A Nonparametric Lower Bound for the Number of Species Shared by Multiple Communities

In biological and ecological statistical inference, it is practically useful to provide a lower bound for species richness in a community. Chao (1984, 1989) derived a nonparametric lower bound for species richness in a single community. However, there have been no lower bounds proposed in the literature for the number of species shared by multiple communities. Based on sample species abundance or replicated incidence records from each of the N communities, we derive in this article a nonparametric approach to constructing a lower bound for the number of species shared by N (N ≥ 2) communities. The approach is valid for all types of species abundance distributions (for abundance data) or species detection probabilities (for replicated incidence data). Variance estimators for the proposed lower bounds are obtained by using typical asymptotic theory. Simulation results are reported to examine the performance of the lower bounds. Replicated incidence data of ciliate species collected in three areas from Namibia, southwest Africa, are used for illustration. We also briefly discuss the application of the proposed method to estimate the size of a shared population (i.e., the number of individuals in the intersection of multiple populations) based on capture-recapture data from each population.

Social information and community dynamics: nontarget effects from simulating social cues for management

Artificially creating social stimuli may be an effective tool for facilitating settlement by rare and/or declining species into suitable habitat. However, the potential consequences for other community members have not been explored and should be considered when evaluating the overall utility of using such management strategies. I report on nontarget, community-wide effects that occurred when manipulating social cues of two competitors that are species of concern in the western United States, the dominant Least Flycatcher (Empidonax minimus) and the subordinate American Redstart (Setophaga ruticilla). The experiment consisted of surveying birds during a pretreatment year, which allows for the control of baseline communities, and a treatment year, in which treatments were applied just prior to settlement by migratory birds. Treatments included broadcasting songs of flycatchers and redstarts and were compared to controls. While the addition of redstart cues did not significantly influence community structure, the addition of flycatcher cues reduced species richness of migratory birds by approximately 30%. This pattern was driven by an absence of local colonizations of small-bodied migrants to sites with added flycatcher cues, rather than by local extinctions occurring from manipulations. The artificial flycatcher stimuli were more responsible for declines in species richness than were changes in actual flycatcher densities. I conclude by identifying some fundamental issues that managers and conservation practitioners should weigh when considering simulating social cues for species conservation prior to implementation.

Human impacts on regional avian diversity and abundance

Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co-occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model-selection analysis with relative abundance of each native species as the response and then asked whether natural-history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model-averaged predictions among a confidence set of candidate models. Eighty-three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Natural-history traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem-stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land-cover gradient indicates that an intermediate-disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover.

When are historical data sufficient for making watershed-level stream fish management and conservation decisions?

Addressing landscape-level threats to stream fishes such as habitat and hydrological alterations requires adequate watershed-level species inventories. Where watershed-level ichthyofaunal surveys are prohibitively expensive, existing (historical) data sources may provide an option for compiling species lists. However, it is critical that managers consider potential biases or limitations of species lists compiled from existing data. Here we assess the suitability of species lists compiled from existing data sources for making watershed-level fish management and conservation decisions. For nine Great Lakes watersheds, we developed existing species lists by compiling all available federal and state agency and museum fish survey data. We then compared the size and species composition of existing species lists to current species lists compiled from intensive field surveys, conducted in 2002, of the same watersheds. Species lists compiled from commonly available existing data sources, such as state and federal agency and museum data, missed many species detected during our 2002 field surveys. In most watersheds, more than 10 species were missed (range 5-21) on existing lists. Sampling over multiple years and seasons increased the size of both current (field) and existing species lists. Existing species lists compiled from surveys conducted over multiple years and seasons included an average of 15 species not captured during the 2002 field surveys. However, such multiyear existing datasets are rare and not available for many watersheds. In addition, species lists compiled from older existing surveys (e.g., before 1984) did not accurately represent current species composition of the watersheds and our results indicate several apparent misidentifications or errors on these lists. Lastly, while most game species were detected on existing lists, migratory species and recently introduced species were commonly missed on these lists. We conclude with recommendations for using existing data for watershed-level stream fish management and conservation decisions.

