Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.     

Marinbiologische Aspekte der Wasserbewegung

The importance of water movement as an ecological factor in littoral areas and open oceans is frequently badly underestimated. Water movement may exert biological effects comparable to those of light and temperature. Without water movement, all marine life would cease to exist. In this papar water movement is taken to embrace all motions which may occur in oceanic and coastal waters, e.g. currents, tides, horizontal and vertical water exchanges. The primary driving forces creating oceanic water movements are: gravity, earth rotation, atmospheric dynamics, and sun radiation. Until recently, water movements have largely, or exclusively, been studied by physical oceanographers; biological aspects of water movements have only lately begun to attract the attention of biologists. The results obtained so far make it quite clear that approaches and terminology employed by physical oceanographers require modification in order to meet the needs of marine biologists. The biological consequences of water movements are particularly complex, since moving water serves as transportation medium for other environmental factors such as temperature, salinity, food, etc. At the same time, some of these factors affect, in turn, speed and direction of the moving water. In addition, speed and intensity of water movements may be differentiated due to the variety of sources which cause or modify them. Various examples are presented to illustrate the complexity of water movement and its effects on biological systems. The intensity values of water movement may vary over an extremely wide range (13 degrees of magnitude).     

A Markov random field spatio-temporal analysis of ocean temperature

The National Oceanic Data Center (NODC) contains historical records from approximately 144,000 hydrographic stations in the North Atlantic. This data has been used by oceanographers to construct maps of point estimates of pressure, temperature, salinity and oxygen in the North Atlantic (Levitus (1994); Lozier et al. (1995)). Because data from any particular year are scarce, the previous maps have been for time-averaged values only. In addition, the maps have been reported without uncertainty estimates. This paper presents a Markov random field (MRF) analysis that can generate maps for specific time periods along with associated uncertainties. To estimate changes in oceanic properties over time previous oceanographic work has focused on differences between a few time periods each having many observations. Due to data scarcity this poses a severe restriction for both spatial and temporal coverage of climatic change. The MRF analysis provides a means for temporal modeling that does not require high data density at each time period. To demonstrate the usefulness of a MRF analysis of oceanic data we investigate the temporal variability along 24.5°N in the North Atlantic. Our results are compared to an earlier analysis (Parrilla et al. (1994)) where data from only three time periods was used. We obtain a more thorough understanding of the temperature change found by this previous study.     

Incorporating Climate and Ocean Change into Extinction Risk Assessments for 82 Coral Species

Many marine invertebrate species facing potential extinction have uncertain taxonomies and poorly known demographic and ecological traits. Uncertainties are compounded when potential extinction drivers are climate and ocean changes whose effects on even widespread and abundant species are only partially understood. The U.S. Endangered Species Act mandates conservation management decisions founded on the extinction risk to species based on the best available science at the time of consideration—requiring prompt action rather than awaiting better information. We developed an expert‐opinion threat‐based approach that entails a structured voting system to assess extinction risk from climate and ocean changes and other threats to 82 coral species for which population status and threat response information was limited. Such methods are urgently needed because constrained budgets and manpower will continue to hinder the availability of desired data for many potentially vulnerable marine species. Significant species‐specific information gaps and uncertainties precluded quantitative assessments of habitat loss or population declines and necessitated increased reliance on demographic characteristics and threat vulnerabilities at genus or family levels. Adapting some methods (e.g., a structured voting system) used during other assessments and developing some new approaches (e.g., integrated assessment of threats and demographic characteristics), we rated the importance of threats contributing to coral extinction risk and assessed those threats against population status and trend information to evaluate each species’ extinction risk over the 21st century. This qualitative assessment resulted in a ranking with an uncertainty range for each species according to their estimated likelihood of extinction. We offer guidance on approaches for future biological extinction risk assessments, especially in cases of data‐limited species likely to be affected by global‐scale threats. Incorporación del Cambio Climático y Oceánico en Estudios de Riesgo de Extinción para 82 Especies de Coral     

