Using model analysis to design monitoring programs for landscape management and impact assessment

While ecologists have long recognized the key role of monitoring programs i n natural-resource management, we have only recently come to appreciate the logistical difficulties of designing powerful yet efficient schemes for mo nitoring large, heterogeneous landscapes. Such designs are especially chall enging if the signal to be monitored is uncertain, such as in the case of e cosystem response to climate change. I illustrate an approach in which a si mulation model is used to design a monitoring scheme that focuses on applic ation-specific sensitivities or uncertainties. Formal model analysis define s these sensitivities in the model's parameter space. These parametric doma ins are then mapped into geographic space by regressing model sensitivity o n terrain variables in a geographic information system. Specific sites for monitoring are then selected by sampling with a two-stage stratified-cluste r design from these parametrically sensitive or uncertain locations, As an example, I use a forest simulation model to design a monitoring scheme as p art of a climate-change research program in the southern Sierra Nevada of C alifornia (USA). I analyze the model to summarize its sensitivity to variat ion in temperature and precipitation, and then add a consideration of uncer tainty due to the influence of topographic convergence on soil moisture-an influence not simulated by the model. Sensitive and uncertain sites are fur ther constrained by logistical concerns about ease of access, resulting in a target sampling domain that represents less than 2% of the study area.