Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-03T01:58:05.205Z Has data issue: false hasContentIssue false

14 - Scale-dependence of habitat sources and sinks

Published online by Cambridge University Press:  05 July 2011

Jeffrey M. Diez
Affiliation:
School of Natural Resources and Environment, Michigan, USA
Itamar Giladi
Affiliation:
Ben-Gurion University of the Negev, Israel
Jianguo Liu
Affiliation:
Michigan State University
Vanessa Hull
Affiliation:
Michigan State University
Anita T. Morzillo
Affiliation:
Oregon State University
John A. Wiens
Affiliation:
PRBO Conservation Science
Get access

Summary

Studies of population dynamics are necessarily contingent on scale, both spatial and temporal extent and grain of study. Observed population dynamics may vary across scales, and different processes may drive these patterns at different scales. Habitat sources and sinks are driven by variation in demographic vital rates such as survival, growth, and reproduction, which often vary widely across spatial and temporal scales. The knowledge that patterns may vary across scales, and different driving variables may be relevant at different scales, is intuitive to ecologists. Merging this awareness of scale with quantitative studies of population dynamics has proven difficult, however. The overall aims of this chapter are to show how scale has influenced studies of source–sink dynamics, and to highlight an emerging statistical approach for better quantifying population dynamics at different scales. After a brief review of how issues of scale are central to understanding source–sink dynamics, we show how hierarchical models can help quantify demographic variation across different scales and make predictions for sparsely populated sites. We use a brief case study of the demography of a forest herb, Hexastylis arifolia (“little brown jug”), to highlight how demographic rates and predicted population growth rates may be quantified at different scales. We conclude with a discussion of important extensions to this work, including the incorporation of dispersal, and the possible implications of scale for assessments of source–sink dynamics.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Apps, C. D., McLellan, B. N., Kinley, T. A. and Flaa, J. P. (2001). Scale-dependent habitat selection by mountain caribou, Columbia Mountains, British Columbia. Journal of Wildlife Management 65: 65–77.CrossRefGoogle Scholar
Battin, J. (2004). When good animals love bad habitats: ecological traps and the conservation of animal populations. Conservation Biology 18: 1482–1491.CrossRefGoogle Scholar
Berry, E. J., Gorchov, D. L., Endress, B. A. and Stevens, M. H. H. (2008). Source–sink dynamics within a plant population: the impact of substrate and herbivory on palm demography. Population Ecology 50: 63–77.CrossRefGoogle Scholar
Blondel, J., Dias, P. C., Ferret, P., Maistre, M. and Lambrechts, M. M. (1999). Selection-based biodiversity at a small spatial scale in a low-dispersing insular bird. Science 285: 1399–1402.CrossRefGoogle Scholar
Bohrer, G., Nathan, R. and Volis, S. (2005). Effects of long-distance dispersal for metapopulation survival and genetic structure at ecological time and spatial scales. Journal of Ecology 93: 1029–1040.CrossRefGoogle Scholar
Boughton, D. A. (1999). Empirical evidence for complex source–sink dynamics with alternative states in a butterfly metapopulation. Ecology 80: 2727–2739.Google Scholar
Boughton, D. A. (2000). The dispersal system of a butterfly: a test of source–sink theory suggests the intermediate-scale hypothesis. American Naturalist 156: 131–144.Google ScholarPubMed
Bowne, D. R. and Bowers, M. A. (2004). Interpatch movements in spatially structured populations: a literature review. Landscape Ecology 19: 1–20.CrossRefGoogle Scholar
Breininger, D. R. and Carter, G. M. (2003). Territory quality transitions and source–sink dynamics in a Florida scrub-jay population. Ecological Applications 13: 516–529.CrossRefGoogle Scholar
Breininger, D. R. and Oddy, D. M. (2004). Do habitat potential, population density, and fires influence scrub-jay source–sink dynamics?Ecological Applications 14: 1079–1089.CrossRefGoogle Scholar
Byers, J. E., Blakeslee, A. M. H., Linder, E., Cooper, A. B. and Maguire, T. J. (2008). Controls of spatial variation in the prevalence of trematode parasites infecting a marine snail. Ecology 89: 439–451.CrossRefGoogle ScholarPubMed
