Abstract
Species richness is the most widely used biodiversity measure. Virtually always, it cannot be observed but needs to be estimated because some species may be present but remain undetected. This fact is commonly ignored in ecology and management, although it will bias estimates of species richness and related parameters such as occupancy, turnover or extinction rates. We describe a species community modeling strategy based on species-specific models of occurrence, from which estimates of important summaries of community structure, e.g., species richness, occupancy, or measures of similarity among species or sites, are derived by aggregating indicators of occurrence for all species observed in the sample, and for the estimated complement of unobserved species. We use data augmentation for an efficient Bayesian approach to estimation and prediction under this model based on MCMC in WinBUGS. For illustration, we use the Swiss breeding bird survey (MHB) that conducts 2–3 territory-mapping surveys in a systematic sample of 267 1 km2 units on quadrat-specific routes averaging 5.1 km to obtain species-specific estimates of occupancy, and estimates of species richness of all diurnal species free of distorting effects of imperfect detectability. We introduce into our model species-specific covariates relevant to occupancy (elevation, forest cover, route length) and sampling (season, effort). From 1995 to 2004, 185 diurnal breeding bird species were known in Switzerland, and an additional 13 bred 1–3 times since 1900. 134 species were observed during MHB surveys in 254 quadrats surveyed in 2001, and our estimate of 169.9 (95% CI 151–195) therefore appeared sensible. The observed number of species ranged from 4 to 58 (mean 32.8), but with an estimated 0.7–11.2 (mean 2.6) further, unobserved species, the estimated proportion of detected species was 0.48–0.98 (mean 0.91). As is well known, species richness declined at higher elevation and fell above the timberline, and most species showed some preferred elevation. Route length had clear effects on occupancy, suggesting it is a proxy for the size of the effectively sampled area. Detection probability of most species showed clear seasonal patterns and increased with greater survey effort; these are important results for the planning of focused surveys. The main benefit of our model, and its implementation in WinBUGS for which we provide code, is its conceptual simplicity. Species richness is naturally expressed as the sum of occurrences of individual species. Information about species is combined across sites, which yields greater efficiency or may even enable estimation for sites with very few observed species in the first place. At the same time, species detections are clearly segregated into a true state process (occupancy) and an observation process (detection, given occupancy), and covariates can be readily introduced, which provides for efficient introduction of such additional information as well as sharp testing of such relationships.
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References
Boulinier T, Nichols JD, Sauer JR, Hines JE, Pollock KH (1998a) Estimating species richness: The importance of heterogeneity in species detectability. Ecology 79:1018–1028.
Boulinier T, Nichols JD, Hines JE, Sauer JR, Flather CH, Pollock KH (1998b) Higher temporal variability of forest breeding bird communities in fragmented landscapes. Proceedings of the National Academy of Sciences 95:7497–7501.
Boulinier T, Nichols JD, Hines JE, Sauer JR, Flather CH, Pollock KH (2001) Forest fragmentation and bird community dynamics: Inference at regional scales. Ecology 82: 1159–1169.
Cam E, Nichols JD, Sauer JR, Hines JE (2002) On the estimation of species richness based on the accumulation of previously unrecorded species. Ecography 25:102–108.
Connolly SR (2005) Process-based models of species distributions and the mid-domain effect. American Naturalist 166:1–11.
Dorazio RM, Royle JA (2005) Estimating size and composition of biological communities by modeling the occurrence of species. Journal of the American Statistical Association 100: 389–398.
Dorazio RM, Royle JA, Söderström B, Glimskär A (2006) Estimating species richness and accumulation by modeling species occurrence and detectability. Ecology 87:842–854.
Freckleton RP, Noble D, Webb TJ (2006) Distribution of habitat suitability and the abundance–occupancy relationship. American Naturalist 167:260–275.
Gelman A, Rubin DB (1992) Inference from iterative simulation using multiple sequences. Statistical Science 7:457–511.
Gotelli NJ, Colwell RK (2001) Quantifying biodiversity: Procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters 4:379–391.
Gotelli NJ, McGill BJ (2006) Null versus neutral models: What's the difference? Ecography 29:793–800.
He F, Gaston KJ (2003) Occupancy, spatial variance, and the abundance of species. American Naturalist 162:366–375.
Kéry M (2002) Inferring the absence of a species – A case study of snakes. Journal of Wildlife Management 66:330–338.
Kéry M, Royle JA (2008) Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys. Submitted to Journal of Applied Ecology, in press.
