The Value of Biodiversity in Reserve Selection: Representation, Species Weighting, and Benefit Functions

Abstract:  The limited availability of resources for conservation has led to the development of many quantitative methods for selecting reserves that aim to maximize the biodiversity value of reserve networks. In published analyses, species are often considered equal, although some are in much greater need of protection than others. Furthermore, representation is usually treated as a threshold: a species is either represented or not, but varying levels of representation over or under a given target level are not valued differently. We propose that a higher representation level should also have higher value. We introduce a framework for reserve selection that includes species weights and benefit functions for under- and overrepresentation (number of locations for each species). We applied the method to conservation planning for herb-rich forests in southern Finland. Our use of benefit functions and weighting changed the identity of about 50% of the selected sites at different funding levels and improved the representation of rare and threatened species. We also identified a small area of additional land that would substantially enhance the existing reserve network. We suggest that benefit functions and species weighting should be considered as standard options in reserve-selection applications.     

Costs of Integrating Economics and Conservation Planning

Abstract: Recent literature on systematic conservation planning has focused strongly on economics. It is a necessary component of efficient conservation planning because the question is about effective resource allocation. Nevertheless, there is an increasing tendency toward economic factors overriding biological considerations. Focusing too narrowly on economic cost may lead us back toward solutions resembling those obtained by opportunistic choice of areas, the avoidance of which was the motivation for development of systematic approaches. Moreover, there are many overlooked difficulties in incorporating economic considerations reliably into conservation planning because available economic data and the free market are complex. For instance, economies based on free markets tend to be shortsighted, whereas biodiversity conservation aims far into the future. Although economic data are necessary, they should not be relied on too heavily or considered separately from other sociopolitical factors. We suggest focusing on development of more‐comprehensive ecological‐economic modeling, while not forgetting the importance of purely biological analyses that are needed as a point of reference for evaluating conservation outcomes.     

Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents

The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.     

Quantifying the Indicator Power of an Indicator Species

Abstract:  Biodiversity indicator species are needed for classifying biotopes and sites for conservation, and a number of methods have been developed for determining indicator species for this purpose. Nevertheless, in addition to site classification, there is sometimes a need to define an indicator species that indicates the occurrence of another species. For example, when a species of interest (target species) is difficult to detect or identify, a reliable indicator species can function as a tool that saves time and money. We derived a method that provides a quantitative measure of the indicator power (IP) of an indicator species for the target species or any species assemblage. We calculated the measure of IP from a presence–absence matrix that covered several sites. The method provided a list of indicator species, the presence of which reliably indicated the presence of another species (e.g., a threatened or rare species in a given area). The IP of the species was highest when the number of shared occurrences between the indicator species and the target species was high and, simultaneously, when the indicator species and the target species occurred separately in only a few cases. The IP was also positively influenced by the number of sites with no occurrences of either the indicator or the target species. Our method can also be used to quantify different types of species occurrence indications. We refer to these types as presence–presence, presence–absence, absence–presence, and absence–absence indications. To clarify the use of the method, we examined the situation with red-listed polypores in White-backed Woodpecker (Dendrocopos leucotos) habitats in Fennoscandia and found some suitable indicator species. Our method provides a new, objective way to evaluate the IP of an indicator species.     

Area-Based Refinement for Selection of Reserve Sites with the Benefit-Function Approach

Abstract:  Optimization of resource use is necessary for efficient conservation planning. Many reserve-selection algorithms aim to identify representative but inexpensive networks, which may lead to selecting small sites due to their lower costs and collectively higher species richness. Nevertheless, larger sites would be preferable regarding species' long-term persistence. An area-based refinement can be used to overcome this problem. We used a reserve-planning framework in which continuous benefit functions valued representation (numbers of populations), and differential species weights were based on a species' local rarity and threatened status. We introduced a refinement based on the species-area relationship that provides relatively higher values for larger sites. We applied the proposed method to rich fen vegetation in southern Finland. The species-area refinement resulted in a network of significantly larger sites with minor trade-offs with representation (numbers of populations). Giving endangered species higher weights ensured that the trade-off occurred mostly between site size and representation of low-priority species. We recommend using a species-area refinement for practical, maximum-coverage conservation planning.