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Species Data (species + data)
Selected AbstractsMonitoring International Wildlife Trade with Coded Species DataCONSERVATION BIOLOGY, Issue 1 2008Article first published online: 1 FEB 200 First page of article [source] Effects of species and habitat positional errors on the performance and interpretation of species distribution modelsDIVERSITY AND DISTRIBUTIONS, Issue 4 2009Patrick E. Osborne Abstract Aim, A key assumption in species distribution modelling is that both species and environmental data layers contain no positional errors, yet this will rarely be true. This study assesses the effect of introduced positional errors on the performance and interpretation of species distribution models. Location, Baixo Alentejo region of Portugal. Methods, Data on steppe bird occurrence were collected using a random stratified sampling design on a 1-km2 pixel grid. Environmental data were sourced from satellite imagery and digital maps. Error was deliberately introduced into the species data as shifts in a random direction of 0,1, 2,3, 4,5 and 0,5 pixels. Whole habitat layers were shifted by 1 pixel to cause mis-registration, and the cumulative effect of one to three shifted layers investigated. Distribution models were built for three species using three algorithms with three replicates. Test models were compared with controls without errors. Results, Positional errors in the species data led to a drop in model performance (larger errors having larger effects , typically up to 10% drop in area under the curve on average), although not enough for models to be rejected. Model interpretation was more severely affected with inconsistencies in the contributing variables. Errors in the habitat layers had similar although lesser effects. Main conclusions, Models with species positional errors are hard to detect, often statistically good, ecologically plausible and useful for prediction, but interpreting them is dangerous. Mis-registered habitat layers produce smaller effects probably because shifting entire layers does not break down the correlation structure to the same extent as random shifts in individual species observations. Spatial autocorrelation in the habitat layers may protect against species positional errors to some extent but the relationship is complex and requires further work. The key recommendation must be that positional errors should be minimised through careful field design and data processing. [source] Site scores and conditional biplots in canonical correspondence analysisENVIRONMETRICS, Issue 1 2004Jan Graffelman Abstract Canonical correspondence analysis is an important multivariate technique in community ecology. It produces an interesting biplot that summarizes the data matrices involved in the analysis. The method produces two sets of site scores that can be used in a biplot. One set concerns site scores that are weighted averages of the species scores (WA scores), and the other set represents site scores that are linear combinations of the environmental variables (LC scores). We show that the use of both sets of scores in a CCA biplot can be justified. The use of the WA scores leads to the best possible representation of the species data conditional on the representation of the weighted averages. Likewise, the LC scores lead to the best possible representation of the environmental variables, also conditional on the representation of the weighted averages and on the use of a Mahalanobis metric. The eigenvalues obtained in CCA indicate how well the species data are represented when LC scores are used. The quality of representation of the species data when WA scores are used can be computed from the CCA eigenvalues and the variances of the WA scores. Scalar products between WA scores and environmental variable vectors do not form a biplot of the environmental data. Theoretical results are illustrated with Australian data from freshwater ecology. Copyright © 2003 John Wiley & Sons, Ltd. [source] ASSESSING CURRENT ADAPTATION AND PHYLOGENETIC INERTIA AS EXPLANATIONS OF TRAIT EVOLUTION:THE NEED FOR CONTROLLED COMPARISONSEVOLUTION, Issue 10 2005Thomas F. Hansen Abstract The determination of whether the pattern of trait evolution observed in a comparative analysis of species data is due to adaptation to current environments, to phylogenetic inertia, or to both of these forces requires that one control for the effects of either force when making an assessment of the evolutionary role of the other. Orzack and Sober (2001) developed the method of controlled comparisons to make such assessments; their implementation of the method focussed on a discretely varying trait. Here, we show that the method of controlled comparisons can be viewed as a meta-method, which can be implemented in many ways. We discuss which recent methods for the comparative analysis of continuously distributed traits can generate controlled comparisons and can thereby be used to properly assess whether current adaptation and/or phylogenetic inertia have influenced a trait's evolution. The implementation of controlled comparisons is illustrated by an analysis of sex-ratio data for fig wasps. This analysis suggests that current adaptation and phylogenetic inertia influence this trait. [source] Using habitat distribution models to evaluate large-scale landscape priorities for spatially dynamic speciesJOURNAL OF APPLIED ECOLOGY, Issue 1 2008Regan Early Summary 1Large-scale conservation planning requires the identification of priority areas in which species have a high likelihood of long-term persistence. This typically requires high spatial resolution data on species and their habitat. Such data are rarely available at a large geographical scale, so distribution modelling is often required to identify the locations of priority areas. However, distribution modelling may be difficult when a species is either not recorded, or not present, at many of the locations that are actually suitable for it. This is an inherent problem for species that exhibit metapopulation dynamics. 