Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations

Abstract: Species’ assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection–nondetection records) are generated. Within‐season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site‐occupancy models are applied directly to the detection‐history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site‐occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen‐science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.     

An occupancy‐based quantification of the highly imperiled status of desert fishes of the southwestern United States

Desert fishes are some of the most imperiled vertebrates worldwide due to their low economic worth and because they compete with humans for water. An ecological complex of fishes, 2 suckers (Catostomus latipinnis, Catostomus discobolus) and a chub (Gila robusta) (collectively managed as the so‐called three species) are endemic to the U.S. Colorado River Basin, are affected by multiple stressors, and have allegedly declined dramatically. We built a series of occupancy models to determine relationships between trends in occupancy, local extinction, and local colonization rates, identify potential limiting factors, and evaluate the suitability of managing the 3 species collectively. For a historical period (1889–2011), top performing models (AICc) included a positive time trend in local extinction probability and a negative trend in local colonization probability. As flood frequency decreased post‐development local extinction probability increased. By the end of the time series, 47% (95% CI 34‐61) and 15% (95% CI 6‐33) of sites remained occupied by the suckers and the chub, respectively, and models with the 2 species of sucker as one group and the chub as the other performed best. For a contemporary period (2001?2011), top performing (based on AIC_c) models included peak annual discharge. As peak discharge increased, local extinction probability decreased and local colonization probability increased. For the contemporary period, results of models that split all 3 species into separate groups were similar to results of models that combined the 2 suckers but not the chub. Collectively, these results confirmed that declines in these fishes were strongly associated with water development and that relative to their historic distribution all 3 species have declined dramatically. Further, the chub was distinct in that it declined the most dramatically and therefore may need to be managed separately. Our modeling approach may be useful in other situations in which targeted data are sparse and conservation status and best management approach for multiple species are uncertain.     

Examining the relationship between local extinction risk and position in range

Over half of globally threatened animal species have experienced rapid geographic range loss. Identifying the parts of species’ distributions most vulnerable to local extinction would benefit conservation planning. However, previous studies give little consensus on whether ranges decline to the core or edge. We built on previous work by using empirical data to examine the position of recent local extinctions within species’ geographic ranges, address range position as a continuum, and explore the influence of environmental factors. We aggregated point‐locality data for 125 Galliform species from across the Palearctic and Indo‐Malaya into equal‐area half‐degree grid cells and used a multispecies dynamic Bayesian occupancy model to estimate rates of local extinctions. Our model provides a novel approach to identify loss of populations from within species ranges. We investigated the relationship between extinction rates and distance from range edge by examining whether patterns were consistent across biogeographic realm and different categories of land use. In the Palearctic, local extinctions occurred closer to the range edge than range core in both unconverted and human‐dominated landscapes. In Indo‐Malaya, no pattern was found for unconverted landscapes, but in human‐dominated landscapes extinctions tended to occur closer to the core than the edge. Our results suggest that local and regional factors override general spatial patterns of recent local extinction within species’ ranges and highlight the difficulty of predicting the parts of a species’ distribution most vulnerable to threat.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.     

Bird‐community responses to habitat creation in a long‐term,large‐scale natural experiment

Ecosystem function and resilience are compromised when habitats become fragmented due to land‐use change. This has led to national and international conservation strategies aimed at restoring habitat extent and improving functional connectivity (i.e., maintaining dispersal processes). However, biodiversity responses to landscape‐scale habitat creation and the relative importance of spatial and temporal scales are poorly understood, and there is disagreement over which conservation strategies should be prioritized. We used 160 years of historic post‐agricultural woodland creation as a natural experiment to evaluate biodiversity responses to habitat creation in a landscape context. Birds were surveyed in 101 secondary, broadleaf woodlands aged 10–160 years with ≥80% canopy cover and in landscapes with 0‐17% broadleaf woodland cover within 3000 m. We used piecewise structural equation modeling to examine the direct and indirect relationships between bird abundance and diversity, ecological continuity, patch characteristics, and landscape structure and quantified the relative conservation value of local and landscape scales for bird communities. Ecological continuity indirectly affected overall bird abundance and species richness through its effects on stand structure, but had a weaker influence (effect size near 0) on the abundance and diversity of species most closely associated with woodland habitats. This was probably because woodlands were rapidly colonized by woodland generalists in ≤10 years (minimum patch age) but were on average too young (median 50 years) to be colonized by woodland specialists. Local patch characteristics were relatively more important than landscape characteristics for bird communities. Based on our results, biodiversity responses to habitat creation depended on local‐ and landscape‐scale factors that interacted across time and space. We suggest that there is a need for further studies that focus on habitat creation in a landscape context and that knowledge gained from studies of habitat fragmentation and loss should be used to inform habitat creation with caution because the outcomes are not necessarily reciprocal.     