Caswell, H. (2001). Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer Associates, Sunderland, MA.Google Scholar
Caudill, C. C. (2003). Empirical evidence for nonselective recruitment and a source–sink dynamic in a mayfly metapopulation. Ecology 84: 2119–2132.CrossRefGoogle Scholar
Caudill, C. C. (2005). Trout predators and demographic sources and sinks in a mayfly metapopulation. Ecology 86: 935–946.CrossRefGoogle Scholar
Chalfoun, A. D. and Martin, T. E. (2007). Assessments of habitat preferences and quality depend on spatial scale and metrics of fitness. Journal of Applied Ecology 44: 983–992.CrossRefGoogle Scholar
Ciarniello, L. M., Boyce, M. S., Seip, D. R. and Heard, D. C. (2007). Grizzly bear habitat selection is scale dependent. Ecological Applications 17: 1424–1440.CrossRefGoogle ScholarPubMed
Clark, J. S. (2003). Uncertainty and variability in demography and population growth: a hierarchical approach. Ecology 84: 1370–1381.CrossRefGoogle Scholar
Clark, J. S. (2007). Models for Ecological Data: An Introduction. Princeton University Press, Princeton, NJ.Google Scholar
Clark, J. S. and Gelfand, A. E. (eds.) (2006). Hierarchical Modelling for the Environmental Sciences. Oxford University Press, Oxford, UK.
Clark, J. S., LaDeau, S. and Ibanez, I. (2004). Fecundity of trees and the colonization–competition hypothesis. Ecological Monographs 74: 415–442.CrossRefGoogle Scholar
Clark, J. S., Ferraz, G. A., Oguge, N., Hays, H. and DiCostanzo, J. (2005). Hierarchical Bayes for structured, variable populations: from recapture data to life-history prediction. Ecology 86: 2232–2244.CrossRefGoogle Scholar
Collins, B. S., Dunne, K. P. and Pickett, S. T. A. (1985). Responses of forest herbs to canopy gaps. In The Ecology of Natural Disturbance and Patch Dynamics (Pickett, S. T. A. and White, P. S., eds.). Academic Press, London.Google Scholar
Cowen, R. K., Lwiza, K. M. M., Sponaugle, S., Paris, C. B. and Olson, D. B. (2000). Connectivity of marine populations: open or closed?Science 287: 857–859.CrossRefGoogle ScholarPubMed
Cowen, R. K., Paris, C. B. and Srinivasan, A. (2006). Scaling of connectivity in marine populations. Science 311: 522–527.CrossRefGoogle ScholarPubMed
Cronin, J. T. (2007). From population sources to sieves: the matrix alters host-parasitoid source–sink structure. Ecology 88: 2966–2976.CrossRefGoogle ScholarPubMed
Damman, H. and Cain, M. L. (1998). Population growth and viability analyses of the clonal woodland herb, Asarum canadense. Journal of Ecology 86: 13–26.CrossRefGoogle Scholar
Delibes, M., Ferreras, P. and Gaona, P. (2001). Attractive sinks, or how individual behavioural decisions determine source–sink dynamics. Ecology Letters 4: 401–403.CrossRefGoogle Scholar
Dias, P. C. (1996). Sources and sinks in population biology. Trends in Ecology and Evolution 11: 326–330.CrossRefGoogle ScholarPubMed
Dias, P. C., Verheyen, G. R. and Raymond, M. (1996). Source–sink populations in Mediterranean blue tits: evidence using single-locus minisatellite probes. Journal of Evolutionary Biology 9: 965–978.CrossRefGoogle Scholar
Diez, J. M. (2007). Hierarchical patterns of symbiotic orchid germination linked to adult proximity and environmental gradients. Journal of Ecology 95: 159–170.CrossRefGoogle Scholar
Doak, D. F. (1995). Source–sink models and the problem of habitat degradation: general models and applications to the Yellowstone grizzly. Conservation Biology 9: 1370–1379.CrossRefGoogle Scholar
Dupré, C. and Ehrlén, J. (2002). Habitat configuration, species traits and plant distributions. Journal of Ecology 90: 796–805.CrossRefGoogle Scholar
Fieberg, J. and Ellner, S. P. (2001). Stochastic matrix models for conservation and management: a comparative review of methods. Ecology Letters 4: 244–266.CrossRefGoogle Scholar
Gelman, A. and Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press, Cambridge, UK.Google Scholar
Gelman, A., Carlin, J. B. and Rubin, H. S. S. B. (2004). Bayesian Data Analysis, 2nd edition. Chapman and Hall/CRC, New York.Google Scholar
Giladi, I. (2004). The role of habitat-specific demography, habitat-specific dispersal, and the evolution of dispersal distances in determining current and future distributions of the ant-dispersed forest herb, Hexastylis arifolia. PhD dissertation, Institute of Ecology, University of Georgia, Athens, GA.
