Indicator Specification

This indicator monitors: observed regional trends in river flood discharges; projected changes in river floods with a return period of 100 years.

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The water intensity of crop production is defined as the total volume of water input (irrigation and soil moisture; measured in cubic meters (m 3) ) for one unit of gross value added generated from the production of all crop types, excluding relevant subsidies on crops (GVA adjusted for subsidies; measured in Purchasing Power Standard (PPS)). The lower the indicator value, the  less water intensive the crop production.

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This indicator is based on the Eurobarometer survey on biodiversity, a quantitative questionnaire-based survey, which also captures qualitative information, involving focus groups.

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The imperviousness indicator is defined as the yearly average imperviousness change between two reference years, as measured by imperviousness change products. The change is aggregated for a certain reference unit and expressed relative to the size of that unit (as a percentage). The imperviousness change value for a 100 m raster cell is based on 100 m imperviousness change products. The default reference unit is the country, but the indicator can be aggregated based on different spatial units. For example, for a certain country, a n imperviousness indicator value of 0.2 %, means that on average, an additional 0.2 % of this country's area has been sealed annually during the period between the two reference years in question. If above a certain rate of increase (threshold values) , this value can be used as a warning sign. The aggregation of imperviousness values to reference units is performed using the integrated spatial data platform at EEA.

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This indicator measures landscape fragmentation due to transport infrastructure and sealed areas. Unlike the previous indicator on fragmentation status, this updated version uses the TeleAtlas® Multinet data set to ensure the statistical comparability of the time series. While the Open Street Map data set is a valuable source of the street network available for the general public, there are still inconsistencies in this data set for some regions of Europe, which render it secondary to the TeleAtlas data set. As in the previous version, this indicator is based on the effective mesh size method  (Jaeger, 2000) . For some species, the effective mesh size (meff) can be interpreted as the area that is accessible when beginning to move from a randomly chosen point inside a landscape without encountering anthropogenic barriers such as transport routes or built-up areas. However, it should be stressed that for many species that can fly, or are effective dispersers in others ways, man-made structures may not act as barriers.  The combination of all barriers in a landscape is referred to as the fragmentation geometry (FG) hereafter. The meff value expresses the probability that any two points chosen randomly in an area are connected. Hence, meff is a measure of landscape connectivity, i.e. the degree to which movements between different parts of the landscape are possible. The larger the meff, the more connected the landscape. The indicator addresses the structural connectivity of the landscape and does not tackle functional, species-specific connectivity. The effective mesh density (seff) is a measure of landscape fragmentation, i.e. the degree to which movement between different parts of the landscape is interrupted by fragmentation geometry. It gives the effective number of meshes (or landscape patches) per 1 000 km 2 , in other words the density of the meshes. The seff value is 1 000 km 2 /meff, hence the number of meshes per 1 000 km 2 . The more barriers fragmenting the landscape, the higher the effective mesh density. The values of meff and seff are reported within the cells of a 1 km 2 regular grid. The value of meff is area-proportionally additive, hence it characterises the fragmentation of any region considered, independently of its size, and thus can be calculated for a combination of two or more regions. It has several advantages over other metrics: It addresses the entire landscape matrix instead of addressing individual patches. It is independent of the size of the reporting unit and its values can be compared among reporting units of differing sizes. It is suitable for comparing the fragmentation of regions with differing total areas and with differing proportions occupied by housing, industry and transportation structures. Its reliability has been confirmed on the basis of suitability criteria through a systematic comparison with other quantitative measures. The suitability of other metrics is limited, as they only partially meet the following criteria: intuitive interpretation; mathematical simplicity; modest data requirements; low sensitivity to small patches; detection of structural differences; mathematical homogeneity (i.e. intensive or extensive).

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