2Rather than basing species distribution models on species locations, we investigated the consequences of predicting the distribution of suitable habitat, and thus inferring species presence/absence. We used habitat surveys to define a vegetation category which is suitable for a threatened species that has spatially dynamic populations (the butterfly Euphydryas aurinia), and used this as the response variable in distribution models. Thus, we developed a practical strategy to obtain high resolution (1 ha) large scale conservation solutions for E. aurinia in Wales, UK. 3Habitat-based distribution models had high discriminatory power. They could generalize over a large spatial extent and on average predicted 86% of the current distribution of E. aurinia in Wales. Models based on species locations had lower discriminatory power and were poorer at generalizing throughout Wales. 4Surfaces depicting the connectivity of each grid cell were calculated for the predicted distribution of E. aurinia habitat. Connectivity surfaces provided a distance-weighted measure of the concentration of habitat in the surrounding landscape, and helped identify areas where the persistence of E. aurinia populations is expected to be highest. These identified successfully known areas of high conservation priority for E. aurinia. These connectivity surfaces allow conservation planning to take into account long-term spatial population dynamics, which would be impossible without being able to predict the species' distribution over a large spatial extent. 5Synthesis and applications. Where species location data are unsuitable for building high resolution predictive habitat distribution models, habitat data of sufficient quality can be easier to collect. We show that they can perform as well as or better than species data as a response variable. When coupled with a technique to translate distribution model predictions into landscape priority (such as connectivity calculations), we believe this approach will be a powerful tool for large-scale conservation planning. [source] Predicting habitat distribution and frequency from plant species co-occurrence dataJOURNAL OF BIOGEOGRAPHY, Issue 6 2007Christine Römermann Abstract Aim, Species frequency data have been widely used in nature conservation to aid management decisions. To determine species frequencies, information on habitat occurrence is important: a species with a low frequency is not necessarily rare if it occupies all suitable habitats. Often, information on habitat distribution is available for small geographic areas only. We aim to predict grid-based habitat occurrence from grid-based plant species distribution data in a meso-scale analysis. Location, The study was carried out over two spatial extents: Germany and Bavaria. Methods, Two simple models were set up to examine the number of characteristic plant species needed per grid cell to predict the occurrence of four selected habitats (species data from FlorKart, http://www.floraweb.de). Both models were calibrated in Bavaria using available information on habitat distribution, validated for other federal states, and applied to Germany. First, a spatially explicit regression model (generalized linear model (GLM) with assumed binomial error distribution of response variable) was obtained. Second, a spatially independent optimization model was derived that estimated species numbers without using spatial information on habitat distribution. Finally, an additional uncalibrated model was derived that calculated the frequencies of 24 habitats. It was validated using NATURA2000 habitat maps. Results, Using the Bavarian models it was possible to predict habitat distribution and frequency from the co-occurrence of habitat-specific species per grid cell. As the model validations for other German federal states were successful, the models were applied to all of Germany, and habitat distribution and frequencies could be retrieved for the national scale on the basis of habitat-specific species co-occurrences per grid cell. Using the third, uncalibrated model, which includes species distribution data only, it was possible to predict the frequencies of 24 habitats based on the co-occurrence of 24% of formation-specific species per grid cell. Predicted habitat frequencies deduced from this third model were strongly related to frequencies of NATURA2000 habitat maps. Main conclusions, It was concluded that it is possible to deduce habitat distributions and frequencies from the co-occurrence of habitat-specific species. For areas partly covered by habitat mappings, calibrated models can be developed and extrapolated to larger areas. If information on habitat distribution is completely lacking, uncalibrated models can still be applied, providing coarse information on habitat frequencies. Predicted habitat distributions and frequencies can be used as a tool in nature conservation, for example as correction factors for species frequencies, as long as the species of interest is not included in the model set-up. [source] The inselberg flora of Atlantic Central Africa.JOURNAL OF BIOGEOGRAPHY, Issue 4 2005Abstract Aims, To identify the relative contributions of environmental determinism, dispersal limitation and historical factors in the spatial structure of the floristic data of inselbergs at the local and regional scales, and to test if the extent of species spatial aggregation is related to dispersal abilities. Location, Rain forest inselbergs of Equatorial Guinea, northern Gabon and southern Cameroon (western central Africa). Methods, We use phytosociological relevés and herbarium collections obtained from 27 inselbergs using a stratified sampling scheme considering six plant formations. Data analysis focused on Rubiaceae, Orchidaceae, Melastomataceae, Poaceae, Commelinaceae, Acanthaceae, Begoniaceae and Pteridophytes. Data were investigated using ordination methods (detrended correspondence analysis, DCA; canonical correspondence analysis, CCA), Sřrensen's