Use of Multispecies Occupancy Models to Evaluate the Response of Bird Communities to Forest Degradation Associated with Logging

Forest degradation is arguably the greatest threat to biodiversity, ecosystem services, and rural livelihoods. Therefore, increasing understanding of how organisms respond to degradation is essential for management and conservation planning. We were motivated by the need for rapid and practical analytical tools to assess the influence of management and degradation on biodiversity and system state in areas subject to rapid environmental change. We compared bird community composition and size in managed (ejido, i.e., communally owned lands) and unmanaged (national park) forests in the Sierra Tarahumara region, Mexico, using multispecies occupancy models and data from a 2‐year breeding bird survey. Unmanaged sites had on average higher species occupancy and richness than managed sites. Most species were present in low numbers as indicated by lower values of detection and occupancy associated with logging‐induced degradation. Less than 10% of species had occupancy probabilities >0.5, and degradation had no positive effects on occupancy. The estimated metacommunity size of 125 exceeded previous estimates for the region, and sites with mature trees and uneven‐aged forest stand characteristics contained the highest species richness. Higher estimation uncertainty and decreases in richness and occupancy for all species, including habitat generalists, were associated with degraded young, even‐aged stands. Our findings show that multispecies occupancy methods provide tractable measures of biodiversity and system state and valuable decision support for landholders and managers. These techniques can be used to rapidly address gaps in biodiversity information, threats to biodiversity, and vulnerabilities of species of interest on a landscape level, even in degraded or fast‐changing environments. Moreover, such tools may be particularly relevant in the assessment of species richness and distribution in a wide array of habitats. Uso de Modelos de Ocupación para Múltiples Especies para Evaluar la Respuesta de las Comunidades de Aves a la Degradación de Bosques Asociada con la Tala     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

Toward quantification of the impact of 21st‐century deforestation on the extinction risk of terrestrial vertebrates

Conservation actions need to be prioritized, often taking into account species’ extinction risk. The International Union for Conservation of Nature (IUCN) Red List provides an accepted, objective framework for the assessment of extinction risk. Assessments based on data collected in the field are the best option, but the field data to base these on are often limited. Information collected through remote sensing can be used in place of field data to inform assessments. Forests are perhaps the best‐studied land‐cover type for use of remote‐sensing data. Using an open‐access 30‐m resolution map of tree cover and its change between 2000 and 2012, we assessed the extent of forest cover and loss within the distributions of 11,186 forest‐dependent amphibians, birds, and mammals worldwide. For 16 species, forest loss resulted in an elevated extinction risk under red‐list criterion A, owing to inferred rapid population declines. This number increased to 23 when data‐deficient species (i.e., those with insufficient information for evaluation) were included. Under red‐list criterion B2, 484 species (855 when data‐deficient species were included) were considered at elevated extinction risk, owing to restricted areas of occupancy resulting from little forest cover remaining within their ranges. The proportion of species of conservation concern would increase by 32.8% for amphibians, 15.1% for birds, and 24.7% for mammals if our suggested uplistings are accepted. Central America, the Northern Andes, Madagascar, the Eastern Arc forests in Africa, and the islands of Southeast Asia are hotspots for these species. Our results illustrate the utility of satellite imagery for global extinction‐risk assessment and measurement of progress toward international environmental agreement targets.     

Understanding Interaction Effects of Climate Change and Fire Management on Bird Distributions through Combined Process and Habitat Models

Abstract: Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process‐based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf‐area index values were lower in shrubland. This high probability of occurrence likely is related to the species’ use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.     

