Estimating the richness of species with variable mobility

By U. Brose, Neo D. Martinez. 2004

134 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/959a50356cfc58d1449add71645518d3375289da

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Comparing measures of species diversity from incomplete inventories: an update (2010, methodology): “Sample completeness (CompTRUE) is calculated as Sobs ⁄ STRUE (note the discrepancy of this definition with ‘estimated completeness’ = Sobs ⁄ Sest in the Brose & Martinez (2004); termed ‘coverage’ there) decision framework and some other publications.”
MYCORRHIZAL COMMUNITY DYNAMICS FOLLOWING NITROGEN FERTILIZATION: A CROSS‐SITE TEST IN FIVE GRASSLANDS (2007, background): “Comparative tests have identified these indices as robust estimators of species richness (Colwell and Coddington 1994, Brose and Martinez 2004).”
Montane Andean rain forests are a global diversity hotspot of geometrid moths (2005, background): “For a sample coverage between 86% and 96%, Brose & Martinez (2004) recommended the incidence coverage estimator, which gives an estimate of 1420 species.”
Effects of tropical forest fragmentation on aerial insectivorous bats in a land-bridge island system. (2010, methodology): “We calculated expected species richness, Sest, following the estimator choice framework developed by Brose and Martinez (2004). Based on our observed level of sample coverage we selected the Michaelis–Menten richness estimator as the most suitable estimator for our data.”
Adaptability and vulnerability of high flying Neotropical aerial insectivorous bats to urbanization (2011, methodology): “Based on the iterative estimator choice framework developed by Brose & Martinez (2004) that takes movement heterogeneity of mobile animals, such as bats, into account, we selected the Michaelis– Menten(mean) estimator to estimate species richness.”
How landscape structure, land-use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes (2007, unknown): “As the number of captured individuals can be influenced by activity patterns (for example as a result of weather conditions), we used abundance-based methods that estimate species richness independent of sample size (Brose & Martinez 2004).”
Scaling of Food-Web Properties with Diversity and Complexity Across Ecosystems (2010, background): “, 2009; Woodward and Hildrew, 2001) or if extrapolation methods suggest a high sampling coverage (Brose and Martinez, 2004; Brose et al., 2003).”
Assemblage‐level responses of phyllostomid bats to tropical forest fragmentation: land‐bridge islands as a model system (2008, methodology): “Based on the estimator choice framework developed by Brose & Martinez (2004), which takes movement heterogeneity of mobile animals such as bats into account, we chose the first-order Jackknife (Jack1).”
An elevational shift in butterfly species richness and composition accompanying recent climate change (2007, methodology): “We estimated the proportion of species present that had been recorded, by dividing observed species richness by final extrapolated richness for each estimator, and calculated the mean for the seven measures as a summary estimate of sample coverage (see Brose et al., 2003; Brose & Martinez, 2004).”
Environmental factors affecting bee diversity in urban and remote grassland plots in Boulder, Colorado (2009, background): “These statistics are based on abundance data rather than incidence data and as such are more appropriate for determining species richness of mobile organisms such as insects (Hellman and Fowler 1999; Brose and Martinez 2004).”
Biome transitions as centres of diversity: Habitat heterogeneity and diversity patterns of West African bat assemblages across spatial scales (2011, methodology): “We followed Brose and Martinez (2004) for the choice of the least biased and most precise estimator to extrapolate estimated species richness, Sest.”
An evaluation of camera traps for inventorying large‐ and medium‐sized terrestrial rainforest mammals (2008, unknown): “…for this dataset supports results obtained from simulated data, where the Jackknife estimators performed best when heterogeneity in capture probability due to spatial distribution or movement of animals was introduced to the data (Brose, Martinez & Williams, 2003; Brose & Martinez, 2004).”