In the European Union (EU), there is an urgent need to define a specific and standardized monitoring strategy for Habitat Directive (HD) forest habitats, like Quercus suber woodlands (EU habitat 9330). Such forests are an important component of western Mediterranean landscapes. In Italy, they are undergoing a relevant regression due to the decline of traditional management. Here, we tested the effectiveness of the Cumulative Abundance Profile (CAP) method in assessing the conservation status (CS) of habitat 9330 in central Italy. The CAP method compares plant communities based on their structure and species composition. Our aims were: i) to test the effectiveness of structure and species composition of the tree layer as predictors of different understories and forest habitat types; ii) to compare the results obtained using the CAP method with those deriving from traditional cover-based (CB) vegetation classification; iii) to evaluate the advantages and limitations of using the two methods to assess the CS of EU forest habitats. The similarity between 48 sampling plots was assessed analysing data through the Fuzzy C-Means clustering method. The three groups resulting from the analysis of CAP data corresponded to as many different community types, each highlighting a different CS of the habitat 9330. For the CAP-based groups, the Mantel test showed a significant correlation between the overstory and the understory composition. Besides, the indicator species analysis detected significantly distinct understories in the three groups, and hypsometric curves suggested that each one is related to soils with different fertility. The CB classification (cover data of all species) produced three clusters, too. However, according to the Adjusted Rand index, the agreement between the two classifications was low. When woods have a higher compositional and structural diversity, in CB classification many plots remain unexplained from an ecological, floristic, and conservation point of view. Compositional data, even if essential, resulted insufficient to classify and monitor the CS of highly structurally complex forest habitats. This highlights that the role of structural data in the classification and monitoring of HD forests is underrated, since they resulted to be an important proxy for forest monitoring and management. The CAP procedure could thus represent a viable standardized methodology to assess the CS of forest habitats, together with the analysis of the understory composition. Further studies applying the CAP method in other woody habitats might support the inclusion of this methodology in the guidelines for EU Habitats monitoring.

Angiolini, C., Foggi, B., Sarmati, S., Gabellini, A., Gennai, M., Castagnini, P., et al. (2021). Assessing the conservation status of EU forest habitats: The case of Quercus suber woodlands. FOREST ECOLOGY AND MANAGEMENT, 496 [10.1016/j.foreco.2021.119432].

Assessing the conservation status of EU forest habitats: The case of Quercus suber woodlands

Angiolini C.;Sarmati S.
;
Fanfarillo E.;Maccherini S.
2021-01-01

Abstract

In the European Union (EU), there is an urgent need to define a specific and standardized monitoring strategy for Habitat Directive (HD) forest habitats, like Quercus suber woodlands (EU habitat 9330). Such forests are an important component of western Mediterranean landscapes. In Italy, they are undergoing a relevant regression due to the decline of traditional management. Here, we tested the effectiveness of the Cumulative Abundance Profile (CAP) method in assessing the conservation status (CS) of habitat 9330 in central Italy. The CAP method compares plant communities based on their structure and species composition. Our aims were: i) to test the effectiveness of structure and species composition of the tree layer as predictors of different understories and forest habitat types; ii) to compare the results obtained using the CAP method with those deriving from traditional cover-based (CB) vegetation classification; iii) to evaluate the advantages and limitations of using the two methods to assess the CS of EU forest habitats. The similarity between 48 sampling plots was assessed analysing data through the Fuzzy C-Means clustering method. The three groups resulting from the analysis of CAP data corresponded to as many different community types, each highlighting a different CS of the habitat 9330. For the CAP-based groups, the Mantel test showed a significant correlation between the overstory and the understory composition. Besides, the indicator species analysis detected significantly distinct understories in the three groups, and hypsometric curves suggested that each one is related to soils with different fertility. The CB classification (cover data of all species) produced three clusters, too. However, according to the Adjusted Rand index, the agreement between the two classifications was low. When woods have a higher compositional and structural diversity, in CB classification many plots remain unexplained from an ecological, floristic, and conservation point of view. Compositional data, even if essential, resulted insufficient to classify and monitor the CS of highly structurally complex forest habitats. This highlights that the role of structural data in the classification and monitoring of HD forests is underrated, since they resulted to be an important proxy for forest monitoring and management. The CAP procedure could thus represent a viable standardized methodology to assess the CS of forest habitats, together with the analysis of the understory composition. Further studies applying the CAP method in other woody habitats might support the inclusion of this methodology in the guidelines for EU Habitats monitoring.
Angiolini, C., Foggi, B., Sarmati, S., Gabellini, A., Gennai, M., Castagnini, P., et al. (2021). Assessing the conservation status of EU forest habitats: The case of Quercus suber woodlands. FOREST ECOLOGY AND MANAGEMENT, 496 [10.1016/j.foreco.2021.119432].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1163810