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence‐background (i.e., presence‐only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine‐resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine‐resolution data). The occupancy models produced significantly (P < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate‐based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km²). Estimates accounting for the area of functional habitats were significantly smaller (2–58% [SD 16]) than estimates based only on the total area occupied. An increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists.     

Assumption‐versus data‐based approaches to summarizing species’ ranges

For conservation decision making, species’ geographic distributions are mapped using various approaches. Some such efforts have downscaled versions of coarse‐resolution extent‐of‐occurrence maps to fine resolutions for conservation planning. We examined the quality of the extent‐of‐occurrence maps as range summaries and the utility of refining those maps into fine‐resolution distributional hypotheses. Extent‐of‐occurrence maps tend to be overly simple, omit many known and well‐documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce substantial error in estimates of species’ true areas of distribution. However, no model‐evaluation steps are taken to assess the predictive ability of these models, so model inaccuracies are not noticed. Whereas range summaries derived by these methods may be useful in coarse‐grained, global‐extent studies, their continued use in on‐the‐ground conservation applications at fine spatial resolutions is not advisable in light of reliance on assumptions, lack of real spatial resolution, and lack of testing. In contrast, data‐driven techniques that integrate primary data on biodiversity occurrence with remotely sensed data that summarize environmental dimensions (i.e., ecological niche modeling or species distribution modeling) offer data‐driven solutions based on a minimum of assumptions that can be evaluated and validated quantitatively to offer a well‐founded, widely accepted method for summarizing species’ distributional patterns for conservation applications.     

Geographic range size and extinction risk assessment in nomadic species

Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to‐and‐fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid‐zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning.     

Evaluating multispecies landscape connectivity in a threatened tropical mammal community

Habitat corridors are important tools for maintaining connectivity in increasingly fragmented landscapes, but generally they have been considered in single‐species approaches. Corridors intended to facilitate the movement of multiple species could increase persistence of entire communities, but at the likely cost of being less efficient for any given species than a corridor intended specifically for that species. There have been few tests of the trade‐offs between single‐ and multispecies corridor approaches. We assessed single‐species and multispecies habitat corridors for 5 threatened mammal species in tropical forests of Borneo. We generated maps of the cost of movement across the landscape for each species based on the species’ local abundance as estimated through hierarchical modeling of camera‐trap data with biophysical and anthropogenic covariates. Elevation influenced local abundance of banded civets (Hemigalus derbyanus) and sun bears (Helarctos malayanus). Increased road density was associated with lower local abundance of Sunda clouded leopards (Neofelis diardi) and higher local abundance of sambar deer (Rusa unicolor). Pig‐tailed macaque (Macaca nemestrina) local abundance was lower in recently logged areas. An all‐species‐combined connectivity scenario with least‐cost paths and 1 km buffers generated total movement costs that were 27% and 23% higher for banded civets and clouded leopards, respectively, than the connectivity scenarios for those species individually. A carnivore multispecies connectivity scenario, however, increased movement cost by 2% for banded civets and clouded leopards. Likewise, an herbivore multispecies scenario provided more effective connectivity than the all‐species‐combined scenario for sambar and macaques. We suggest that multispecies habitat connectivity plans be tailored to groups of ecologically similar, disturbance‐sensitive species to maximize their effectiveness. Evaluación de la Conectividad de Terrenos Multiespecie en una Comunidad Tropical de Mamíferos     