Towards improved socio-economic assessments of ocean acidification’s impacts

Ocean acidification is increasingly recognized as a component of global change that could have a wide range of impacts on marine organisms, the ecosystems they live in, and the goods and services they provide humankind. Assessment of these potential socio-economic impacts requires integrated efforts between biologists, chemists, oceanographers, economists and social scientists. But because ocean acidification is a new research area, significant knowledge gaps are preventing economists from estimating its welfare impacts. For instance, economic data on the impact of ocean acidification on significant markets such as fisheries, aquaculture and tourism are very limited (if not non-existent), and non-market valuation studies on this topic are not yet available. Our paper summarizes the current understanding of future OA impacts and sets out what further information is required for economists to assess socio-economic impacts of ocean acidification. Our aim is to provide clear directions for multidisciplinary collaborative research.     

Complex call in male rock hyrax (<Emphasis Type="Italic">Procavia capensis</Emphasis>): a multi-information distributing channel

Chemicals such as those used for scent marking, or visual cues such as color badges, can transmit information pertaining to different aspects of individual, group and species recognition and attributes. Here, we show that complex acoustic cues, such as calls also have the capacity for such information transfer. Although songs are usually attributed to birds, rock hyraxes (Procavia capensis) engage in a rich and complex vocalizing behavior that we term ‘singing’. Previous studies on various species have shown that a specific vocalization can closely reflect a specific attribute. Using a series of multiple regressions, we show that a single complex vocalization by the adult male rock hyrax closely reflects numerous individual traits, possibly encoding various types of biologically important information (multiple-messages hypothesis). Our study reveals that hyrax songs provide accurate information regarding body weight, size and condition, social status and hormonal state of the singer. We also show that these independent data are sent in a sequential manner, a pattern that probably allows a better partition of the messages embedded in the song. Our results imply that animals, through complex individual vocalizations, can potentially advertise multiple individual attributes in the same manner as that produced by chemical scent marking. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Integrated Monitoring and Information Systems for Managing Aquatic Invasive Species in a Changing Climate

Abstract:  Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.     

Integrating Biological and Social Values When Prioritizing Places for Biodiversity Conservation

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species’ distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. Integración de Valores Biológicos y Sociales al Priorizar Sitios para la Conservación de la Biodiversidad     

A nonparametric procedure for analyzing repeated measures of spatially correlated data

Many agricultural, biological, and environmental studies involve detecting temporal changes of a response variable, based on data observed at sampling sites in a spatial region and repeatedly over several time points. That is, data are repeated measures over time and are potentially correlated across space. The traditional repeated-measures analysis allows for time dependence but assumes that the observations at different sampling sites are mutually independent, which may not be suitable for field data that are correlated across space. In this paper, a nonparametric large-sample inference procedure is developed to assess the time effects while accounting for the spatial dependence using a block bootstrap. For illustration, the methodology is applied to describe the population changes of root-lesion nematodes over time in a production field in Wisconsin.     

Dissipation of Tidal Energy and Associated Mixing in a Wide Fjord

This paper sets out to test the hypothesis that vertical mixing due to the dissipation of the internal tide accounts for a significant proportion of the total vertical mixing in a fjordic basin during a period of deep water isolation. During July and August 1999 two locations in the Clyde Sea were instrumented with moored RD Instruments Acoustic Doppler Current Profilers (ADCPs) and conductivity-temperature-pressure chains: Station C2, near the shallow entrance sill (55 m water depth), and station C1 in the deep basin (155 m water depth). A bottom pressure recorder was also deployed at station C3 by the seaward entrance to the Clyde Sea in the North Channel of the Irish Sea. A Free-falling Light Yo-yo shear microstructure profiler (FLY) was used to measure the dissipation rate of turbulent kinetic energy (TKE) throughout the water column over 25 h at both C1 and C2. These were interspersed with two-hourly conductivity-temperature-depth casts at both sites. The observations show agreement between the dissipation rate of TKE estimated by using a microstructure profiler and that estimated from the decay of the internal tide as measured by the two ADCPs. However, to account for all the implied mixing it is necessary to invoke an additional source of buoyancy flux, the most probable candidate mechanism is enhanced internal wave breaking near the sill and at the sloping boundaries of the deep basin. In addition, the vertical eddy diffusivity estimated from the micro-structure profiler (O(0.5 cm² s^–1) indicates that internal tide induced mixing away from any boundaries contributed significantly to the overall level of mixing which is required to account for the observed evolution of the deep basin water properties.     

