Landscape Ecology

Individual responses to landscape structure: habitat selection via movement


Terms/people:

habitat habitat selection

Fretwell & Lucas 1970 Fretwell 1972

ideal free distribution despotic distribution

Van Horne 1983 percolation

random walk/correlated random walk spanning cluster

movement rules critical threshold

hierarchical (Johnson 1980) pcrit

Part 1 - Habitat selection

But first...what is habitat?

Because we know so little about most species, identifying habitat is very difficult. For example, you might consider forest habitats: these habitats can be distinguished on the basis of the most abundant tree species, the tallest tree species, stand age, understory type, etc. Each way you identify habitat can affect the types of observations you make and the data you obtain. And keep in mind that habitat types that may be identifiable to us may not be perceived that way by your focal organism.

So how is habitat selection defined?

Habitat __________ vs. _______________________

Habitat selection:

Habitat avoidance:

selection  preference

null hypothesis (no selection, habitats used in proportion to their availability): most time spent will be in most abundant/widespread habitat type

Selection usually assessed statistically via a chi-square test with 95% confidence intervals calculated using a Bonferroni z statistic (see Neu et al. 1974, Sparks et al. 1994):

if O and E overlap within the 95% CI, then no selection (click here for an example)

Requires independent observations (usually individuals are the replicates, but this may not be good if your animals are social and travel in packs, going where the pack leader dictates: in this case the pack and not the individuals is the replicate).

Best statistical power if number of observations per category is > 5 and there are > 5 categories.

But there are lots of alternative analytical/statistical methods, none of which is the clear best to use. The two references by Alldredge and Ratti give excellent overviews.

Habitat selection is a hierarchical process in space and time (see Johnson 1980)

Selection criteria may differ at different scales, making prediction difficult/impossible across scales: e.g. McIntyre 1997


Certain things can make the use vs. availability relationship more complicated. One of the biggest complications involves an animal’s social system (obviously relevant primarily to vertebrates), so there are two alternative mechanisms of how organisms select habitat: Ideal Free Distribution and Despotic Distribution

Ideal Free Distribution (IFD) -

• Fretwell & Lucas (1970, Acta Biotheoretica 19:16-36)

Alternative to the IFD: the Despotic Distribution (DD) -

• Fretwell (1972, Populations in a Seasonal Environment, Princeton University Press)

• Van Horne (1983, Journal of Wildlife Management 47:893-901)

The bottom line

To assess habitat selection, you need data on habitat use and habitat availability. Given that it is difficult to translate among scales, one needs to collect data at multiple scales (or confine one’s conclusions to only the scale measured).

Even with these data, without having information about the social system of a species, you will not know whether density is a good indicator of habitat quality and therefore will not be able to assess habitat selection accurately.

Part 2 – Movement

Why is studying movement important to landscape ecology?

Movement is a critically important phenomenon. It is what allows habitat selection to occur, it helps prevent extinction, and it permits gene flow. It therefore determines the abundance and distribution of organisms. A movement path is also a physical record of how an organism interacts with its environment. Therefore, studying movement allows us to quantify how spatial environmental patterns affect organism behaviors. Movement paths provide us with insights about organism-environment relationships.

How do we quantify and study movement?

In landscape ecology, we are most interested in how spatial environmental patterns affect movement behaviors. We therefore need some way of assessing how organisms move through a landscape (and we also need a neutral model as a frame of reference).

There are many ways to study movement. One common way is to develop a null model that consists of a random walk. In a random walk, movement follows an algorithm for passive diffusion (whereby an organism behaves as though it were an atom floating through the environment, without any directionality). For slightly more realism, a correlated random walk may be adopted (which allows more directionality). Both of these null models, however, assume that the environment is basically a porous medium without structure. This is obviously unrealistic. One way we can improve on this is by using percolation models, which are forms of random walks planted atop a landscape of a given pattern.