Effects of sample standardization on mean species detectabilities and estimates of relative differences in species richness among assemblages

Ecological surveys provide the basic information needed to estimate differences in species richness among assemblages. Comparable estimates of the differences in richness between assemblages require equal mean species detectabilities across assemblages. However, mean species detectabilities are often unknown, typically low, and potentially different from one assemblage to another. As a result, inferences regarding differences in species richness among assemblages can be biased. We evaluated how well three methods used to produce comparable estimates of species richness achieved equal mean species detectabilities across diverse assemblages: rarefaction, statistical estimators, and standardization of sampling effort on mean taxonomic similarity among replicate samples (MRS). We used simulated assemblages to mimic a wide range of species-occurrence distributions and species richness to compare the performance of these three methods. Inferences regarding differences in species richness based on rarefaction were highly biased when richness estimates were compared among assemblages with distinctly different species-occurrence distributions. Statistical estimators only marginally reduced this bias. Standardization on MRS yielded the most comparable estimates of differences in species richness. These findings have important implications for our understanding of species-richness patterns, inferences drawn from biological monitoring data, and planning for biodiversity conservation.

A BAYESIAN STATE-SPACE FORMULATION OF DYNAMIC OCCUPANCY MODELS

Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by non-detection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and WinBUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site-specific heterogeneity in model parameters. The results indicate relatively low turnover and a stable distribution of Cerulean Warblers which is in contrast to analyses of counts of individuals from the same survey that indicate important declines. This discrepancy illustrates the inertia in occupancy relative to actual abundance. Furthermore, the model reveals a declining patch survival probability, and increasing turnover, toward the edge of the range of the species, which is consistent with metapopulation perspectives on the genesis of range edges. Given detection/non-detection data, dynamic occupancy models as described here have considerable potential for the study of distributions and range dynamics.

Functional homogenization effect of urbanization on bird communities

We studied the community richness and dynamics of birds in landscapes recently affected by urbanization to test the prediction that biotic communities living in degraded landscapes are increasingly composed of generalist species. We analyzed bird communities in 657 plots monitored by the French Breeding Bird Survey from 2001 to 2005, accounting for the probability of species detection and spatial autocorrelation. We used an independent land-cover program to assess urbanization intensity in each FBBS plot, from 1992 to 2002. We found that urbanization induced community homogenization and that populations of specialist species became increasingly unstable with increasing urbanization of the landscape. Our results emphasize that urbanization has a substantial impact on the spatial component of communities and highlight the destabilizing effect of urbanization on communities over time. These results illustrate that urbanization may be a strong driving force in functional community composition and that measuring community homogenization is a powerful tool in the assessment of the effects of landscape changes and thus aides sustainable urban planning.

Toward ecologically explicit null models of nestedness

A community is "nested" when species assemblages in less rich sites form nonrandom subsets of those at richer sites. Conventional null models used to test for statistically nonrandom nestedness are under- or over-restrictive because they do not sufficiently isolate ecological processes of interest, which hinders ecological inference. We propose a class of null models that are ecologically explicit and interpretable. Expected values of species richness and incidence, rather than observed values, are used to create random presence-absence matrices for hypothesis testing. In our examples, based on six datasets, expected values were derived either by using an individually based random placement model or by fitting empirical models to richness data as a function of environmental covariates. We describe an algorithm for constructing unbiased null matrices, which permitted valid testing of our null models. Our approach avoids the problem of building too much structure into the null model, and enabled us to explicitly test whether observed communities were more nested than would be expected for a system structured solely by species-abundance and species-area or similar relationships. We argue that this test or similar tests are better determinants of whether a system is truly nested; a nested system should contain unique pattern not already predicted by more fundamental ecological principles such as species-area relationships. Most species assemblages we studied were not nested under these null models. Our results suggest that nestedness, beyond that which is explained by passive sampling processes, may not be as widespread as currently believed. These findings may help to improve the utility of nestedness as an ecological concept and conservation tool.