Improving seabed classification from Multi-Beam Echo Sounder (MBES) backscatter data with visual data mining

Multi-Beam Echo Sounders are often used for classification of seabed type, as there exists a strong link between sonar backscatter and sediment characteristics of the seabed. Most of the methods for seabed classification from MBES backscatter create a highly-dimensional data set of statistical features and then use a combination of Principal Component Analysis and k-means clustering to derive classes. This procedure can be time consuming for contemporary large MBES data sets with millions of records. This paper examines the complexity of one of most commonly used classification approaches and suggests an alternative where feature data set is optimised in terms of dimensionality using computational and visual data mining. Both the original and the optimised method are tested on an MBES backscatter data set and validated against ground truth. The study found that the optimised method improves accuracy of classification and reduced complexity of processing. This is an encouraging result, which shows that bringing together methods from acoustic classification, visual data mining, spatial analysis and remote sensing can support the unprecedented increases in data volumes collected by contemporary acoustic sensors.     

Regional ecotoxicological hazards associated with anthropogenic enrichment of heavy metals

Regional geochemical data of heavy metals are commonly used for environmental risk assessment and management. Often these data are based on so-called total concentrations, whereas the exposure to the mobile or reactive fraction of these elements finally determines whether the exposed ecosystem is at risk and to which extent. The objective of our research was to develop a wider applicable method for quantitative hazard assessment of soil metal contamination attributable to the activity of man, based on and illustrated with data from the Netherlands. Since chemical availability (0.43 M HNO3 extractable concentrations) of Cd, Cu, Pb and Zn appeared strongly related to the estimated anthropogenic enrichment, we used these concentrations to assess the hazard of human-induced enrichment of these metals. We expressed the enrichment hazard using the toxic pressure concept, which estimates the fraction of biological species (varying between 0 and 1) potentially affected due to the level of exposure to single metals or their local mixtures. This is done using logistic (enrichment) concentration/response models parameterized with ecotoxicological effect data from toxicity tests and mixture models. Hazards varied from very low toxic pressures (lower than 0.01) to (most often) toxic pressure less than 0.05, whereby the latter relates to the so-called 95%-protection criterion used in some soil protection legislations. In rare cases, the toxic pressure exceeded the value of 0.05, to an upper limit of 0.054 for Cd. The rank order of metal enrichment hazards suggests that Cd enrichment induces the largest hazard increase. There are limited (rank order) differences in enrichment hazards between soil types. Comparing the judgement of soils based on soil screening levels and based on toxic pressure of anthropogenic Cd, Cu, Pb and Zn enrichments, the soil screening values appear to more conservative. This exemplifies the use of soil screening values as a method to note regulatory concern, but not always indicating an actual hazard or risk. When screening values are exceeded, refined hazard insights can be obtained, as illustrated in this paper. This provides a more refined insight in the ecotoxic implications of human-induced metal enrichments in soils, as refined basis for risk management decisions.     

Forecasting extinction risk with nonstationary matrix models.

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.     

