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A proposal for a scalable and semantically interoperable family of indices of taxa richness

Daniele de Rigo

edited by: Marta Pérez‐Soba, Maria L. Paracchini

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[...] In this study, we introduce a novel estimate of richness of forest tree genera, based on a harmonised dimensionless family of indices at the continental scale. Each index ranges from 0 (null richness) up to 1 (maximum potential richness) and estimates the richness of tree genera under the assumption of a uniform sampling effort, explicitlydeclared.
Given a category of relevant taxa (here represented by the forest tree taxa for which harmonised pan-European information is available), the family of indicesis designed to cover with variable granularity the description of richness. Considering the forest tree taxa in Europe,the granularity of the index is suitable to be adapted to the specific application. It may potentially range from the aggregatedanalysisofforesttree familiesor genera, uptomore detailed analysis (but potentially subject to a higher uncertainty and share of missing taxa) of forest tree species or sub-species which might also be of interest for assessing genetic diversitywhenever asufficientamountofintraspecificinformationwould become available at the pan-European scale.
For this application aiming at studying the relationship between forest tree taxa-richness and forest management, the modelled granularity is at the genus level. This granularity is able to overcome some regional inconsistencies of national forest inventories at the specieslevel.
For the available forest tree genera for which pan-European information on their distribution (relative probability of presence at 1 km2) is available in the European Atlas of Forest Tree Species [36], different levels of sampling effort have been simulated. Depending on the share of forest cover in a given 1 km2 pixel, a sample randomly selected within the pixel may have a variable probability of observing a treecovered area instead of any other area without trees. With a constant sampling effort (e.g. 10 random samples per each km2), two pixels with the same share of forest cover show a different statistical distribution for the total number of sampled tree taxa, depending on the taxa richness of each pixel. Increased sampling efforts nonlinearly affect the statistical distribution for the total number of sampled tree taxa depending on both the local taxa richness and share of forest cover. The proposed family of indices provides a systematic way for exploring these combined effects, so as to also contribute to assess the role of different patterns of forest taxa abundance [35] in mixed landscapes, very frequent in Europe.

In Database and classification system of different types of Public Goods and Ecosystem Services in relation to farming/forestry systems - PEGASUS Deliverable 2.2 (2016), pp. 79-86 
Key: INRMM:14634881



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