Annemarie Bastrup-Birk

Mapping and Assessment of Ecosystems and their Services: Indicators for ecosystem assessments under Action 5 of the EU Biodiversity Strategy to 2020

Environment Europe Direct is a service to help you find answers to your questions about the European Union Summary The second MAES report presents indicators that can be used at European and Member States level to map and assess biodiversity, ecosystem condition and ecosystem services according to the Common International Classification of Ecosystem Services (CICES v4.3). This work is based on a review of data and indicators available at national and European level and is applying the MAES analytical framework adopted in 2013.

Modelling and mapping the suitability of European forest formations at 1-km resolution

Proactive forest conservation planning requires spatially accurate information about the potential distribution of tree species. The most cost-efficient way to obtain this information is habitat suitability modelling i.e. predicting the potential distribution of biota as a function of environmental factors. Here, we used the bootstrap-aggregating machine-learning ensemble classifier Random Forest (RF) to derive a 1-km resolution European forest formation suitability map. The statistical model use as inputs more than 6,000 field data forest inventory plots and a large set of environmental variables. The field data plots were classified into different forest formations using the forest category classification scheme of the European Environmental Agency. The ten most dominant forest categories excluding plantations were chosen for the analysis. Model results have an overall accuracy of 76%. Between categories scores were unbalanced and Mesophitic deciduous forests were found to be the least correctly classified forest category. The model’s variable ranking scores are used to discuss relationship between forest category/environmental factors and to gain insight into the model’s limits and strengths for map applicability. The European forest suitability map is now available for further applications in forest conservation and climate change issues.

National Forest Inventories: Prospects for Harmonised International Reporting

Despite the important differences in inventory estimates resulting from the use of different national definitions, variables, and variable thresholds, prospects for developing procedures leading to compatible estimates amongst countries are generally positive. Analyses of national definitions and responses to questionnaires distributed by COST Action E43 indicate that definitions tend to be based on the same rather small set of inventory variables. For example, national definitions of forest all focus on minimum area, minimum cover, minimum width, and minimum height, although the thresholds for these variables differ considerably among countries (Vidal et al. 2008). Important differences among these national definitions relate mostly to kinds of lands with tree cover that are considered forest for reporting purposes: for example, managed versus unmanaged forest land, inclusion or exclusion of forested park and leisure lands, inclusion or exclusion of forest lands whose tree cover consists primarily of non-native species, and inclusion or exclusion of permanently non-stocked areas within forest land (Cienciala et al. 2008).

The Need for Harmonized Estimates of Forest Biodiversity Indicators

Forest biodiversity is crucial to the ecological, economic, and social well-being of earth’s civilisations. Unfortunately, however, forest biodiversity is threatened to a serious degree in nearly all countries. Therefore, many countries have agreed to be parties to international agreements focused on maintaining, restoring, and monitoring biodiversity; further, these countries have agreed to report to international bodies on the status and trends in forest biodiversity. NFIs are the primary source of large-scale information available for this purpose, but the large variety of definitions, protocols, sampling designs, and plot configurations used by NFIs makes comparable international reporting extremely difficult. COST Action E43 was initiated to address this problem by developing harmonization techniques that facilitate common reporting. Harmonization typically consists of two components: development of common international reference definitions and development of bridging techniques that facilitate estimation according to reference definitions using data collected according to national definitions. Working Group 3 of COST Action E43 has focused its harmonization efforts on issues related to biodiversity. The chapters and sections that follow document these efforts in detail.

Chapter 17 - Meteorology

Meteorological variables affect composition, structure, growth, health, and dynamics of forest ecosystems. The measurement of meteorological data at forest monitoring plots is essential for the interpretation of climate change effects. Within an ecological monitoring network, standard meteorological variables such as precipitation, air temperature, relative humidity, solar radiation, wind velocity, and direction should be measured. These variables are essential for the calculation of total deposition of air pollutants, for the interpretation of biological processes or for the derivation of water budgets and percolation from the rooting zone. Additional variables of interest are soil temperature, stand precipitation, and soil moisture. The magnitude and changes in time of the meteorological variables can be assessed as explanatory factors for other observations made in forest ecological monitoring. A detailed description of different methods is given. As an example for an integrated analysis, the application of meteorological data in water budget modeling is described and results of a pilot study are shown.