coefficient of similarity and spatial autocorrelation statistics. Comparisons were made at the local and regional scales using ordinations of life-form spectra and ordinations of species data. Results, At the local scale, the forest-inselberg ecotone is the main gradient structuring the floristic data. At the regional scale, this is still the main gradient in the ordination of life-form spectra, but other factors become predominant in analyses of species assemblages. CCA identified three environmental variables explaining a significant part of the variation in floristic data. Spatial autocorrelation analyses showed that both the flora and the environmental factors are spatially autocorrelated: the similarity of species compositions within plant formations decreasing approximately linearly with the logarithm of the spatial distance. The extent of species distribution was correlated with their a priori dispersal abilities as assessed by their diaspore types. Main conclusions, At a local scale, species composition is best explained by a continuous cline of edaphic conditions along the forest-inselberg ecotone, generating a wide array of ecological niches. At a regional scale, these ecological niches are occupied by different species depending on the available local species pool. These subregional species pools probably result from varying environmental conditions, dispersal limitation and the history of past vegetation changes due to climatic fluctuations. [source] The ED strategy: how species-level surrogates indicate general biodiversity patterns through an ,environmental diversity' perspectiveJOURNAL OF BIOGEOGRAPHY, Issue 8 2004D. P. Faith Abstract Biodiversity assessment requires that we use surrogate information in practice to indicate more general biodiversity patterns. ,ED' refers to a surrogates framework that can link species data and environmental information based on a robust relationship of compositional dissimilarities to ordinations that indicate underlying environmental variation. In an example analysis of species and environmental data from Panama, the environmental and spatial variables that correlate with an hybrid multi-dimensional scaling ordination were able to explain 83% of the variation in the corresponding Bray Curtis dissimilarities. The assumptions of ED also provide the rationale for its use of p-median optimization criteria to measure biodiversity patterns among sites in a region. M.B. Araújo, P.J. Densham & P.H. Williams (2004, Journal of Biogeography31, 1) have re-named ED as ,AD' in their evaluation of the surrogacy value of ED based on European species data. Because lessons from previous work on ED options consequently may have been neglected, we use a corroboration framework to investigate the evidence and ,background knowledge' presented in their evaluations of ED. Investigations focus on the possibility that their weak corroboration of ED surrogacy (non-significance of target species recovery relative to a null model) may be a consequence of Araújo et al.'s use of particular evidence and randomizations. We illustrate how their use of discrete ED, and not the recommended continuous ED, may have produced unnecessarily poor species recovery values. Further, possible poor optimization of their MDS ordinations, due to small numbers of simulations and/or low resolution of stress values appears to have provided a possible poor basis for ED application and, consequently, may have unnecessarily favoured non-corroboration results. Consideration of Araújo et al.'s randomizations suggests that acknowledged sampling biases in the European data have not only artefactually promoted the non-significance of ED recovery values, but also artefactually elevated the significance of competing species surrogates recovery values. We conclude that little credence should be given to the comparisons of ED and species-based complementarity sets presented in M.B. Araújo, P.J. Densham & P.H. Williams (2004, Journal of Biogeography31, 1), unless the factors outlined here can be analysed for their effects on results. We discuss the lessons concerning surrogates evaluation emerging from our investigations, calling for better provision in such studies of the background information that can allow (i) critical examination of evidence (both at the initial corroboration and re-evaluation stages), and (ii) greater synthesis of lessons about the pitfalls of different forms of evidence in different contexts. [source] Life history, ecology and longevity in batsAGING CELL, Issue 2 2002Gerald S. Wilkinson Summary The evolutionary theory of aging predicts that life span should decrease in response to the amount of mortality caused by extrinsic sources. Using this prediction, we selected six life history and ecological factors to use in a comparative analysis of longevity among 64 bat species. On average, the maximum recorded life span of a bat is 3.5 times greater than a non-flying placental mammal of similar size. Records of individuals surviving more than 30 years in the wild now exist for five species. Univariate and multivariate analyses of species data, as well as of phylogenetically independent contrasts obtained using a supertree of Chiroptera, reveal that bat life span significantly increases with hibernation, body mass and occasional cave use, but decreases with reproductive rate and is not influenced by diet, colony size or the source of the record. These results are largely consistent with extrinsic mortality risk acting as a determinant of bat longevity. Nevertheless, the strong association between life span and both reproductive rate and hibernation also suggests that bat longevity is strongly influenced by seasonal allocation of non-renewable resources to reproduction. We speculate that hibernation may provide a natural example of caloric restriction, which is known to increase longevity in other mammals. [source] Can the cause of aggregation be inferred from species distributions?OIKOS, Issue 1 2007Astrid J.A. Van Teeffelen Species distributions