Strategic Planning for Species Conservation: A Handbook - IUCN

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Strategic Planning for Species Conservation 5.3.4.2 Current Distribution (including Extent of occurrence and Area of occupancy) Although recent survey locations (5.3.4.1) provide the most precise information about species distribution, they usually represent only samples from a larger geographic distribution. For planning purposes, it is useful to have distribution maps which convey the current distribution of the species in a manner which is comparable with the historical distribution. These current distribution maps can be developed in a few different ways. The Red List Criteria for Critically Endangered, Endangered, and Vulnerable Species refer, among other parameters, to “extent of occurrence” and “area of occupancy”. Extent of occurrence is defined as the “area contained within the shortest continuous imaginary boundary which can be drawn to encompass all the known, inferred or projected sites of present occurrence of a species, excluding cases of vagrancy� This measure may exclude discontinuities or disjunctions within the overall distributions of taxa (e.g., large areas of obviously unsuitable habitat). � Extent of occurrence can often be measured by a minimum convex polygon (the smallest polygon in which no internal angle exceeds 180 degrees and which contains all the sites of occurrence).” The Red List term “area of occupancy” is defined as “the area within its 'extent of occurrence' � which is occupied by a taxon, excluding cases of vagrancy. The measure reflects the fact that a taxon will not usually occur throughout the area of its extent of occurrence, which may contain unsuitable or unoccupied habitats. The size of the area of occupancy will be a function of the scale at which it is measured, and should be at a scale appropriate to relevant biological aspects of the taxon, the nature of threats and the available data.” The Red List guidelines recommend that to avoid inconsistencies and bias in assessments caused by estimating area of occupancy at different scales, estimates should be standardized by applying a scale-correction factor. How exactly standardization should be done depends on the scale-area relationships of the different taxa of concern (IUCN 2001). Several statistical methods exist for extrapolating from point data across larger geographic regions. These methods vary in the number and types of observations required, in the types of ancillary environmental and human geographic data needed, and in their assumptions about the statistical properties of the species’ distribution. Commonly used “species distribution models” are MAXENT (maximum-entropy approach for species habitat modelling; Phillips, Anderson, and Schapire 2006), regression models (Scott, Heglund, and Morrison 2002), GARP (Genetic Algorithm for Rule-set Production; Stockwell and Peters 1999), and bio-climatic envelope models (Pearson and Dawson 2003). Appropriate training and software are required to use these techniques successfully. Moreover, ground-truthing is required to check model predictions. In addition to such predictive models of species distribution, various “expert-based” methods have also been employed, which take into account not only the occurrence data but less precise information about habitat status, human pressure, and other less quantifiable factors. Although less computationally intensive and more conducive to application in a workshop setting, expert-based methods are subjective, susceptible to peer pressure, and can mask differences in interpretation between different experts. These disadvantages mean that expert-based methods may be less replicable than empirical methods. Although statistical methods are more replicable, given that they are appropriately documented, such methods are not entirely without bias, as choices are still required about which method to use, the underlying assumptions of the method, and the quality and type of other data used in the analysis. Statistical models can also be less transparent, requiring specialist knowledge to interpret correctly; and they are less conducive to building a community of stakeholders with a shared purpose. 29
Figure 5.3 Map of the current distribution of jaguars Source: Sanderson et al. 2002. 30 5. Status Review Additionally, the two methods will vary in their reliability according to the threats which have shaped the species’ current distribution. For example, if a species is closely tied to a particular habitat type, and is threatened primarily because that habitat type is being destroyed, the modelling approach might be well suited to predicting the species’ current distribution. In contrast, if the species’ distribution has been reduced by some factor which is less readily mapped, such as episodic (but unpredictable) disease epidemics, or hunting by particular groups of people (not well captured by maps of human density), then predictive models might provide very inaccurate projections. However current distribution maps are developed, they too should be attributed regarding sources, time period, method by which they were created and certainty. An example of the data form associated with a current range distribution assessment for jaguars can be downloaded at http:// intranet.iucn.org/webfiles/doc/SSC/SCS/ Ch5_jaguar_forms.pdf, and for cheetah and African wild dogs, available at http:// intranet.iucn.org/webfiles/docs/SSC/SCS/Ch5_cheetwd_forms.pdf. . A suggested set of certainty measures associated with current distribution areas is provided in Blanc et al. (2007). An additional example is provided by the system used for the Asian Wild Cattle and Buffaloes Status Review, available at http://intranet.iucn.org/webfiles/docs/SSC/SCS/ Ch5_AWCB_forms.pdf. Figure 5.3. shows an example of a map of the current distribution of the jaguar. 5.3.4.3 Identifying Populations Species are rarely uniformly distributed across their ranges; clumps, patches, or other definable areas can be used to distinguish populations 4 . Individual populations are often the focus of conservation effort and are the basic units of the SCS. Populations may be defined through genetic testing (Moritz 1994; Avise 2000), but are more frequently, though less exactly, defined through geographic analysis and field experience. Some populations are simply defined by convenient boundaries, such as a reserve or other administrative unit, rather than by some biological criteria. If populations represent different subspecies or other genetic units below the species level, that fact should be noted for each population. 4 The Red List Criteria use the term “population” differently, specifically referring to the total number of (mature) individuals of the taxon. On the other hand, the Criteria define subpopulations as geographically or otherwise distinct groups in the population between which there is little demographic or genetic exchange (typically one successful migrant individual or gamete per year or less) (see IUCN 2001).
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IUCN, International Union for Conse
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Strategic Planning for Species Conservation: A Handbook - IUCN

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