Historical spatial reconstruction of a spawning‐aggregation fishery

Aggregations of individual animals that form for breeding purposes are a critical ecological process for many species, yet these aggregations are inherently vulnerable to exploitation. Studies of the decline of exploited populations that form breeding aggregations tend to focus on catch rate and thus often overlook reductions in geographic range. We tested the hypothesis that catch rate and site occupancy of exploited fish‐spawning aggregations (FSAs) decline in synchrony over time. We used the Spanish mackerel (Scomberomorus commerson) spawning‐aggregation fishery in the Great Barrier Reef as a case study. Data were compiled from historical newspaper archives, fisher knowledge, and contemporary fishery logbooks to reconstruct catch rates and exploitation trends from the inception of the fishery. Our fine‐scale analysis of catch and effort data spanned 103 years (1911–2013) and revealed a spatial expansion of fishing effort. Effort shifted offshore at a rate of 9.4 nm/decade, and 2.9 newly targeted FSAs were reported/decade. Spatial expansion of effort masked the sequential exploitation, commercial extinction, and loss of 70% of exploited FSAs. After standardizing for improvements in technological innovations, average catch rates declined by 90.5% from 1934 to 2011 (from 119.4 to 11.41 fish/vessel/trip). Mean catch rate of Spanish mackerel and occupancy of exploited mackerel FSAs were not significantly related. Our study revealed a special kind of shifting spatial baseline in which a contraction in exploited FSAs occurred undetected. Knowledge of temporally and spatially explicit information on FSAs can be relevant for the conservation and management of FSA species.     

A Matrix‐Calibrated Species‐Area Model for Predicting Biodiversity Losses Due to Land‐Use Change

Abstract: Application of island biogeography theory to prediction of species extinctions resulting from habitat loss is based on the assumption that the transformed landscape matrix is completely inhospitable to the taxa considered, despite evidence demonstrating the nontrivial influence of matrix on populations within habitat remnants. The island biogeography paradigm therefore needs refining to account for specific responses of taxa to the area of habitat “islands” and to the quality of the surrounding matrix. We incorporated matrix effects into island theory by partitioning the slope (z value) of species–area relationships into two components: γ, a constant, and σ, a measure of taxon‐specific responses to each component of a heterogeneous matrix. We used our matrix‐calibrated model to predict extinction and endangerment of bird species resulting from land‐use change in 20 biodiversity hotspots and compared these predictions with observed numbers of extinct and threatened bird species. We repeated this analysis with the conventional species–area model and the countryside species–area model, considering alternative z values of 0.35 (island) or 0.22 (continental). We evaluated the relative strength of support for each of the five candidate models with Akaike's information criterion (AIC). The matrix‐calibrated model had the highest AIC weight (w_i = 89.21%), which means the weight of evidence in support of this model was the optimal model given the set of candidate models and the data. In addition to being a valuable heuristic tool for assessing extinction risk, our matrix‐calibrated model also allows quantitative assessment of biodiversity benefits (and trade‐offs) of land‐management options in human‐dominated landscapes. Given that processes of secondary regeneration have become more widespread across tropical regions and are predicted to increase, our matrix‐calibrated model will be increasingly appropriate for practical conservation in tropical landscapes.     

Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species

Abstract: Species distribution models are critical tools for the prediction of invasive species spread and conservation of biodiversity. The majority of species distribution models have been built with environmental data. Community ecology theory suggests that species co‐occurrence data could also be used to predict current and potential distributions of species. Species assemblages are the products of biotic and environmental constraints on the distribution of individual species and as a result may contain valuable information for niche modeling. We compared the predictive ability of distribution models of annual grassland plants derived from either environmental or community‐composition data. Composition‐based models were built with the presence or absence of species at a site as predictors of site quality, whereas environment‐based models were built with soil chemistry, moisture content, above‐ground biomass, and solar radiation as predictors. The reproductive output of experimentally seeded individuals of 4 species and the abundance of 100 species were used to evaluate the resulting models. Community‐composition data were the best predictors of both the site‐specific reproductive output of sown individuals and the site‐specific abundance of existing populations. Successful community‐based models were robust to omission of data on the occurrence of rare species, which suggests that even very basic survey data on the occurrence of common species may be adequate for generating such models. Our results highlight the need for increased public availability of ecological survey data to facilitate community‐based modeling at scales relevant to conservation.     

