involves various degrees of human intervention to safeguard the forest ecosystem and its functions as well as the exploitation of forest resources. While the objectives of management vary widely and include the protection of resources in protected forests and nature reserves, the primary objective is mostly the production of wood products. Although sustained yield forestry continues to be widely practised, there is an increasing trend towards the management of forests as ecological systems with multiple economic benefits and environmental values, ensuring that benefits meet present as well as future generations’ needs. In order to assess forest management intensity in Europe an indicator based on three data sources has been developed: a) Fast track ecosystem capital accounts (forest growth & harvest – disaggregated to 1km grid), b) Potential forest management (gradient of intensity of intervention with the natural processes in a forest) c) Forest fragmentation (forest ecosystem network connected by forest bridges – GUIDOS Morphological Spatial Pattern Analysis).
Each input dataset has been assessed separately in a first step in terms of pressures on forest ecosystems which are the result of the specific management, use or respectively state of the forest patch. The overall management related pressure is then derived by crossing the relative pressures by each input and evaluating the constellation of the input representative factors.
This updated version of the management related forest pressures is based on the first assessment done in framework of the ETC-SIA report "Land use and land management related pressures on agricultural and forest ecosystems" (ETC-SIA, Task 1.8.4.3 Ecosystem pressures).
The natural assemblage species indicator dataset is a forest dataset that measures the congruency between the potential and current tree species distribution. The natural assemblage indicator is considered one of the key indicator for the identification of High Nature Value forest area in Europe. The reference year for this data set is 2006 and the spatial coverage is including the 28 EU Member States, Liechtenstein, Norway, Switzerland, and Turkey.
The methodological approach is based on two data sources: (1) EUNIS woodland, forest and other wooded land habitats, predicted potential distribution of habitat suitability –EEA- as potential distribution; (2) Relative probability of presence of forest tree species (RPP) of European Atlas of Forest Tree Species –JRC- as current distribution.
The dataset values express, in the fuzzy values between 0 and 1, the percentage of tree species vegetation agreed with potentially dominant tree species by pixels. This measure is independent of the current forest coverage. The values close to 1 mean high percentage of native tree species (natural) whereas values close to 0 are an approximation of a low level of naturalness, being a high percentage of non-native species.
Land recycling addresses the reuse of abandoned, vacant or underused urban land for new developments within FUAs (Functional Urban Areas, i.e. urban agglomerations). Land recycling is considered a response to land take within FUAs, i.e. urban development on arable land, permanent crop land or semi-natural areas. It is a key planning instrument for achieving the goal of no net land take by 2050 (EC, 2016).
The intensity of land take is calculated as land take in the given period in % of artificial surfaces in the year 2000. For easier comparability land take is summarized within NUTS3 regions.
Monitoring schemes show significant long-term (25-year) downward trends in common birds (in particular farmland birds) and grassland butterfly population numbers, with no signs of recovery.
Between 1990 and 2016, there was a 9 % decrease in the index of common birds in the 26 EU Member States with bird population monitoring schemes. This decrease is slightly greater (11 %) if figures for Norway and Switzerland are included. The common forest bird index decreased by 3 % (EU) and by 5 % (EU plus Norway and Switzerland) over the same period.
The decline in common farmland bird numbers over the same period was much more pronounced, at 32 % (EU) and 35 % (EU plus Norway and Switzerland).
The index of grassland butterflies has declined significantly in the 15 EU countries where butterfly monitoring schemes exist. In 2017, the index was 39 % below its 1990 value.
This indicator shows trends in the abundance of common birds and butterflies across their European ranges over time . It is a composite of many species trend indices. A value of 100 is set for each species in the start year. If a species is added to the composite index after the start year, it is scaled to the index value of the year it was added to the indicator.
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