Browsing by Autor "Deborah Faria"

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Accounting for detectability improves estimates of species richness in tropical bat surveys
(Wiley, 2011) Christoph F. J. Meyer; Ludmilla Aguiar; Luís F. Aguirre; Júlio Baumgarten; Frank M. Clarke; Jean‐François Cosson; Sergio Estrada Villegas; Jakob Fahr; Deborah Faria; Neil M. Furey
Summary\n\n\n1. Species richness is a state variable of some interest in monitoring programmes but raw species counts are often biased due to imperfect species detectability. Therefore, monitoring programmes should quantify detectability for target taxa to assess whether it varies over temporal or spatial scales. We assessed the potential for tropical bat monitoring programmes to reliably estimate trends in species richness.\n\n\n2. Using data from 25 bat assemblages from the Old and New World tropics, we estimated detectability for all species in an assemblage (mean proportion of species detected per sampling plot) and for individual species (species-specific detectability). We further assessed how these estimates of detectability were affected by external sources of variation relating to time, space, survey effort and biological traits.\n\n\n3. The mean proportion of species detected across 96 sampling plots was estimated at 0·76 (range 0·57–1·00) and was significantly greater for phytophagous than for animalivorous species. Species-averaged detectability for phytophagous species was influenced by the number of surveys and season, whereas the number of surveys and sampling methods [ground- or canopy-level mist nets, harp traps and acoustic sampling (AS)] most strongly affected estimates of detectability for animalivorous bats. Species-specific detectability averaged 0·4 and was highly heterogeneous across 232 species, with estimates ranging from 0·03 to 0·84. Species-level detectability was influenced by a range of external factors such as location, season, or sampling method, suggesting that raw species counts may sometimes be strongly biased.\n\n\n4.Synthesis and applications. Due to generally high species-specific detection probabilities, Neotropical aerial insectivorous bats proved to be well suited for monitoring using AS. However, for species with low detectability, such as most gleaning animalivores or nectarivores, count data obtained in bat monitoring surveys must be corrected for detection bias. Our results indicate that species-averaged detection probabilities will rarely approach 1 unless many surveys are conducted. Consequently, long-term bat monitoring programmes need to adopt an estimation scheme that corrects for variation in detectability when comparing species richness over time and when making regional comparisons. Similar corrections will be needed for other species-rich tropical taxa.
An assessment of the suitability of bats as a possible target taxon for long-term monitoring within the framework of Conservation International’s Tropical Ecology, Assessment and Monitoring (TEAM) Initiative
(Centre National de la Recherche Scientifique, 2009) Christoph F. J. Meyer; Ludmilla Aguiar; Luís F. Aguirre; Júlio Baumgarten; Frank M. Clarke; Jean‐François Cosson; Sergio Estrada Villegas; Jakob Fahr; Deborah Faria; Neil M. Furey
Long-term monitoring of tropical bats for anthropogenic impact assessment: Gauging the statistical power to detect population change
(Elsevier BV, 2010) Christoph F. J. Meyer; Ludmilla Aguiar; Luís F. Aguirre; Júlio Baumgarten; Frank M. Clarke; Jean‐François Cosson; Sergio Estrada Villegas; Jakob Fahr; Deborah Faria; Neil M. Furey
Species undersampling in tropical bat surveys: effects on emerging biodiversity patterns
(Wiley, 2014) Christoph F. J. Meyer; Ludmilla Aguiar; Luís F. Aguirre; Júlio Baumgarten; Frank M. Clarke; Jean‐François Cosson; Sergio Estrada Villegas; Jakob Fahr; Deborah Faria; Neil M. Furey
Undersampling is commonplace in biodiversity surveys of species-rich tropical assemblages in which rare taxa abound, with possible repercussions for our ability to implement surveys and monitoring programmes in a cost-effective way. We investigated the consequences of information loss due to species undersampling (missing subsets of species from the full species pool) in tropical bat surveys for the emerging patterns of species richness (SR) and compositional variation across sites. For 27 bat assemblage data sets from across the tropics, we used correlations between original data sets and subsets with different numbers of species deleted either at random, or according to their rarity in the assemblage, to assess to what extent patterns in SR and composition in data subsets are congruent with those in the initial data set. We then examined to what degree high sample representativeness (r ≥ 0·8) was influenced by biogeographic region, sampling method, sampling effort or structural assemblage characteristics. For SR, correlations between random subsets and original data sets were strong (r ≥ 0·8) with moderate (ca. 20%) species loss. Bias associated with information loss was greater for species composition; on average ca. 90% of species in random subsets had to be retained to adequately capture among-site variation. For nonrandom subsets, removing only the rarest species (on average c. 10% of the full data set) yielded strong correlations (r > 0·95) for both SR and composition. Eliminating greater proportions of rare species resulted in weaker correlations and large variation in the magnitude of observed correlations among data sets. Species subsets that comprised ca. 85% of the original set can be considered reliable surrogates, capable of adequately revealing patterns of SR and temporal or spatial turnover in many tropical bat assemblages. Our analyses thus demonstrate the potential as well as limitations for reducing survey effort and streamlining sampling protocols, and consequently for increasing the cost-effectiveness in tropical bat surveys or monitoring programmes. The dependence of the performance of species subsets on structural assemblage characteristics (total assemblage abundance, proportion of rare species), however, underscores the importance of adaptive monitoring schemes and of establishing surrogate performance on a site by site basis based on pilot surveys.