Estimating Extinction Risk with Metapopulation Models of Large‐Scale Fragmentation

Habitat loss is the principal threat to species. How much habitat remains—and how quickly it is shrinking—are implicitly included in the way the International Union for Conservation of Nature determines a species’ risk of extinction. Many endangered species have habitats that are also fragmented to different extents. Thus, ideally, fragmentation should be quantified in a standard way in risk assessments. Although mapping fragmentation from satellite imagery is easy, efficient techniques for relating maps of remaining habitat to extinction risk are few. Purely spatial metrics from landscape ecology are hard to interpret and do not address extinction directly. Spatially explicit metapopulation models link fragmentation to extinction risk, but standard models work only at small scales. Counterintuitively, these models predict that a species in a large, contiguous habitat will fare worse than one in 2 tiny patches. This occurs because although the species in the large, contiguous habitat has a low probability of extinction, recolonization cannot occur if there are no other patches to provide colonists for a rescue effect. For 4 ecologically comparable bird species of the North Central American highland forests, we devised metapopulation models with area‐weighted self‐colonization terms; this reflected repopulation of a patch from a remnant of individuals that survived an adverse event. Use of this term gives extra weight to a patch in its own rescue effect. Species assigned least risk status were comparable in long‐term extinction risk with those ranked as threatened. This finding suggests that fragmentation has had a substantial negative effect on them that is not accounted for in their Red List category. Estimación del Riesgo de Extinción Mediante Modelos Metapoblacionales de Fragmentación a Gran Escala     

Specimen‐Based Modeling,Stopping Rules,and the Extinction of the Ivory‐Billed Woodpecker

Abstract: Assessing species survival status is an essential component of conservation programs. We devised a new statistical method for estimating the probability of species persistence from the temporal sequence of collection dates of museum specimens. To complement this approach, we developed quantitative stopping rules for terminating the search for missing or allegedly extinct species. These stopping rules are based on survey data for counts of co‐occurring species that are encountered in the search for a target species. We illustrate both these methods with a case study of the Ivory‐billed Woodpecker (Campephilus principalis), long assumed to have become extinct in the United States in the 1950s, but reportedly rediscovered in 2004. We analyzed the temporal pattern of the collection dates of 239 geo‐referenced museum specimens collected throughout the southeastern United States from 1853 to 1932 and estimated the probability of persistence in 2011 as <6.4 × 10^?5, with a probable extinction date no later than 1980. From an analysis of avian census data (counts of individuals) at 4 sites where searches for the woodpecker were conducted since 2004, we estimated that at most 1–3 undetected species may remain in 3 sites (one each in Louisiana, Mississippi, Florida). At a fourth site on the Congaree River (South Carolina), no singletons (species represented by one observation) remained after 15,500 counts of individual birds, indicating that the number of species already recorded (56) is unlikely to increase with additional survey effort. Collectively, these results suggest there is virtually no chance the Ivory‐billed Woodpecker is currently extant within its historical range in the southeastern United States. The results also suggest conservation resources devoted to its rediscovery and recovery could be better allocated to other species. The methods we describe for estimating species extinction dates and the probability of persistence are generally applicable to other species for which sufficient museum collections and field census results are available.     

Extinction in a hyperdiverse endemic Hawaiian land snail family and implications for the underestimation of invertebrate extinction

The International Union for Conservation of Nature (IUCN) Red List includes 832 species listed as extinct since 1600, a minuscule fraction of total biodiversity. This extinction rate is of the same order of magnitude as the background rate and has been used to downplay the biodiversity crisis. Invertebrates comprise 99% of biodiversity, yet the status of a negligible number has been assessed. We assessed extinction in the Hawaiian land snail family Amastridae (325 species, IUCN lists 33 as extinct). We did not use the stringent IUCN criteria, by which most invertebrates would be considered data deficient, but a more realistic approach comparing historical collections with modern surveys and expert knowledge. Of the 325 Amastridae species, 43 were originally described as fossil or subfossil and were assumed to be extinct. Of the remaining 282, we evaluated 88 as extinct and 15 as extant and determined that 179 species had insufficient evidence of extinction (though most are probably extinct). Results of statistical assessment of extinction probabilities were consistent with our expert evaluations of levels of extinction. Modeling various extinction scenarios yielded extinction rates of 0.4‐14.0% of the amastrid fauna per decade. The true rate of amastrid extinction has not been constant; generally, it has increased over time. We estimated a realistic average extinction rate as approximately 5%/decade since the first half of the nineteenth century. In general, oceanic island biotas are especially susceptible to extinction and global rate generalizations do not reflect this. Our approach could be used for other invertebrates, especially those with restricted ranges (e.g., islands), and such an approach may be the only way to evaluate invertebrates rapidly enough to keep up with ongoing extinction.