How To Prioritize Sites: Steps 4-6

Step 4: Identify and gather appropriate data

The data required for a planning effort depends on the goals of the plan and the specific targets or features that the plan is intended to protect (Step 3). If the goals are concerned with open space protection and viewshed or recreational values, then photographic and other data on the aesthetics of the landscape are critical. For a biodiversity-driven plan, the ideal centralized data source is often the state or provincial natural heritage program or conservation data center. Examples of data types for the three classes of biodiversity conservation targets are provided in Noss (2004).

In the absence of institutionalized databases like those maintained by natural heritage programs, planners must determine the reliability and consistency of their data sources as well as their areas of uncertainty. They should also consider dropping features for which reliable data are lacking, cannot be easily obtained, or contain significant spatial or other biases. Criteria for narrowing the list of potential conservation targets to those that will be most useful include:

  1. Validity: The target should be an element of conservation interest in its own right or have a well-documented or compelling relationship to such elements;
  2. Data availability and uniformity: Information on selected targets must be readily available as digital, spatial databases that are relatively uniform and continuous in distribution across the planning region in order to avoid biases; and
  3. Complementarity and comprehensiveness: The suite of targets selected should be complementary and span a broad spectrum of biodiversity or environmental variation (Noss 2004).

Step 5: Choose and implement a prioritization methodology

There are essentially three ways to prioritize sites, once the targets have been determined and the data collected:

  • Expert-based (use expert opinion or knowledge)
  • Site-selection algorithms
  • Some combination of algorithmic and expert approaches to gain advantages of both while avoiding biases.

Generally speaking, algorithmic approaches to site selection result in more cost-efficient and objective conservation networks than priorities developed by experts. On the other hand, reliance on expert opinion may be the only choice in regions where data are highly deficient. Use of experts is more reliable if the experts consider and synthesize information from the peer-reviewed literature, rather than simply relying on their opinions or “gut feeling.” Experts can also help identify key sites that don’t show up even in data-rich regions, and their “buy-in” may increase the chances for a plan’s acceptance and implementation. Considering these factors, Cowling et al. (2003) recommend integrating both algorithmic and expert-based approaches to prioritization.

Step 6: Use focal species and processes to determine or refine the spatial configuration of a conservation network

As noted in Step 3, one of the three main classes of conservation targets is focal species. Consideration of the life-history needs and processes of particular focal species often alters the conservation network design scenarios deemed “optimal” by site-selection algorithms. Although some site-selection algorithms consider connectivity to some extent, functional connectivity is very species-specific and landscape-specific. Identifying the species in a given landscape most sensitive to ecological disruption helps planners determine the overall area and configuration of sites required to maintain viable populations. Planners may then wish to employ spatially explicit population or metapopulation modeling, which can be combined with site-selection algorithms (Carroll et al. 2003) to determine connectivity requirements and other aspects of conservation network configuration. There are other useful approaches, however, for determining where to place landscape linkages (see Beier et al. 2008).

The operation of key natural processes, such as fire and hydrologic regimes, is another spatial consideration that might not be easy to incorporate into site-selection algorithms. Consultation with experts about key features of these processes and how to maintain them in the landscape of interest will be beneficial.

Step 7

Go Straight to Your State

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