Gonzalez, V. C. (1972). The ecology of Hexastylis arifolia, an evergreen herb in the North Carolina deciduous forest. PhD dissertation, Department of Botany, Duke University, Durham, NC.
Grear, J. S. and Burns, C. E. (2007). Evaluating effects of low-quality habitats on regional population growth in Peromyscus leucopus: insights from field-parameterized spatial matrix models. Landscape Ecology 22: 45–60.CrossRefGoogle Scholar
Gundersen, G., Johannesen, E., Andreassen, H. P. and Ims, R. A. (2001). Source–sink dynamics: how sinks affect demography of sources. Ecology Letters 4: 14–21.CrossRefGoogle Scholar
Hatchwell, B. J., Chamberlain, D. E. and Perrins, C. M. (1996). The demography of blackbirds Turdus merula in rural habitats: is farmland a sub-optimal habitat?Journal of Applied Ecology 33: 1114–1124.CrossRefGoogle Scholar
Hobson, K. A., Wassenaar, L. I. and Bayne, E. (2004). Using isotopic variance to detect long-distance dispersal and philopatry in birds: an example with ovenbirds and American redstarts. Condor 106: 732–743.CrossRefGoogle Scholar
Holt, R. D. (1985). Population dynamics in two-patch environments: some anomalous consequences of an optimal habitat distribution. Theoretical Population Biology 28: 181–208.CrossRefGoogle Scholar
Hunter, C. M. and Caswell, H. (2005). The use of the vec-permutation matrix in spatial matrix population models. Ecological Modelling 188: 15–21.CrossRefGoogle Scholar
Johnson, D. M. (2004). Source–sink dynamics in a temporally heterogeneous environment. Ecology 85: 2037–2045.CrossRefGoogle Scholar
Kadmon, R. and Shmida, A. (1990). Spatiotemporal demographic processes in plant populations: an approach and a case-study. American Naturalist 135: 382–397.CrossRefGoogle Scholar
Kadmon, R. and Tielborger, K. (1999). Testing for source–sink population dynamics: an experimental approach exemplified with desert annuals. Oikos 86: 417–429.CrossRefGoogle Scholar
Kery, M., Gregg, K. B. and Schaub, M. (2005). Demographic estimation methods for plants with unobservable life-states. Oikos 108: 307–320.CrossRefGoogle Scholar
Kotliar, N. B. and Wiens, J. A. (1990). Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity. Oikos 59: 253–260.CrossRefGoogle Scholar
Kreuzer, M. P. and Huntly, N. J. (2003). Habitat-specific demography: evidence for source–sink population structure in a mammal, the pika. Oecologia 134: 343–349.CrossRefGoogle Scholar
Kunin, W. E. (1998). Biodiversity at the edge: a test of the importance of spatial “mass effects” in the Rothamsted Park Grass experiments. Proceedings of the National Academy of Sciences of the USA 95: 207–212.CrossRefGoogle ScholarPubMed
Lele, S. R., Dennis, B. and Lutscher, F. (2007). Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Ecology Letters 10: 551–563.CrossRefGoogle ScholarPubMed
Lloyd, P., Martin, T. E., Redmond, R. L., Langner, U. and Hart, M. M. (2005). Linking demographic effects of habitat fragmentation across landscapes to continental source–sink dynamics. Ecological Applications 15: 1504–1514.CrossRefGoogle Scholar
McGeoch, M. A. and Price, P. W. (2005). Scale-dependent mechanisms in the population dynamics of an insect herbivore. Oecologia 144: 278–288.CrossRefGoogle ScholarPubMed
McMahon, S. M. and Diez, J. M. (2007). Scales of association: hierarchical linear models and the measurement of ecological systems. Ecology Letters 10: 437–452.CrossRefGoogle ScholarPubMed
McPeek, M. A. and Holt, R. D. (1992). The evolution of dispersal in spatially and temporally varying environments. American Naturalist 140: 1010–1027.CrossRefGoogle Scholar