Mate choice plasticity in the field cricket <Emphasis Type="Italic">Teleogryllus oceanicus</Emphasis>: effects of social experience in multiple modalities

Social experience can elicit phenotypically plastic changes in mate choice, but little is known about the degree to which social information from one modality can influence mating decisions based on information from a different modality. I used the field cricket Teleogryllus oceanicus to test whether experience of chemical cues mimicking a high density of sexually mature males causes changes in mate choice based on acoustic signals. T. oceanicus males produce long-range calling songs to attract females for mating, but they also produce waxy, non-volatile hydrocarbons on their cuticle (CHCs) which, when deposited on a substrate, can be detected by females and may provide demographic information. I manipulated female experience of substrate-bound male CHCs and then performed acoustic mate choice trials. When CHCs were present on the substrate during trials, females showed greater motivation to respond to male calling song. This effect diminished with repeated exposure to male songs, demonstrating that the importance of olfactory cues in altering acoustic mate choice decreased with increasing exposure to acoustic signals. However, the temporal nature of CHC experience mattered: previous experience of CHCs did not alter subsequent female choice for male calling song traits. Exposure to male song increased the threshold of mate acceptance over time, and individuals varied considerably in overall levels of responsiveness. Taken together, the results demonstrate that mate choice is dependent on social context mediated by multiple modalities in T. oceanicus, but they do not support the idea that prior experience of social cues in one modality necessarily influences later mating decisions based on other signalling modalities.     

An effective dietary survey framework for the assessment of total dietary arsenic intake in Bangladesh: Part-A—FFQ design

Groundwater contaminated with arsenic (As), when extensively used for irrigation, causes potentially long term detrimental effects to the landscape. Such contamination can also directly affect human health when irrigated crops are primarily used for human consumption. Therefore, a large number of humans are potentially at risk worldwide due to daily As exposure. Numerous previous studies have been severely limited by small sample sizes which are not reliably extrapolated to large populations or landscapes. Human As exposure and risk assessment are no longer simple assessments limited to a few food samples from a small area. The focus of more recent studies has been to perform risk assessment at the landscape level involving the use of biomarkers to identify and quantify appropriate health problems and large surveys of human dietary patterns, supported by analytical testing of food, to quantify exposure. This approach generates large amounts of data from a wide variety of sources and geographic information system (GIS) techniques have been used widely to integrate the various spatial, demographic, social, field, and laboratory measured datasets. With the current worldwide shift in emphasis from qualitative to quantitative risk assessment, it is likely that future research efforts will be directed towards the integration of GIS, statistics, chemistry, and other dynamic models within a common platform to quantify human health risk at the landscape level. In this paper we review the present and likely future trends of human As exposure and GIS application in risk assessment at the landscape level.     

An introduction to flux measurements in difficult conditions

The origins of the aerodynamic techniques now widely used at sites around the world to measure continuous biosphere-atmosphere exchange of carbon and energy are briefly reviewed. A survey of the current state of this approach concludes that the technique often fails when standard analysis routines are applied to data from single towers in complex flows. In the daytime, problems are signaled by failure to close the surface energy balance because turbulent energy fluxes are routinely underestimated. Complex flows are more prevalent at night when they lead to failure to measure all the respired CO2. At such times, the aerodynamic methodology is commonly supplemented by biological models. A set of papers from a workshop on "Flux Measurements in Difficult Conditions" held at the National Center for Atmospheric Research (NCAR) in January 2006 are introduced next. Two papers review the causes and magnitude of these flow-based problems. Four papers describe intensive field experiments that detail the mechanisms that cause problematic complex flows. These experiments show, inter alia, that the technique of replacing nighttime eddy flux measurements by biological models can also be systematically biased. Finally, two model studies are used both to illustrate the physics behind these complex flows and to motivate an approach to systematic correction of single-tower results.     

