Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.     

Do predators control prey species abundance? An experimental test with brown treesnakes on Guam

The effect of predators on the abundance of prey species is a topic of ongoing debate in ecology; the effect of snake predators on their prey has been less debated, as there exists a general consensus that snakes do not negatively influence the abundance of their prey. However, this viewpoint has not been adequately tested. We quantified the effect of brown treesnake (Boiga irregularis) predation on the abundance and size of lizards on Guam by contrasting lizards in two 1-ha treatment plots of secondary forest from which snakes had been removed and excluded vs. two 1-ha control plots in which snakes were monitored but not removed or excluded. We removed resident snakes from the treatment plots with snake traps and hand capture, and snake immigration into these plots was precluded by electrified snake barriers. Lizards were sampled in all plots quarterly for a year following snake elimination in the treatment plots. Following the completion of this experiment, we used total removal sampling to census lizards on a 100-m2 subsample of each plot. Results of systematic lizard population monitoring before and after snake removal suggest that the abundance of the skink, Carlia ailanpalai, increased substantially and the abundance of two species of gekkonids, Lepidodactylus lugubris and Hemidactylus frenatus, also increased on snake-free plots. No treatment effect was observed for the skink Emoia caeruleocauda. Mean snout-vent length of all lizard species only increased following snake removal in the treatment plots. The general increase in prey density and mean size was unexpected in light of the literature consensus that snakes do not control the abundance of their prey species. Our findings show that, at least where alternate predators are lacking, snakes may indeed affect prey populations.     

Using Phylogenetic Diversity Measures to Set Priorities in Conservation: an Example from Southern South America

Abstract: Phylogenetic diversity measures rank areas for biodiversity conservation priorities based on information encoded in phylogenies (cladograms). The goal of these ranks for conservation is to consider as many factors as possible that provide additional taxic information, such as taxa richness, taxa distributional patterns, area endemicity, and complementarity between areas. At present there are many measures that consider phylogenetic information, including node-based, genetic-distance, and feature-based measures. We devised a modified phylogenetic node-based index that we call "taxonomic endemicity standardized weight," which considers not only the taxonomic distinctness of the taxa that inhabit a given area but their endemicity as well. Once the standardized weight of the taxonomic endemicity identifies the area of highest priority, complementarity can be used to identify the second area and so on. We used this node-based index to rank priority areas for conservation in southern South America, and we compared the results of our rankings to results based on other node-based indexes. Our index identified Santiago district, in Central Chile province, as the highest priority area for conservation, followed by Maule, Malvinas, and districts of Subantarctic province. Malvinas exhibits greater complementarity relative to Santiago than Maule does, however, so Malvinas is ranked second in priority. Indexes based on phylogenetic information measure the evolutionary component of biodiversity and allow one to identify areas that will ensure the preservation of evolutionary potential and phylogenetically rare taxa. The modified index we propose is sensitive to taxic distinctness and endemicity as well and allows information from diverse taxa to be combined (i.e., different cladograms). The use of complementarity allows for preservation of the maximum quantity of taxa in a minimal number of protected areas.     

Avian Conservation under the Endangered Species Act: Expenditures versus Recovery Priorities

Abstract: Budget constraints require the U.S. Fish and Wildlife Service to prioritize species for recovery spending. Each listed species is ranked according to the degree of threat it faces, its recovery potential, and its taxonomic distinctness. We analyzed state and federal government expenditures for recovery of threatened and endangered birds ( n = 85 species) from 1992 to 1995 to determine if the priority system was being followed. Although recovery spending correlated with priority rank, priority rank explained <5% of the variation in spending. A small number of the same moderately ranked species dominated expenditures each year (41–79% of total annual budgets). Species with wide distributions, high recovery potential, and captive breeding programs received the most funding, and more funding than their priority ranks dictated. Island species received significantly less funding than expected based on priority rank. Twelve species, 10 of which resided on islands, received <$5000 at least once from 1992 to 1995. Recovery spending was unrelated to degree of threat, taxonomic distinctness, and migratory status. There also was no relationship between land-purchase expenditures and priority ranks. To improve the relationship between recovery spending on threatened and endangered birds and their priority rank, significant changes need to be made within the private sector ( less litigation and special-interest lobbying  ), U.S. Congress (increased budget and reduced earmarking  ), and the U.S. Fish and Wildlife Service (restructuring of regional offices and increased accountability).     