Percolation
-developed by mathematicians in the 1950s to describe movement of particles (see Broadbent and Hammersley (1956), Proc. Camb. Phil. Soc. 53:629-641)
-applied in the physical sciences to study flow in porous media (see R. Zallen (1983), The Physics of Amorphous Solids. Wiley, New York)
-applied to LE by Gardner and others in 1980s (see Gardner et al. (1987), Landscape Ecol. 1:19-28)


How to make a percolation map (a type of neutral landscape model):

neighborhood rule

p

pcrit

critical threshold

spanning cluster

Recall that larger animals or animals with greater vagility interact with the landscape at a different grain than do smaller/less mobile organisms. Therefore, an organism-centered viewpoint is crucial.

References:

Alldredge, J.R., and J.T. Ratti. 1986. Comparison of some statistical techniques for analysis of resource selection. J. Wildl. Manage. 50:157-165.

Alldredge, J.R., and J.T. Ratti. 1992. Further comparison of some statistical techniques for analysis of resource selection. J. Wildl. Manage. 56:1-9.

Crist, T.O., D.S. Guertin, J.A. Wiens, and B.T. Milne. 1992. Animal movement in heterogeneous landscapes: An experiment with Eleodes beetles in shortgrass prairie. Funct. Ecol. 6:536-544.

Fretwell, S.D. 1972. Populations in a Seasonal Environment. Princeton University Press, Princeton, NJ.

Fretwell, S.D., and H.L. Lucas. 1970. On territorial behaviour and other factors influencing habitat distribution in birds. Acta Biotheoretica 19:16-36.

Gardner, R.H., B.T. Milne, M.G. Turner, and R.V. O'Neill. 1987. Neutral models for the analysis of broad-scale landscape pattern. Landscape Ecol. 1:19-28.

Gardner, R.H., R.V. O’Neill, M.G. Turner, and V.H. Dale. 1989. Quantifying scale-dependent effects of animal movements with simple percolation models. Landscape Ecol. 3:217-227.

Garshelis, D.L. 2000. Delusions in habitat evaluation: measuring use, selection, and importance. Pp. 111-164 in: Research Techniques in Animal Ecology: Controversies and Consequences (L. Boitani and T.K. Fuller, eds.). Columbia University Press, New York, NY.

Johnson, A.R., J.A. Wiens, B.T. Milne, and T.O. Crist. 1992. Animal movements and population dynamics in heterogeneous landscapes. Landscape Ecol. 7:63-75.

Johnson, D.H. 1980. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61:65-71.

McClean, S.A., M.A. Rumble, R.M. King, and W.L. Baker. 1998. Evaluation of resource selection methods with different definitions of availability. J. Wildl. Manage. 62:793-801.

McIntyre, N.E. 1997. Scale-dependent habitat selection by the darkling beetle Eleodes hispilabris (Coleoptera: Tenebrionidae). Am. Midl. Nat. 138:230-235.

Neu, C.W., C.R. Byers, and J.M. Peek. 1974. A technique for analysis of utilization-availability data. J. Wildl. Manage. 38:541-545.

Pearson, S.M., M.G. Turner, and D.L. Urban. 1999. Effective exercises in teaching landscape ecology. Pp. 335-368 in: Landscape Ecological Analysis: Issues and Applications (J.M. Klopatek and R.H. Gardner, eds.). Springer, New York, NY.

Schultz, C.B., and E.E. Crone. 2001. Edge-mediated dispersal behavior in a prairie butterfly. Ecology 82:1879-1892.

Sparks, E.J., J.R. Belthoff, and G. Ritchison. 1994. Habitat use by Eastern Screech-Owls in central Kentucky. J. Field Ornith. 65:83-95.

Stauffer, D. 1985. Introduction to Percolation Theory. Taylor and Francis, London.

Szacki, J., and A. Liro. 1991. Movements of small mammals in the heterogeneous landscape. Landscape Ecol. 5:219-224.

Turchin, P. 1998. Quantitative Analysis of Movement: Measuring and Modeling Population Redistribution in Animals and Plants. Sinauer, Sunderland, MA.

Van Horne, B. 1983. Density as a misleading indicator of habitat quality. J. Wildl. Manage. 47:893-901.

Wiens, J.A., and B.T. Milne. 1989. Scaling of 'landscapes' in landscape ecology, or, landscape ecology from a beetle's perspective. Landscape Ecol. 3:87-96.

With, K.A. 1994. Using fractal analysis to assess how species perceive landscape structure. Landscape Ecol. 9:25-36.