Meisel, J. E. and Turner, M. G. (1998). Scale detection in real and artificial landscapes using semivariance analysis. Landscape Ecology 13: 347–362.CrossRefGoogle Scholar
Milot, E., Weimerskirch, H. and Bernatchez, L. (2008). The seabird paradox: dispersal, genetic structure and population dynamics in a highly mobile, but philopatric albatross species. Molecular Ecology 17: 1658–1673.CrossRefGoogle Scholar
Moloney, K. A. (1988). Fine-scale spatial and temporal variation in the demography of a perennial bunchgrass. Ecology 69: 1588–1598.CrossRefGoogle Scholar
Murphy, M. T. (2001). Habitat-specific demography of a long-distance, neotropical migrant bird, the eastern kingbird. Ecology 82: 1304–1318.CrossRefGoogle Scholar
Nathan, R. (2006). Long-distance dispersal of plants. Science 313: 786–788.CrossRefGoogle Scholar
Nathan, R., Perry, G., Cronin, J. T., Strand, A. E. and Cain, M. L. (2003). Methods for estimating long-distance dispersal. Oikos 103: 261–273.CrossRefGoogle Scholar
Nystrand, M., Griesser, M., Eggers, S. and Ekman, J. (2010). Habitat-specific demography and source–sink dynamics in a population of Siberian jays. Journal of Animal Ecology 79: 266–274.CrossRefGoogle Scholar
O’Neill, R. V., Milne, B. T., Turner, M. G. and Gardner, R. H. (1986). A Hierarchical Concept of Ecosystems. Princeton University Press, Princeton, NJ.Google Scholar
Oostermeijer, J. G. B., Brugman, M. L., DeBoer, E. R. and DenNijs, H. C. M. (1996). Temporal and spatial variation in the demography of Gentiana pneumonanthe, a rare perennial herb. Journal of Ecology 84: 153–166.CrossRefGoogle Scholar
Orians, G. H. and Wittenberger, J. F. (1991). Spatial and temporal scales in habitat selection. American Naturalist 137: S29–S49.CrossRefGoogle Scholar
Pulliam, H. R. (1988). Sources, sinks, and population regulation. American Naturalist 132: 652–661.CrossRefGoogle Scholar
R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria [available at ]Google Scholar
Raudenbush, S. W. and Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods. Sage Publications, London.Google Scholar
Reid, J. M., Bignal, E. M., Bignal, S., McCracken, D. I. and Monaghan, P. (2006). Spatial variation in demography and population growth rate: the importance of natal location. Journal of Animal Ecology 75: 1201–1211.CrossRefGoogle ScholarPubMed
Roberts, C. M. (1997). Connectivity and management of Caribbean coral reefs. Science 278: 1454–1457.CrossRefGoogle ScholarPubMed
Robinson, S. K., Thompson, F. R., Donovan, T. M., Whitehead, D. R. and Faaborg, J. (1995). Regional forest fragmentation and the nesting success of migratory birds. Science 267: 1987–1990.CrossRefGoogle ScholarPubMed
Runge, J. P., Runge, M. C. and Nichols, J. D. (2006). The role of local populations within a landscape context: defining and classifying sources and sinks. American Naturalist 167: 925–938.CrossRefGoogle ScholarPubMed
Schooley, R. L. and Branch, L. C. (2007). Spatial heterogeneity in habitat quality and cross-scale interactions in metapopulations. Ecosystems 10: 846–853.CrossRefGoogle Scholar
Shefferson, R. P., Sandercock, B. K., Proper, J. and Beissinger, S. R. (2001). Estimating dormancy and survival of a rare herbaceous perennial using mark–recapture models. Ecology 82: 145–156.Google Scholar
Sodhi, N. S., Paszkowski, C. A. and Keehn, S. (1999). Scale-dependent habitat selection by American redstarts in aspen-dominated forest fragments. Wilson Bulletin 111: 70–75.Google Scholar
