Terrestrial vertebrates as surrogates for selecting conservation areas in a biodiversity hotspot in Mexico (original) (raw)
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Conservation Science and Practice, 2024
Anthropogenic loss of biodiversity continues to increase worldwide, and existing conservation area networks (CANs) are inadequate for its adequate representation and persistence. To identify a set of new nominal conservation areas in Oaxaca, a Mesoamerican biodiversity hotspot in Mexico, for terrestrial vertebrate species, we used a multi-criteria systematic conservation planning approach. Besides minimizing the area incorporated into the nominal CAN, we incorporated 25 socioeconomic variables using multi-attribute value theory. We constructed a portfolio of nominal CAN solutions for four different scenarios all of which satisfied a 10% representation target for the modeled suitable habitat of each vertebrate species: (1) existing protected area-based (PA) solution; (2) voluntary conservation area-based (VCA) solution; (3) PAVCA solution; and (4) R-C solution (rarity-complementary algorithm). The PA-VCA and PA solutions were the most expensive in terms of area that had to be included in the nominal CANs (13,352 km2 and 12,587 km2, respectively). In all our multi-criteria analyses, highest costs were associated with maximizing the number of airports, amount of tourism, and length of available highways in a nominal CAN. We have thus established a portfolio of multicriteria solutions to the problem of creating an adequate CAN for the representation of terrestrial vertebrate species.
Diversity and Distributions, 2008
Oaxaca, located in south-west México within the Mesoamerican biodiversity hotspot, holds exceptionally high biodiversity for several taxa, including mammals. It has four decreed natural protected areas (NPAs) covering 5% of its total area, but only three of these, covering only 0.2% of the area, are strictly protected as National Parks. The current study develops ecological niche models for 183 terrestrial mammals for use as biodiversity surrogates in a systematic conservation planning exercise. Forty-five of these species were selected on the basis of their being either endangered or threatened or otherwise listed under the Mexican Red List or because they were endemic to either Oaxaca or to Mexico. The niche models were constructed with a machine-learning algorithm (GARP, Genetic Algorithm for Rule-Set Prediction) and refined by restricting each model to sites with suitable vegetation and habitat patches contiguous with known occurrences of the species. If the entire predicted geographical distribution of each of the 45 species listed above is put under protection, the entire state of Oaxaca gets included. Therefore, we imposed different constraints on the maximum area that can be put under protection (5–30% of the area of Oaxaca) and selected nominal conservation area networks based on different percentage representation targets for the species’ modelled distributions based on their conservation status (10–100%). The area selection utilized a rarity- and complementarity-based algorithm (in the ResNet software package). The goal was to have as many as possible of the 45 species at risk meet their specified representation targets in the budgeted area. The methods developed here combine ecological niche modelling and area prioritization algorithms for integrated conservation planning in a protocol that is suitable for other highly biodiverse regions.
Modelling spatial patterns of biodiversity for conservation prioritization in North���eastern Mexico
2004
Relationships between spatial patterns of bird and mammal species richness in northeastern Mexico were analysed in relation to the location of three biosphere reserves (El Abra-Tanchipa, El Cielo, and Sierra Gorda) and 13 priority areas recently identified for conservation. Ecological niches were modelled and potential distributions delimited for 285 bird and 114 mammal species using a genetic algorithm based on locality information from museum specimens and 15 selected environmental attributes. Potential distributions were transformed into hypothesized current distributions based on species-habitat associations as reflected in a recent land-use map. Although species richness was lower when distributions were reduced from potential to current, spatial patterns of potential and current richness were similar. Heuristic, complementarity-based prioritization procedures were used to identify combinations of areas and sites with maximal species representation: the biosphere reserves included 79% of birds and 74% of mammal species; eight priority areas provided an additional 11% of birds and 13% of mammals; the remaining 10% of birds and 13% of mammals were concentrated in new sites across the study area.