often show an aggregated pattern, which can be due to a number of endo- and exogenous factors. While autologistic models have been used for modelling such data with statistical rigour, little emphasis has been put on disentangling potential causes of aggregation. In this paper we ask whether it is possible to infer sources of aggregation in species distributions from a single set of occurrence data by comparing the performance of various autologistic models. We create simulated data sets, which show similar occupancy patterns, but differ in the process that causes the aggregation. We model the distribution of these data with various autologistic models, and show how the relative performance of the models is sensitive to the factor causing aggregation in the data. This information can be used when modelling real species data, where causes of aggregation are typically unknown. To illustrate, we use our approach to assess the potential causes of aggregation in data of seven bird species with contrasting statistical patterns. Our findings have important implications for conservation, as understanding the mechanisms that drive population fluctuations in space and time is critical for the development of effective management actions for long-term conservation. [source] Identification of a spatially efficient portfolio of priority conservation sites in marine and estuarine areas of FloridaAQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 4 2009Laura Geselbracht Abstract 1.A systematic conservation planning approach using benthic habitat and imperilled species data along with the site prioritization algorithm, MARXAN, was used to identify a spatially efficient portfolio of marine and estuarine sites around Florida with high biodiversity value. 2.Ensuring the persistence of an adequate geographic representation of conservation targets in a particular area is a key goal of conservation. In this context, development and testing of different approaches to spatially-explicit marine conservation planning remains an important priority. 3.This detailed case study serves as a test of existing approaches while also demonstrating some novel ways in which current methods can be tailored to fit the complexities of marine planning. 4.The paper reports on investigations of the influence of varying several algorithm inputs on resulting portfolio scenarios including the conservation targets (species observations, habitat distribution, etc.) included, conservation target goals, and socio-economic factors. 5.This study concluded that engaging stakeholders in the development of a site prioritization framework is a valuable strategy for identifying broadly accepted selection criteria; universal target representation approaches are more expedient to use as algorithm inputs, but may fall short in capturing the impact of historic exploitation patterns for some conservation targets; socio-economic factors are best considered subsequent to the identification of priority conservation sites when biodiversity value is the primary driver of site selection; and the influence of surrogate targets on portfolio selection should be thoroughly investigated to ensure unintended effects are avoided. 6.The priority sites identified in this analysis can be used to guide allocation of limited conservation and management resources. Copyright © 2008 John Wiley & Sons, Ltd. [source] The use of volunteers for conducting sponge biodiversity assessments and monitoring using a morphological approach on Indo-Pacific coral reefsAQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 2 2007James J. Bell Abstract 1.Sponges are an important component of coral reef ecosystems, but even though they are widespread with the ability to significantly influence other benthic community members they rarely feature to any great extent in current monitoring or biodiversity assessment programmes conducted by volunteer and professional groups. This exclusion is usually because of the taxonomic problems associated with sponge identification. 2.A potential alternative to monitoring temporal or spatial change in sponge assemblages and assessing biodiversity levels is to characterize sponges using morphologies present rather than collecting species data. Quantifying sponge biodiversity (for monitoring and biodiversity assessments) at the morphological level is less time and resource consuming than collecting species data and more suited to groups with little training and experience of sponge taxonomy or in regions where detailed taxonomic information on sponges is sparse. 3.This paper considers whether the same differences and similarities in sponge richness and assemblage composition can be identified using species and morphological data in response to environmental gradients at two coral reef ecosystems in south-east Sulawesi, Indonesia, and whether volunteers can be used to reliably collect morphological information. Sponge morphologies were classified into 14 groups and different morphological assemblages were found by the author at the two sites and between depth intervals. Comparisons of sponge species and morphological composition data showed that common patterns in assemblage structuring and richness could be identified irrespective of whether morphological or species data were used. In addition, a positive linear relationship was found between sponge species and morphological richness. 4.The morphological data recorded by volunteer divers (n=10) were compared with that collected by the author. Although volunteers recorded fewer sponges than the author (approximately 15% less), missing mainly small encrusting specimens, similar assemblage structure could be identified from both the volunteers' and the author's data. 5.The results showed that the same differences in sponge assemblages between sites and depths could be identified from both species and morphological data. In addition, these morphological data could be reliably collected by volunteer divers. Copyright © 2006 John Wiley & Sons, Ltd. [source] | ||||||||||