The proposed project addresses a key question in current approaches to sustain biodiversity in managed landscapes. How do species respond to changes in habitat attributes, and can response curves be used to set reliable retention or other targets?
Recently, a framework for species conservation in managed landscapes has been proposed based on the concepts of ?thresholds? and ?targets? (Huggett 2005). The theory of ecological thresholds proposes that species respond non-linearly to changes in resources through time such that there is a threshold beyond which large-scale, rapid, and potentially irreversible changes occur (May 1973). Estimates of habitat thresholds may be useful in determining target amounts of forest necessary to support healthy populations (Huggett 2005). The theory of response thresholds is supported by recent modeling work showing a minimum habitat amount, a so-called ?extinction threshold?, below which further habitat loss causes rapid population decline (Fahrig 2001).
A suite of variables can be measured to gauge the response of species to forestry-induced changes in habitat, including population-level responses such as presence/absence, density, productivity, and the more immediate behavioural responses of individuals. However, most empirical tests for thresholds have been limited to the relationship between the probability of occurrence generated from the presence/absence of forest songbirds and changes in percent forest cover (e.g. Guénette and Villard 2005). The use of presence/absence data to predict probability of occurrence is problematic because the required statistical transformations almost always produce a threshold-like relationship (back-transformation to the probability scale of logit-transformed binomial data).
To extend our empirical knowledge of responses to habitat change, more relevant response measures need to be quantified. Further, because forest songbirds use some areas with little cover, forest cover is an inadequate measure of habitat (Lindenmayer and Luck 2005). The measurement of abundance and reproduction, in response to habitat attributes more closely tied to known habitat requirements, will make significant contributions to the empirical assessment of the ?threshold? approach to management. Reliable estimates of the response of abundance and reproduction to habitat change are highly valuable whether or not these relationships contain thresholds. These relationships can still inform target-setting, provide useful information on the effectiveness of current forest practices, and allow prediction of the likely effects of changes in management practices. Thus, we propose to 1) quantify the responses of forest songbirds and woodpeckers to changes in habitat attributes at the stand and landscape scales, and 2) test for thresholds in responses to habitat change.
Estimates of responses to habitat change, and thus response curves, may differ depending on the intensity of monitoring. Thus, we also propose to 3) compare the response curves generated by intensive survey methods used in the proposed study with those generated by a related study in the same area using a standard, less intensive survey method (Breeding Bird Survey) (F. Bunnell Y071014; Preston 2006). More intensive methods are usually more expensive and time-consuming, but do not necessarily derive more meaningful or accurate indices. However, low-intensity methods, such as the Breeding Bird Survey (BBS), have inherent biases and thus limited applications. In particular, higher detection rates have been found at roadside versus off-road stations for species associated with habitat typical of roadsides, such as shrubs, grass/forbs, and ?edge?, while detection rates are lower for forest interior species (Hutto et al. 1995). In addition, the BBS method does not generate reproductive indices, which are necessary to accurately quantify habitat for species which occur at high densities in poor habitats (?ecologic ...
Squires, Kelly A.. 2010. Quantifying the responses of songbirds and woodpeckers to changes in habitat at the stand and landscape scales ? does intensive monitoring result in different response curves?. Forest Investment Account (FIA) - Forest Science Program. Forest Investment Account Report. FIA2010MR331
Topic: FLNRORD Research Program
Keywords: Forest, Investment, Account, (FIA), British, Columbia
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