Re-Evaluation of Stand Indicators for the Assessment of the Representativity Status of the Natura 2000 Habitat Type forests/Loodusdirektiivi Metsaelupaikade Esinduslikkusklasse Eristavate Tunnuste Maaratlemisest
Palo, Anneli, Hoder, Dagmar, Liira, Jaan, Estonian Journal of Ecology
INTRODUCTION
Ecological assessment of habitat representativity
International and European environmental organizations are making serious efforts to stop the loss of biodiversity in various habitat types, including forests (European Commission, 1992; CBD, 2006; Oja, 2009). For that purpose, the Natura 2000 Network of important habitats in the EU has been established. The Natura 2000 Standard Data Form for habitat evaluation (European Commission, 1996a, 1996b, 2006) sets terminology and principles for the inventory and monitoring of habitats, including their representativity and conservation status. The major focus in interpretation manuals for fieldworkers is on the description of the habitat and its deductive comparison to a typical example (Airaksinen & Karttunen, 2001; Vicenikova & Polak, 2003; Guth & Kucera, 2005; Aunins, 2010). In the case of Estonia, the comparative description of an old-growth forest is used to determine the habitat's representativity in three- or four-level grade system (Ministry of Environment, 2002; Paal, 2002, 2007; Palo, 2004). This representativity grading system consists of four grades, from grade A (an old-growth forest, historically continuous and without management signs) to D (hardly suits under the definition of a habitat type, but has a potential to develop into one in the future).
The commonly used representativity grading for forest habitats is based on an expert opinion given in the field according to mapping manuals. In theory, the adequate evaluation and monitoring of habitat type forests require the description of various aspects of these habitats, which would provide information about their status. The majority of monitoring and forest inventory methods are based on the evaluation of the number of forest structural elements and the registration of indicator species (Noss, 1990, 1999; Lindenmayer et al., 2000; Korjus, 2002; Andersson et al., 2003; Liira & Kohv, 2004; Brang et al., 2008; Winter et al., 2008; Adermann, 2009; Lamb et al., 2009; Oja, 2009). Informative characteristics are called indicators, but they must be tested for causal correlations, universality of use, power of extrapolation, and robustness for errors in practice, and they must be easy and inexpensive to apply (Liira & Kohv, 2010). There is no single universal indicator trait that would work uniformly in all habitats, and therefore a complex of indicative traits should be considered (Jonsson & Jonsell, 1999; Buchs, 2003; Zenner, 2004; Ranius & Jonsson, 2007; Liira & Kohv, 2010; Lohmus & Kraut, 2010).
Only recently researchers in Estonia have become interested in more specific topics, such as the distinction of old near-natural forests rich in structural elements from managed ones and whether it varies along environmental gradients (Trass et al., 1999; Kohv & Liira, 2005; Liira et al., 2007; Liira & Sepp, 2009; Sepp & Liira, 2009; Liira & Kohv, 2010; Lohmus & Kraut, 2010). Increasingly more attention has been paid to responses of forest species to changes in stands (Vellak & Paal, 1999; Meier et al., 2005; Vellak & Ingerpuu, 2005; Lohmus & Lohmus, 2008; Juriado & Liira, 2009; Meier & Paal, 2009). It is also very important to consider direct and indirect anthropogenic effects (Pikk, 2003; Palo et al., 2004; Remm, 2005; Liira et al., 2007; Kaasik et al., 2008).
The first updates toward standardized methods have been made in the evaluation and monitoring of the Natura 2000 habitat type forests that focus on biological diversity in Estonia (Viilma & Palo, 2008; Adermann, 2009; Liira, 2009). However, in order to ensure methodological adequacy and suggest future improvements in the list of structural indicators, the methods need to be tested in the field for practicality and universality of use in a wide range of habitats.
The goal of our research was to test the effectiveness of widely used forest structural indicators for the characterization of the representativity grade of forests belonging to some most common Natura 2000 habitat types, to compare the conformity of the trait-based approach with the grading given by an expert, and to determine which stand characteristics are non-specific to habitat type. The final task of our study was to develop an optimized forest habitat indicator complex, which should serve as an updated tool for an objective classification of Natura 2000 forests into representativity classes.
METHODS
Study site
Our pilot project was conducted in Ida-Viru County in north-eastern Estonia (Fig. 1). In 2007 the forest land coverage in the county was about 57.7%, compared to the Estonian total of 50.6% (data calculated without the area of Lake Peipsi) (Adermann, 2009). Ida-Viru County includes three landscape regions: the north Estonian coastal lowland, the Viru tableland, and Alutaguse, with a combined territory of 3369 km2 (Arold, 2005). Alutaguse, situated in the central and southern parts of Ida-Viru County, is one of the most untouched and densely forested areas in Estonia. The settlements of Alutaguse were in earlier times concentrated on the banks of the Narva River. Large forest and mire areas remained mostly untouched by human influence until the 18th century; cutting activity increased in the 19th and 20th centuries. Trees were extracted near historically settled regions (areas close to the northern cliff coastline and at Tudu and Avinurme) and in areas easy to reach (the western bank of the Narva River). Large mires with enclosed forest areas were preserved until the first half of the 20th century, when a number of narrow-gauge railways were built for forest extraction, and the drainage of mires intensified. The main changes in the forests of the Alutaguse region began after World War II, when forest stands that had been degraded and burned during the battles were cut again, and very intensive drainage of forest land began (Laasimer, 1965; Saaber, 1996). By today, small former villages have overgrown with forest, and the Alutaguse region is mainly forest land. Many of the Natura 2000 forest habitat patches are situated in this region.
[FIGURE 1 OMITTED]
Data sampling
The most common forest habitat types in Estonia are the western taiga (*9010), Fennoscandian deciduous swamp woods (*9080), and bog woodlands (*91D0) (Adermann, 2009). These three habitat types were selected as our study objects. During the years 2008-2009 we described the forests from each habitat type selecting 75 sites from western taiga, 24 sites from Fennoscandian deciduous swamp woods, and 22 sites from bog woodlands.
First we checked all potential habitat polygons from aerophotos (from the Estonian Land Board Geoportal) and excluded those clear-cut or with obviously intensive management. A circular sample area was positioned in the centre of each habitat polygon. In general, the forest sample plot had a radius of 10 m. The observed continuous characteristics in the sample plot area were transformed into estimates per hectare, and alternatively, all continuous and classification traits were treated as binary (presence/absence). The representativity grading was given by an expert in the field according to mapping manuals (Ministry of Environment, 2002; Viilma & Palo, 2008). Experts used a four-grade system: A--old-growth forests, old or continuously developed stand without forest management signs; B--stand with all typical structural characteristics, mostly old enough or continuously developed, but some management signs are detectable; C--because of earlier forest management, some …
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Publication information:
Article title: Re-Evaluation of Stand Indicators for the Assessment of the Representativity Status of the Natura 2000 Habitat Type forests/Loodusdirektiivi Metsaelupaikade Esinduslikkusklasse Eristavate Tunnuste Maaratlemisest.
Contributors: Palo, Anneli - Author, Hoder, Dagmar - Author, Liira, Jaan - Author.
Journal title: Estonian Journal of Ecology.
Volume: 60.
Issue: 3
Publication date: September 2011.
Page number: 209+.
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