Modeling the brown bear population in Slovenia: A tool in the conservation management of a threatened species

In this paper, we address three aspects of the brown bear population in Slovenia: its size (and its evolution over time), its spatial expansion out of the core area, and its potential habitat based on natural habitat suitability. Data collected through measurement/observation of the bear population and from the literature are used. A model is developed for each aspect. The results are estimates of population size, a picture of the spatial expansion of the population and maps of its optimal and maximal potential habitat (based on natural suitability). Overall, the brown bear population has been increasing since the establishment of a core protective area and has been expanding outside this area. The habitat suitability maps show that there is room for further expansion. Based on habitat suitability and bear population density, as well as human activity and current damage reports, we recommend that the Alps should be temporarily kept free of the bears, until the necessary mitigation measures regarding human–bear conflicts are carried out. On the other hand it is of crucial importance to adapt human activities and improve bear management in the optimal habitat, with which the goals of successful conservation of the species might be achieved.     

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard‐to‐detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts’ assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural‐appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best‐performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola.     

Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios.

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.     

Bayesian Decision Analysis for Evaluating Management Options to Promote Recovery of a Depleted Salmon Population

Abstract:  The endangered population of sockeye salmon (Oncorhynchus nerka) in Cultus Lake, British Columbia, Canada, migrates through commercial fishing areas along with other, much more abundant sockeye salmon populations, but it is not feasible to selectively harvest only the latter, abundant populations. This situation creates controversial trade-offs between recovery actions and economic revenue. We conducted a Bayesian decision analysis to evaluate options for recovery of Cultus Lake sockeye salmon. We used a stochastic population model that included 2 sources of uncertainty that are often omitted from such analyses: structural uncertainty in the magnitude of a potential Allee effect and implementation uncertainty (the deviation between targets and actual outcomes of management actions). Numerous state-dependent, time-independent management actions meet recovery objectives. These actions prescribe limitations on commercial harvest rates as a function of abundance of Cultus Lake sockeye salmon. We also quantified how much reduction in economic value of commercial harvests of the more abundant sockeye salmon populations would be expected for a given increase in the probability of recovery of the Cultus population. Such results illustrate how Bayesian decision analysis can rank options for dealing with conservation risks and can help inform trade-off discussions among decision makers and among groups that have competing objectives.     

Impacts of phylogenetic nomenclature on the efficacy of the U.S. Endangered Species Act

Cataloging biodiversity is critical to conservation efforts because accurate taxonomy is often a precondition for protection under laws designed for species conservation, such as the U.S. Endangered Species Act (ESA). Traditional nomenclatural codes governing the taxonomic process have recently come under scrutiny because taxon names are more closely linked to hierarchical ranks than to the taxa themselves. A new approach to naming biological groups, called phylogenetic nomenclature (PN), explicitly names taxa by defining their names in terms of ancestry and descent. PN has the potential to increase nomenclatural stability and decrease confusion induced by the rank‐based codes. But proponents of PN have struggled with whether species and infraspecific taxa should be governed by the same rules as other taxa or should have special rules. Some proponents advocate the wholesale abandonment of rank labels (including species); this could have consequences for the implementation of taxon‐based conservation legislation. I examined the principles of PN as embodied in the PhyloCode (an alternative to traditional rank‐based nomenclature that names biological groups based on the results of phylogenetic analyses and does not associate taxa with ranks) and assessed how this novel approach to naming taxa might affect the implementation of species‐based legislation by providing a case study of the ESA. The latest version of the PhyloCode relies on the traditional rank‐based codes to name species and infraspecific taxa; thus, little will change regarding the main targets of the ESA because they will retain rank labels. For this reason, and because knowledge of evolutionary relationships is of greater importance than nomenclatural procedures for initial protection of endangered taxa under the ESA, I conclude that PN under the PhyloCode will have little impact on implementation of the ESA. Impactos de la Nomenclatura Filogenética sobre la Eficiencia del Acta Estadunidense para las Especies en Peligro     

Evaluating tributary restoration potential for Pacific salmon recovery.