Kéry M, Royle JA, Schmid H (2005) Modeling avian abundance from replicated counts using binomial mixture models. Ecological Applications 15:1450–1461.
Kéry M, Schmid H (2006) Estimating species richness: Calibrating a large-scale avian monitoring program. Journal of Applied Ecology 43:101–110.
Link WA, Sauer JR (1998) Estimating population change from count data: Application to the North American breeding bird survey. Ecological Applications 8:258–268.
MacKenzie DI, Nichols JD, Lachman GB, Droege S, Royle JA, Langtimm CA (2002) Estimating site occupancy when detection probabilities are less than one. Ecology 83:2248–2255.
MacKenzie DI, Nichols JD, Royle JA, Pollock KH, Hines JE, Bailey LL (2006) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence, Academic Press, San Diego, USA.
Mao CX, Colwell RK (2005) Estimation of species richness: Mixture models, the role of rare species, and inferential challenges. Ecology 86:1143–1153.
McCoy ED, Heck Jr. KL, (1987) Some observations on the use of taxonomic similarity in large-scale biogeography. Journal of Biogeography 14:79–87.
Nichols JD, Boulinier T, Hines JE, Pollock KH, Sauer JR (1998a) Inference methods for spatial variation in species richness and community composition when not all species are detected. Conservation Biology 12:1390–1398.
Nichols JD, Boulinier T, Hines JE, Pollock KH, Sauer JR (1998b) Estimating rates of local species extinction, colonization, and turnover in animal communities. Ecological Applications 8:1213–1225.
Orme CDL, Davies RG, Burgess M, Eigenbrod F, Pickup N, Olson VA, Webster AJ, Ding TS, Rasmussen PC, Ridgely RS, Stattersfield AJ, Bennett PM, Blackburn TM, Gaston KJ, and Owens, I.P.F. (2005) Global hotspots of species richness are not congruent with endemism or threat. Nature 436:1016–1019.
Otis DL, Burnham KP, White GC, Anderson DR (1978) Statistical inference for capture data on closed animal populations. Wildlife Monographs 62:1–135.
Purvis A, Hector A (2000) Getting the measure of biodiversity. Nature 405:212–219.
Royle JA, Nichols JD (2003) Estimating abundance from repeated presence-absence data or point counts. Ecology 84:777–790.
Royle JA, Nichols JD, Kéry M (2005) Modeling occurrence and abundance of species with imperfect detection. Oikos 110:353–359.
Royle JA, Dorazio RM, Link WA (2007a) Analysis of multinomial models with unknown index using data augmentation. Journal of Computational and Graphical Statistics 16:67–85.
Royle JA, Kéry M (2007) A Bayesian state-space formulation of dynamic occupancy models. Ecology 88:1813–1823.
Royle JA, Kéry M, Gautier R, Schmid H (2007b) Hierarchical spatial models of abundance and occurrence from imperfect survey data. Ecological Monographs 77:465–481.
Sauer JR, Peterjohn BG, Link WA (1994) Observer differences in the North American Breeding bird survey. Auk 111:50–62.
Schmid H, Zbinden N, Keller V (2004) Überwachung der Bestandsentwicklung häufiger Brutvögel in der Schweiz, Swiss Ornithological Institute, Sempach, Switzerland.
Schmidt BR (2005) Monitoring the distribution of pond-breeding amphibians when species are detected imperfectly. Aquatic Conservation: Marine and Freshwater Ecosystems 15: 681–692.
Smith BJ (2005) Bayesian Output Analysis Program (BOA), Version 1.1.5. The University of Iowa. http://www.public-health.uiowa.edu/boa (accessed March 23, 2005).
Spiegelhalter D, Thomas A, Best NG (2003) WinBUGS User Manual, Version 1.4., MCR Biostatistics Unit, Cambridge.
Volet B (2006) Liste der Vogelarten der Schweiz (Checklist of the birds of Switzerland). Der Ornithologische Beobachter 103:271–294.
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Kéry, M., Royle, J.A. (2009). Inference About Species Richness and Community Structure Using Species-Specific Occupancy Models in the National Swiss Breeding Bird Survey MHB. In: Thomson, D.L., Cooch, E.G., Conroy, M.J. (eds) Modeling Demographic Processes In Marked Populations. Environmental and Ecological Statistics, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78151-8_28
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DOI: https://doi.org/10.1007/978-0-387-78151-8_28
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