Tackenberg, O. (2003). Modeling long-distance dispersal of plant diaspores by wind. Ecological Monographs 73: 173–189.CrossRefGoogle Scholar
Thomas, A., O’Hara, R. B., Ligges, U. and Sturtz, S. (2006). Making BUGS open. R News 6: 12–17.Google Scholar
Thomas, C. D. and Kunin, W. E. (1999). The spatial structure of populations. Journal of Animal Ecology 68: 647–657.CrossRefGoogle Scholar
Thompson, F. R., Donovan, T. M., DeGraaf, R. M., Faaborg, J. and Robinson, S. K. (2002). A multi-scale perspective of the effects of forest fragmentation on birds in eastern forests. In Effects of Habitat Fragmentation on Birds in Western Landscapes: Contrasts With Paradigms from the Eastern United States (George, T. L. and Dobkin, D. S., eds.). Studies in Avian Biology 25, Cooper Ornithological Society, Norman, OK.Google Scholar
Thomson, D. M. (2007). Do source–sink dynamics promote the spread of an invasive grass into a novel habitat?Ecology 88: 3126–3134.CrossRefGoogle ScholarPubMed
Tittler, R., Fahrig, L. and Villard, M. A. (2006). Evidence of large-scale source–sink dynamics and long-distance dispersal among wood thrush populations. Ecology 87: 3029–3036.CrossRefGoogle ScholarPubMed
Trakhtenbrot, A., Nathan, R., Perry, G. and Richardson, D. M. (2005). The importance of long-distance dispersal in biodiversity conservation. Diversity and Distributions 11: 173–181.CrossRefGoogle Scholar
Van Horne, B. (1983). Density as a misleading indicator of habitat quality. Journal of Wildlife Management 47: 893–901.CrossRefGoogle Scholar
Vavrek, M. C., McGraw, J. B. and Yang, H. S. (1996). Within-population variation in demography of Taraxacum officinale: maintenance of genetic diversity. Ecology 77: 2098–2107.CrossRefGoogle Scholar
Vellend, M., Myers, J. A., Gardescu, S. and Marks, P. L. (2003). Dispersal of Trillium seeds by deer: implications for long-distance migration of forest herbs. Ecology 84: 1067–1072.CrossRefGoogle Scholar
Virgl, J. A. and Messier, F. (2000). Assessment of source–sink theory for predicting demographic rates among habitats that exhibit temporal changes in quality. Canadian Journal of Zoology – Revue Canadienne de Zoologie 78: 1483–1493.CrossRefGoogle Scholar
Warren, R. J. (2007). Linking understory evergreen herbaceous distributions and niche differentiation using habitat-specific demography and experimental common gardens. PhD dissertation, University of Georgia, Athens, GA.
Watkinson, A. R. and Sutherland, W. J. (1995). Sources, sinks and pseudo-sinks. Journal of Animal Ecology 64: 126–130.CrossRefGoogle Scholar
Whigham, D. E. (2004). Ecology of woodland herbs in temperate deciduous forests. Annual Review of Ecology Evolution and Systematics 35: 583–621.CrossRefGoogle Scholar
Wiens, J. A. (1989). Spatial scaling in ecology. Functional Ecology 3: 385–397.CrossRefGoogle Scholar
With, K. A. and King, A. W. (1999). Dispersal success on fractal landscapes: a consequence of lacunarity thresholds. Landscape Ecology 14: 73–82.CrossRefGoogle Scholar
With, K. A., Schrott, G. R. and King, A. W. (2006). The implications of metalandscape connectivity for population viability in migratory songbirds. Landscape Ecology 21: 157–167.CrossRefGoogle Scholar
Zelikova, T. J., Dunn, R. R. and Sanders, N. J. (2008). Variation in seed dispersal along an elevational gradient in Great Smoky Mountains National Park. Acta Oecologica – International Journal of Ecology 34: 155–162.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×