Although habitat restoration can play a key role in the conservation of imperiled species, for animals that demonstrate long migrations and complex life histories, reliance on physical restoration of isolated habitat patches comes with considerable uncertainty. Nevertheless, within freshwater ecosystems, stream restoration has become a major conservation focus, with millions of dollars spent annually on efforts aimed at recovering degraded habitat and imperiled riverine species. Within this context, we addressed fundamental uncertainties of the focus on tributary restoration for recovery of salmon: (1) Is there potential for improving habitat in tributaries? (2) What magnitude of early survival improvement can be expected based on stream restoration? and (3) Will incremental increases in early survival be sufficient to ensure viability overall? We combined simple mechanistic habitat models, population viability measures, and categorical filters to quantify "restoration potential," expressed as increased total life-cycle survival in response to restored tributary condition, across 32 populations composing five major population groups (MPG). A wide gap remains between how much survival improvement is needed vs. what is likely to occur; restoration potential meets the necessary minimum increase needed for only four populations within one MPG. The remaining populations (84%, 4 MPG) still fall far below the survival increase needed for future viability. In addition, across all populations and groups, a 171% increase (on average) in total life-cycle survival is needed; only approximately 106% appears possible. A recovery strategy for these salmon that relies largely on tributary restoration to mitigate for known mortality imposed at other life stages (e.g., migration through hydropower dams) is risky with a low probability of success. We demonstrate an approach for completing an a priori evaluation of restoration potential linked to population viability, such that habitat restoration efforts can be biologically prioritized and scarce resources can be allocated to efforts with the greatest potential and the least amount of risk, in terms of meeting conservation and recovery goals.     

A roadmap for ladybird conservation and recovery

Ladybirds (Coleoptera: Coccinellidae) provide services that are critical to food production, and they fulfill an ecological role as a food source for predators. The richness, abundance, and distribution of ladybirds, however, are compromised by many anthropogenic threats. Meanwhile, a lack of knowledge of the conservation status of most species and the factors driving their population dynamics hinders the development and implementation of conservation strategies for ladybirds. We conducted a review of the literature on the ecology, diversity, and conservation of ladybirds to identify their key ecological threats. Ladybird populations are most affected by climate factors, landscape composition, and biological invasions. We suggest mitigating actions for ladybird conservation and recovery. Short-term actions include citizen science programs and education, protective measures for habitat recovery and threatened species, prevention of the introduction of non-native species, and the maintenance and restoration of natural areas and landscape heterogeneity. Mid-term actions involve the analysis of data from monitoring programs and insect collections to disentangle the effect of different threats to ladybird populations, understand habitat use by taxa on which there is limited knowledge, and quantify temporal trends of abundance, diversity, and biomass along a management-intensity gradient. Long-term actions include the development of a worldwide monitoring program based on standardized sampling to fill data gaps, increase explanatory power, streamline analyses, and facilitate global collaborations.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Method of estimating the standing stock of Trochus niloticus incorporating Landsat satellite data,with application to the trochus resources of the Bourke Isles,Torres Strait,Australia