Determinants of local extinction and turnover rates in urban bird communities

Studying the effects of urbanization on the dynamics of communities has become a priority for biodiversity conservation. The consequences of urbanization are mainly an increased fragmentation of the original landscapes associated with a decrease in the amount of favorable habitats and an increased pressure of human activities on the remaining patches suitable for wildlife. Patterns of bird species richness have been studied at different levels of urbanization, but little is known about the temporal dynamics of animal communities in urban landscapes. In particular, urbanization is expected to have stronger negative effects on migratory breeding bird communities than on sedentary ones, which should lead to different patterns of change in composition. Using an estimation method accounting for heterogeneity in species detection probability and data collected between 2001 and 2003 within a suburban area near the city of Paris, France, we tested whether these communities differ in their local extinction and turnover rates. We considered the potential effects of patch size and distance to Paris' center as a measure of the degree of urbanization around the patches. As expected, local rates of extinction and turnover were higher for migratory than for sedentary species, and they were negatively related to patch size for migratory species. Mean species richness of the sedentary species increased during the study period and their local turnover rate was negatively related to the distance to the urban core, showing a trend to colonize the most urban patches. These results highlight the very dynamic nature of the composition of some local bird communities in fragmented habitats and help to identify factors affecting colonization and extinction.

Estimating species richness and accumulation by modeling species occurrence and detectability

A statistical model is developed for estimating species richness and accumulation by formulating these community-level attributes as functions of model-based estimators of species occurrence while accounting for imperfect detection of individual species. The model requires a sampling protocol wherein repeated observations are made at a collection of sample locations selected to be representative of the community. This temporal replication provides the data needed to resolve the ambiguity between species absence and nondetection when species are unobserved at sample locations. Estimates of species richness and accumulation are computed for two communities, an avian community and a butterfly community. Our model-based estimates suggest that detection failures in many bird species were attributed to low rates of occurrence, as opposed to simply low rates of detection. We estimate that the avian community contains a substantial number of uncommon species and that species richness greatly exceeds the number of species actually observed in the sample. In fact, predictions of species accumulation suggest that even doubling the number of sample locations would not have revealed all of the species in the community. In contrast, our analysis of the butterfly community suggests that many species are relatively common and that the estimated richness of species in the community is nearly equal to the number of species actually detected in the sample. Our predictions of species accumulation suggest that the number of sample locations actually used in the butterfly survey could have been cut in half and the asymptotic richness of species still would have been attained. Our approach of developing occurrence-based summaries of communities while allowing for imperfect detection of species is broadly applicable and should prove useful in the design and analysis of surveys of biodiversity.

Bayesian Estimation of Species Richness from Quadrat Sampling Data in the Presence of Prior Information

We consider the problem of estimating the number of species of an animal community. It is assumed that it is possible to draw up a list of species liable to be present in this community. Data are collected from quadrat sampling. Models considered in this article separate the assumptions related to the experimental protocol and those related to the spatial distribution of species in the quadrats. Our parameterization enables us to incorporate prior information on the presence, detectability, and spatial density of species. Moreover, we elaborate procedures to build the prior distributions on these parameters from information furnished by external data. A simulation study is carried out to examine the influence of different priors on the performances of our estimator. We illustrate our approach by estimating the number of nesting bird species in a forest.

A 16-year study of forest disturbance and understory bird community structure and composition in Tanzania

I compared understory bird community structure and composition among primary, slightly disturbed, and moderately disturbed forest in the East Usambara Mountains in Tanzania. Comparisons were conducted at two spatiotemporal scales: short term, conducted in 1999 and 2000, in which treatments (disturbance levels) were replicated, and long term, conducted from 1989-2004 along the same disturbance gradient of a subset of the short-term sites. I used capture-recapture models to assess the probability of detection and estimate species richness and population growth rates. The probability of detection of species did not vary significantly among disturbance levels but did vary significantly among species. Over the short- and long-term surveys, estimated species richness did not vary significantly among disturbance levels. Temporal variability in estimated species richness and the relative abundance of guilds did vary significantly among disturbance levels yet was contingent on survey length. The coefficient of variation in species richness over the short-term survey was <5% across all disturbance levels, whereas over the long-term survey it was 35% in slightly disturbed forest, 11% in moderately disturbed forest, and 0% in primary forest. In the short-term survey, zero of seven feeding guilds varied significantly in relative abundance among disturbance levels, whereas over the long-term survey four of seven (57%) feeding guilds did so. Terrestrial insectivores were most adversely affected by forest disturbance. Population growth rates (lamda) between 1989 and 2004 for the more common species of terrestrial insectivores did not vary significantly among disturbance levels and for these species were significantly < or = 1.00, indicating the recovery time for terrestrial insectivores in slightly and moderately disturbed forest is very long. These results illustrate the importance of long-term studies in assessing ecological impacts of forest disturbance and the importance of protecting primary forest in the Eastern Arc Mountains.

