Evaluating a vegetation-recovery plan in Mediterranean alpine ski slopes: A chronosequence-based study in Sierra Nevada (SE Spain)
ABSTRACT In this paper, we assess the results found in the restoration of vegetation on ski runs in the Mediterranean high mountain, contrasting different issues widely used for evaluating recovery plans, such as cover, richness, diversity, growth, and qualitative species composition, with the aim of establishing their relative validity as well as finding a straightforward model to assess the success of the restoration of degraded areas. Ski runs were selected in Sierra Nevada ski station (SE Spain) in which hydroseeding was performed from 2002 to 2005. The sampling design was based on a chronosequence approach, using natural areas established as ‘models’ (i.e. target for long-term restoration) to evaluate the restoration success based on the similarity to the model. Although parameters such as growth, cover, and even richness or diversity reached similar values to the ones in the model areas after 4 years (i.e. natural perennial mountain pastures), other indicators such as composition, measured in a qualitative way as the ratio of colonizing species to total species, showed different occurrence values for the most abundant species. Moreover, when the whole pool of species was taken into account using discriminant analysis, the results differed, showing that although the process performed well, the recovery (sensu stricto) requires longer periods than the duration assessed to be fully successful. The results showed that common parameters, such as growth, cover, richness, or diversity, when used solely may lead to misinterpretation, and therefore additional methods to compare composition, such as the discriminant analysis, are strongly recommended.
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ABSTRACT: When evaluating the success or failure of ecological restoration projects, practitioners need to verify success within the first few years of the monitoring process to apply corrective measures if necessary or to reclaim environmental down payment where required. This could be achieved with ecological indicators, if they can be easily and routinely measured and are representative of the complexity of the restored ecosystems. We used peatlands restored after horticultural peat extraction in eastern Canada to test a methodological approach that predicts restoration success early after restoration implementation. The goal of restoration of these extracted peatlands is to re-establish a moss carpet typically dominated by Sphagnum mosses, the main peat-accumulating plant group in these northern ecosystems. Vegetation in a total of 152 plots in 41 peatlands restored after peat extraction activities and distributed across a span of 600 km was monitored every 2 years since the third year after restoration. The plots were clustered in three restoration outcome categories: Sphagnum-dominated, bare peat-dominated and Polytrichum-dominated, according to their characteristic vegetation composition at the time of the latest survey for each plot (4–11 years since restoration). Second, vegetation composition in the same plots from the earliest survey, 3 years since restoration, and key environmental and management variables such as summer temperature, effectiveness of ditch blockage, season of restoration works and delay in P fertilization were analyzed using linear discriminant analysis (LDA) to obtain the combination of parameters that best discriminated between the restoration outcome categories. LDA correctly classified 71% of the plots of a calibration database (for which 75% of the sectors were used) and 75% of a validation database (for which 25% of the sectors were used) into the three categories. The obtained LDA models can be used to allocate new plots to one of the restoration outcome categories by providing a series of linear equations (classification functions) that are computed from the combination of ecological indicators. One additional and recently restored peatland was used to illustrate application of these equations of the LDA model to predict future restoration outcome and subsequently adapt management strategies. Such a LDA model provides an unequivocal (i.e., one new plot assigned to one and only one restoration outcome category) prediction of success based on multiple but simple, easily recognizable indicators and spares managers the complex task of interpreting many individual predictors for establishing a clear diagnosis.Ecological Indicators 11/2014; 46:156–166. DOI:10.1016/j.ecolind.2014.06.016 · 3.23 Impact Factor
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ABSTRACT: Sierra Nevada is a protected mountain in the Iberian Peninsula classified as a Biosphere Reserve (1986), Natural Park (1989) and National Park (1999). All these environmental protection programmers are a consequence of its unique landscape in the context of the mid-latitude semiarid mountains, with enclaves of exceptional scientific and cultural value. Thanks to its high altitude, Sierra Nevada held the southernmost Quaternary glaciers in Europe, as well as it happened during the Little Ice Age. In turn, Sierra Nevada is also singular thanks to its vast cultural heritage, since very early societies settled on its slopes and valleys and accommodate their lifestyles and economy to the characteristics of this mountain environment. Currently, Sierra Nevada has become an important tourist centre and receives a large amount of visitors. This process of change has conditioned the implementation of a different economic model: it brings benefits to the populations but it involves changes in the landscape as well, sometimes questionable. From this perspective, a critical revision of the legislation is required balancing the sustainable economic development of the population and the preservation and safeguarding of the heritage values of the landscape. With this goal, we suggest creating and implementing the Sites of Geomorphological Interest.Applied Geography 08/2013; 42:227-239. DOI:10.1016/j.apgeog.2013.02.006 · 3.08 Impact Factor
Conference Paper: Predicting success in restored bogs shortly after restoration works[Show abstract] [Hide abstract]
ABSTRACT: Background/Question/Methods Bog exploitation for horticultural purposes leaves large surfaces of residual peat that remain devoid of vegetation for decades. Restoration of those bogs is necessary to mitigate the loss of local biodiversity. However, tools to assess the success of restoration works have not been rigorously defined yet. We used vacuum-milled peat extracted bogs restored by the moss transfer technique in Eastern Canada as a model system to test an approach for assessing restoration success, based on plant composition. A total of 188 plots in 12 restored bogs that had been restored from 4 to 11 years ago and continuously monitored were clustered in three success categories, according to their characteristic vegetation composition. Then, vegetation composition in the plots was analyzed retrospectively at the third year since restoration to obtain the combination of indicator species that best discriminated between the success categories using linear discriminant analysis (LDA). Results/Conclusions LDA classified correctly 86% of the cases into three success categories: a first one representing Successful restoration, with dominance of Sphagnum, a typical bog genus that is able to initiate self-regulatory mechanisms leading back to bog ecosystems (restoration goal); a second one representing Failure, with dominance of bare peat; and a third category, interpreted as a dead-ended successional pathway, dominated by Polytrichum strictum, a pioneer moss that usually facilitates Sphagnum colonization. Recently restored bogs were finally used to illustrate the use of our predictive tool and suggest different management strategies.98th ESA Annual Convention 2013; 08/2013