The habitat of Trochus niloticus in the Bourke Isles, Torres Strait, was classified into areas of a Landsat image, using high-ratio values of green (Band 2) to red (Band 3) light, along the windward reef margins. These shallow-water (< 15 m) areas have a coral and rubble/algal pavement cover, which constitutes the optimal habitat for this gastropod. The habitat was sampled to estimate the abundance of T. niloticus. The proportion of commercial-sized individuals was estimated by measuring the basal width of all individuals in a sample. A multistage sample design incorporating three spatial scales -100 m² (transect), 1500 m² (site) and 1 km² (reef) — was used to provide variance estimates for sample-design optimisation and to provide data on the spatial variation of abundance. Most variation (68%) in abundance was within reefs and was attributable to differences in reef cover. Variations in abundance and time costs for sampling 2 and 4 m transects were compared; the 2 m transect was more efficient than the 4 m transect. The abundance estimates were combined with habitat-area estimates and the proportion of commerical-sized individuals was estimated at a standing stock of 186000 (24% precision), or 14 t of commerical-sized T. niloticus.     

Eliciting expert knowledge in conservation science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

Ecological implications of the presence of the tube-building polychaete <Emphasis Type="Italic">Lanice conchilega</Emphasis> on soft-bottom benthic ecosystems

The common tube-building polychaete Lanice conchilega is known as a habitat structuring species and can form dense aggregations. The effects of L. conchilega on the surrounding benthic community have received little attention, especially in subtidal areas. Therefore, the presence of L. conchilega in different habitats in the North Sea and its effect on the abundance, species richness, diversity and community structure in these habitats are evaluated in the present paper, based on data from the ICES North Sea Benthos Survey of 2000. Lanice conchilega has a wide geographical distribution and a low habitat specialization, but optimally occurs in shallow fine sands. In the present study, the presence of L. conchilega resulted in a density increase and a significant (positive) correlation of the benthos density with the density of L. conchilega. Furthermore, the species richness (number of species) increased with increasing density of L. conchilega. This trend was, however, not consistent: the number of species reached more or less an asymptotic value or even decreased after reaching a critical density of L. conchilega (>500–1,000 ind/m2), as observed in shallow fine sands. The same overall pattern was detected concerning the expected number of species. The N ₁-diversity index showed similar or slightly higher values in L. conchilega patches compared to patches without L. conchilega. From the results of the community analysis, it can be concluded that the species, which were responsible for the increase of the diversity, belonged to the overall species-pool of that habitat. The effects on density and diversity differed between the four discerned habitats (shallow muddy sand, shallow fine sand, shallow medium sand and deep fine sand), and were most pronounced in shallow fine sands. These patterns can be attributed to the habitat structuring capacity of L. conchilega. The mechanisms responsible for the increase of the habitat quality in patches of L. conchilega can be summarized as (1) changes in the hydrodynamics, (2) increases of the habitat stability and oxygen supply, and (3) a creation of habitat heterogeneity in a uniform environment. In this way, L. conchilega alters the habitat characteristics and affects other organisms, and can therefore even be considered as an ecosystem engineer. In other words, L. conchilega patches are responsible for an increased habitat quality in an otherwise uniform habitat, which results in a higher survival of the surrounding benthic species.     

Habitat Loss and Changes in the Species-Area Relationship

Abstract: The species-area relationship (SAR) has been used successfully to predict extinction from extent of habitat reduction. These extinction estimates assume that species have uniformly distributed range requirements and a minimum abundance level required for persistence; how many species are lost depends solely on how much habitat is removed, not on where it is removed. We consider another limiting case in which range requirements, rather than abundances, determine extinctions. We used a new method for constructing SARs based on assumptions about geographic ranges of species. Our results show that habitat destruction can change the SAR and consequently the number of species predicted to be lost due to habitat destruction. Our method generates SARs that vary in shape according to the specific distributions of geographic range and occupancy but that have the common feature of being described by a power law with an exponent of <1. When the geographic range of species was included in the SAR, the way habitat was lost became important. Although the SAR before habitat destruction is often used to predict species loss after habitat destruction, assumptions must be clearly stated. To predict the damage caused by habitat loss with our model, it is necessary to know the fraction of aggregated species, the distribution of geographic ranges, the form of habitat destruction, and the sampling protocol. The remaining theoretical challenge is to develop a full theory that links abundance and range.     

Comparing wildlife habitat suitability models based on expert opinion with camera trap detections

Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.