Monitoring coyote population dynamics by genotyping faeces

Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single population estimates. We evaluated the use of faecal genotyping as a tool for monitoring long-term population dynamics, using coyotes (Canis latrans) in the Alaska Range as a case study. We obtained 544 genotypes from 56 coyotes over 3 years (2000-2002). Tissue samples from all 15 radio-collared coyotes in our study area had > or = 1 matching faecal genotypes. We used flexible maximum-likelihood models to study coyote population dynamics, and we tested model performance against radio telemetry data. The staple prey of coyotes, snowshoe hares (Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold with a 1(1/2)-year time lag. Survival rates declined the year after hares crashed but recovered the following year. We conclude that long-term monitoring of elusive species using faecal genotyping is feasible and can provide data that are useful for wildlife conservation and management. We highlight some drawbacks of standard open-population models, such as low precision and the requirement of discrete sampling intervals, and we suggest that the development of open models designed for continuously collected data would enhance the utility of faecal genotyping as a monitoring tool.

A method for estimating wildlife detection probabilities in relation to home-range use: insights from a field study on the common brushtail possum (Trichosurus vulpecula)

Using field data from brushtail possums (Trichosurus vulpecula), we present a method for modelling wildlife detection probabilities. Whereas detection functions typically (e.g. for distance sampling) describe the probability of direct human observations of animal subjects, we adapted this approach for cryptic species where observation depends on animals being caught in traps. Specifically, we characterised the probability of individual brushtail possums being caught by leg-hold traps in an area of farmland and native forest in New Zealand. Detection probability was defined as the per-individual, per-trap, per-night probability of a possum being captured, and was modelled as a function of home-range utilisation. Radio-telemetry was used to define the home-range distributions of 18 possums, and a combination of scanning radio-receivers and movement-activated video-cameras recorded instances when radio-collared possums encountered and stepped on the trigger of leg-hold traps (inactivated by being wired open). We estimated a 5% chance of trapping individual possums with a single leg-hold trap located in the centre of their home range for one night (median value across possums). Furthermore, this probability decreased rapidly as a function of distance, so that at 120 m from the centre of the home range there was less than a 1% chance of trapping success per possum per night. The techniques developed in this study could be applied to a wide variety of species and sampling methods.

The relationship between species detection probability and local extinction probability

In community-level ecological studies, generally not all species present in sampled areas are detected. Many authors have proposed the use of estimation methods that allow detection probabilities that are <1 and that are heterogeneous among species. These methods can also be used to estimate community-dynamic parameters such as species local extinction probability and turnover rates (Nichols et al. Ecol Appl 8:1213-1225; Conserv Biol 12:1390-1398). Here, we present an ad hoc approach to estimating community-level vital rates in the presence of joint heterogeneity of detection probabilities and vital rates. The method consists of partitioning the number of species into two groups using the detection frequencies and then estimating vital rates (e.g., local extinction probabilities) for each group. Estimators from each group are combined in a weighted estimator of vital rates that accounts for the effect of heterogeneity. Using data from the North American Breeding Bird Survey, we computed such estimates and tested the hypothesis that detection probabilities and local extinction probabilities were negatively related. Our analyses support the hypothesis that species detection probability covaries negatively with local probability of extinction and turnover rates. A simulation study was conducted to assess the performance of vital parameter estimators as well as other estimators relevant to questions about heterogeneity, such as coefficient of variation of detection probabilities and proportion of species in each group. Both the weighted estimator suggested in this paper and the original unweighted estimator for local extinction probability performed fairly well and provided no basis for preferring one to the other.