Sensitivity and Vulnerability in Marine Environments: an Approach to Identifying Vulnerable Marine Areas

Abstract:  Marine environments have suffered from a lack of quantitative methods for delineating areas that are sensitive or vulnerable to particular stresses, natural and anthropogenic. We define sensitivity as the degree to which marine features respond to stresses, which are deviations of environmental conditions beyond the expected range. Vulnerability can then be defined as the probability that a feature will be exposed to a stress to which it is sensitive. Using these definitions, we provide a quantitative methodology for identifying vulnerable marine areas based on valued ecological features, defined as biological or physical features, processes, or structures deemed by humans to have environmental, social, cultural, or economic significance. The vulnerability of the valued ecological features is a function of their sensitivity to particular stresses and their vulnerability to those stresses. We used the methodology to demonstrate how vulnerable marine areas for two groups of endangered whale species (inshore and offshore) could be identified with a predictive habitat model and acoustic stress surfaces. Acoustic stress surfaces were produced for ferry traffic, commercial shipping traffic, potential offshore oil production, and small-boat traffic. The vulnerabilities of the two whale groups to the four stressors considered in this example were relatively similar; however, inshore species were more sensitive to on-shelf, coastal activities such as offshore hydrocarbon production, ferry traffic, and small-boat traffic. Our approach demonstrates how valued features can be associated with stresses and the likelihood of encountering these stresses (vulnerability) in order to identify geographic areas for management and conservation purposes. The method can be applied to any combination of valued ecological features and stressors.     

Conservation Genetics at the Species Boundary

Abstract: Conservation genetics has expanded its purview such that molecular techniques are now used routinely to prioritize populations for listing and protection and infer their historical relationships in addition to addressing more traditional questions of heterozygosity and inbreeding depression. Failure to specify whether molecular data are being used for diagnosis-related questions or for population viability questions, however, can lead either to misinterpretation of character data as adaptive information or to misinterpretation of frequency or distance data as diagnostic or historical information. Each of these misinterpretations will confound conservation programs. The character-based approach to delimiting phylogenetic species is both operationally and logically superior to "diagnostic" methods that involve distance- or frequency-based routines, which are unstable over time. Tree-based criteria for the diagnosis of conservation "units" are also inappropriate because they can depend on patterns inferred without reference to diagnostic characters. Intraspecific studies, conservation-related or otherwise, that adopt terminology and methods designed to infer nested hierarchic relationships confuse diagnosis with historical inferences by treating diagnoses as outcomes rather than as precursors to phylogeny reconstruction. A character-based diagnostic approach recognizes the analytical dichotomy between species hierarchies and population statistics and provides a framework for the understanding of each. No species concept, however, should be viewed as an absolute criterion for protecting populations, but as part of a framework from within which identification of protection and management goals can be achieved effectively and defensibly.     

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

Evaluation of Museum Collection Data for Use in Biodiversity Assessment

Abstract: Natural-history collections in museums contain data critical to decisions in biodiversity conservation. Collectively, these specimen-based data describe the distributions of known taxa in time and space. As the most comprehensive, reliable source of knowledge for most described species, these records are potentially available to answer a wide range of conservation and research questions. Nevertheless, these data have shortcomings, notably geographic gaps, resulting mainly from the ad hoc nature of collecting effort. This problem has been frequently cited but rarely addressed in a systematic manner. We have developed a methodology to evaluate museum collection data, in particular the reliability of distributional data for narrow-range taxa. We included only those taxa for which there were an appropriate number of records, expert verification of identifications, and acceptable locality accuracy. First, we compared the available data for the taxon of interest to the "background data," comprised of records for those organisms likely to be captured by the same methods or by the same collectors as the taxon of interest. The "adequacy"of background sampling effort was assessed through calculation of statistics describing the separation, density, and clustering of points, and through generation of a sampling density contour surface. Geographical information systems (GIS) technology was then used to model predicted distributions of species based on abiotic (e.g., climatic and geological) data. The robustness of these predicted distributions can be tested iteratively or by bootstrapping. Together, these methods provide an objective means to assess the likelihood of the distributions obtained from museum collection records representing true distributions. Potentially, they could be used to evaluate any point data to be collated in species maps, biodiversity assessment, or similar applications requiring distributional information.