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Tytuł pozycji:

Different definitions of species presence to refine estimates of local species richness

Tytuł :
Different definitions of species presence to refine estimates of local species richness
Autorzy :
Ruete, Alejandro
Pärt, Tomas
Berg, Åke
Knape, Jonas
Arlt, Debora
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Wydawca :
PeerJ, 2017.
Rok publikacji :
2017
Język :
English
DOI :
10.7287/peerj.preprints.3077v1
Numer akcesji :
edsair.issn21679843..80584468eda55b6e00455c6be56388ee
Aim To improve predictions of spatial and temporal patterns of species richness it is important to consider how species presence at a site is defined. This is because this definition affects our estimate of species richness, which should be aligned with the aims of the study, e.g. estimating richness of the breeding community. Here we explore the sensitivity of species richness estimates to criteria for defining presence of species (e.g. in relation to number of days present during the breeding season) at 107 wetlands. Innovation We use opportunistic citizen science data of high density (a total of 151,817 observations of 77 wetland bird species; i.e. about 16 observations per day) to build site-occupancy models calculating occupancy probabilities at a high temporal resolution (e.g. daily occupancies) to derive probabilistic estimates of seasonal site use of each species. We introduce a new way for defining species presence by using different criteria related to the number of days the species are required to be present at local sites. We compared patterns of species richness when using these different criteria of species inclusions. Main conclusion While estimates of local species richness derived from high temporal resolution occupancy models are robust to observational bias, these estimates are sensitive to restrictions concerning the number of days of presence required during the breeding season. Unlike complete local species lists, summaries of seasonal site use and different presence criteria allow identifying differences between sites and amplifying the variability in species richness among sites. Thus, this approach allows filtering out species according to their phenology and migration behaviour (e.g. passer-by species) and could improve the explanatory power of environmental variables on predictive models.

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