English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Evaluating the steady state assumption: Simulations of gorilla nest decay

MPS-Authors
/persons/resource/persons73030

Walsh,  Peter D.
Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Walsh, P. D., & White, L. J. T. (2005). Evaluating the steady state assumption: Simulations of gorilla nest decay. Ecological Applications, 15(4), 1342-1350. Retrieved from http://www.jstor.org/stable/4543442.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-02A6-0
Abstract
Large mammal surveys are often based on indices of animal abundance such as dung or, for great apes, sleeping nests. They also tend to rely on the "steady state" assumption that the rate at which an index is deposited in the environment is exactly balanced by the rate at which it disappears (decays). Here we use a data set on western gorilla (Gorilla gorilla) sleeping nest decay rates to show that this assumption is likely to be strongly violated often and in ways that have serious implications for our ability to accurately survey and monitor a wide range of endangered species, particularly in tropical forests. We first fit the data using a model describing the daily probability of nest decay as a function of nest age. and monthly rainfall. We then use this decay model to simulate time series of gorilla nest standing stock, given observed rainfall regimes from a series of sites in the equatorial African country of Gabon. These simulations suggest that, within a given site, the relationship between nest standing stock and true gorilla density fluctuates wildly and is, on average, tens of percent away from the mean nest decay time for the empirical data set. The behavior of nest standing stock is extremely sensitive to variability in rainfall, not just annual mean rainfall. Differences between sites in rainfall variability produce counterintuitive differences between sites in nest standing stock. Multiyear trends in the mean and variance of rainfall produce the spurious impression of trends in animal abundance. Furthermore, heterogeneity in rainfall exists at all spatial and temporal scales, so that attempts to use regression models based on rainfall measurements taken at one location or time are not likely to accurately predict the nest decay regime at other places or times. We close with some suggestions on alternative estimation methods that do not rely on extrapolations of environmental conditions from one time or place to another. [References: 25]