Identifying strengths and limitations of pan-European forest cover maps through spatial comparison

Detailed and harmonized information on spatial forest distribution is an essential input for forest-related environmental assessments, in particular, for biomass and growing stock modeling. In the last years, several mapping approaches have been developed in order to provide such information for Europe in a harmonized way. Each of these maps exhibits particular properties and varies in accuracy. Yet, they are often used in parallel for different modeling purposes. A detailed spatial comparison seemed necessary in order to provide information on the advantages and limitations of each of these forest cover maps in order to facilitate their selection for modeling purposes. This article confronts the high-resolution forest cover map recently developed by the Joint Research Centre for the year 2000 (FMAP2000) with previously existing maps for the same time period: the CORINE Land Cover 2000 (CLC2000) and the Calibrated European Forest Map 1996 (CEFM1996). The spatial comparison of these three maps was carried out based on forest proportion maps of 1 km derived from the original maps. To characterize differences according to biogeographic regions, two criteria were used: detail of thematic content within each map and local spatial agreement. Concerning thematic content, CLC2000 displayed a surfeit of non-forested areas at the cost of low forest proportions, while FMAP2000 showed a more balanced distribution likely to preserve more detail in forest spatial pattern. Good spatial agreement was found for CLC2000 and FMAP2000 within about 70% of the study area, while only 50% agreement was found when compared with CEFM1996. The largest spatial differences between all maps were found in the Alpine and Mediterranean regions. Reasons for these might be different input data and classification techniques and, in particular, the calibration of CEFM1996 to reported national statistics.

Mapping and assessment of forest ecosystems and their services - Applications and guidance for decision making in the framework of MAES

The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mapping and Assessment of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosytem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2000.

Essential Features of Forest Biodiversity for Assessment Purposes

Forest biodiversity assessments may be based on species or taxon groups, structural traits of forest ecosystems and/or biodiversity indicators derived from these variables. Working Group 3 (WG3) of COST Action E43 initially selected 41 candidate biodiversity variables based on current ecological knowledge. The next step entailed construction and distribution of a questionnaire regarding the importance of the candidate variables for assessing forest biodiversity and their feasibility for assessment by national forest inventories (NFI). Responses were received from 22 countries. Analyses of the responses with respect to importance and feasibility resulted in further selection of 17 biodiversity variables that were then grouped into seven essential biodiversity features: forest categories, forest age, forest structure, deadwood, regeneration, ground vegetation and naturalness. These seven essential features constitute the second level of WG3’s 4-level reference framework: (1) concept, (2) essential feature, (3) indicator, and (4) NFI variable. This chapter addresses in detail the analyses of the questionnaire responses, selection of the 17 biodiversity variables, and derivation of the seven essential forest biodiversity features.

European Forest Types: toward an automated classification

Key messageThe outcome of the present study leads to the application of a spatially explicit rule-based expert system (RBES) algorithm aimed at automatically classifying forest areas according to the European Forest Types (EFT) system of nomenclature at pan-European scale level. With the RBES, the EFT system of nomenclature can be now easily implemented for objective, replicable, and automatic classification of field plots for forest inventories or spatial units (pixels or polygons) for thematic mapping.ContextForest Types classification systems are aimed at stratifying forest habitats. Since 2006, a common scheme for classifying European forests into 14 categories and 78 types (European Forest Types, EFT) exists.AimsThis work presents an innovative method and automated classification system that, in an objective and replicable way, can accurately classify a given forest habitat according to the EFT system of nomenclature.MethodsA rule-based expert system (RBES) was adopted as a transparent approach after comparison with the well-known Random Forest (RF) classification system. The experiment was carried out based on the information acquired in the field in 2010 ICP level I plots in 17 European countries. The accuracy of the automated classification is evaluated by comparison with an independent classification of the ICP plots into EFT carried out during the BioSoil project field survey. Finally, the RBES automated classifier was tested also for a pixel-based classification of a pan-European distribution map of beech-dominated forests.ResultsThe RBES successfully classified 94% of the plots, against a 92% obtained with RF. When applied to the mapped domain, the accuracy obtained with the RBES for the beech forest map classification was equal to 95%.ConclusionThe RBES algorithm successfully automatically classified field plots and map pixels on the basis of the EFT system of nomenclature. The EFT system of nomenclature can be now easily and objectively implemented in operative transnational European forest monitoring programs.

Mapping and assessment of ecosystems and their services indicators for ecosystem assessments under action 5 of the EU biodiversity strategy to 2020: 2nd report - final, February 2014

Environment Europe Direct is a service to help you find answers to your questions about the European Union Summary The second MAES report presents indicators that can be used at European and Member States level to map and assess biodiversity, ecosystem condition and ecosystem services according to the Common International Classification of Ecosystem Services (CICES v4.3). This work is based on a review of data and indicators available at national and European level and is applying the MAES analytical framework adopted in 2013.