Diversity and …, 2008
Oaxaca, located in south-west México within the Mesoamerican biodiversity hotspot, holds exceptionally high biodiversity for several taxa, including mammals. It has four decreed natural protected areas (NPAs) covering 5% of its total area, but only three of these, covering only 0.2% of the area, are strictly protected as National Parks. The current study develops ecological niche models for 183 terrestrial mammals for use as biodiversity surrogates in a systematic conservation planning exercise. Forty-five of these species were selected on the basis of their being either endangered or threatened or otherwise listed under the Mexican Red List or because they were endemic to either Oaxaca or to Mexico. The niche models were constructed with a machine-learning algorithm (GARP, Genetic Algorithm for Rule-Set Prediction) and refined by restricting each model to sites with suitable vegetation and habitat patches contiguous with known occurrences of the species. If the entire predicted geographical distribution of each of the 45 species listed above is put under protection, the entire state of Oaxaca gets included. Therefore, we imposed different constraints on the maximum area that can be put under protection (5 -30% of the area of Oaxaca) and selected nominal conservation area networks based on different percentage representation targets for the species' modelled distributions based on their conservation status (10 -100%). The area selection utilized a rarityand complementarity-based algorithm (in the ResNet software package). The goal was to have as many as possible of the 45 species at risk meet their specified representation targets in the budgeted area. The methods developed here combine ecological niche modelling and area prioritization algorithms for integrated conservation planning in a protocol that is suitable for other highly biodiverse regions.
Identifying conservation priorities in Mexico through geographic information systems and modeling
Ecological …, 1995
Environmental assessments of regional development projects have been used in Mexico to determine where conflicts between conservation of biodiversity and resource extraction are likely to occur. Species-rich areas have been acknowledged as a priority for conservation. However, biological information is incomplete and biased toward accessible sites, so species-rich areas cannot be depicted directly from current biological knowledge.
Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species' geographic ranges to reduce the effect of biased sampling and partial knowledge about species' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network.
Biodiversity and Conservation, 2017
The objective of the present paper is to provide a holistic framework to delineate ''territories of opportunity'' where agrarian communities can manage areas to enhance the conservation of large vertebrates. The study was conducted Mexico, which is sociologically, culturally and ecologically complex, similar to other ''megadiverse'' countries. We conducted ensemble niche modeling of endangered top predators to define a set of large vertebrate species. Environmental attributes were used to perform three distance-based and two artificial intelligence-based algorithms. Socio-cultural attributes were included to depict agricultural communities with strong social government schemes and clear evidence of well-managed natural resources. Other socioeconomic attributes such as land acquisition cost, human agglomeration and anthropogenic land use were included in the analysis. Scenarios were computed and displayed cartographically with the aid of a geographic information system. Results showed that the largest concentration of biodiversity converges on regions with large land cover persistence and high local governance, defined as potential willingness to engage in conservation actions. The cartographic areas identified Communicated by Daniel Sanchez Mata. This article belongs to the Topical Collection: Biodiversity protection and reserves.
Ecological-Niche Modeling and Prioritization of Conservation-Area Networks for Mexican Herpetofauna.
bution of species and the variables determining those patterns. We used maximum-entropy niche modeling to run distribution models for 222 amphibian and 371 reptile species (49% endemics and 27% threatened) for which we had 34,619 single geographic records. The planning region is in southeastern Mexico, is 20% of the country's area, includes 80% of the country's herpetofauna, and lacks an adequate protected-area system. We used probabilistic data to build distribution models of herpetofauna for use in prioritizing conservation areas for three target groups (all species and threatened and endemic species). The accuracy of species-distribution models was better for endemic and threatened species than it was for all species. Forty-seven percent of the region has been deforested and additional conservation areas with 13.7% to 88.6% more native vegetation (76% to 96% of the areas are outside the current protected-area system) are needed. There was overlap in 26 of the main selected areas in the conservation-area network prioritized to preserve the target groups, and for all three target groups the proportion of vegetation types needed for their conservation was constant: 30% pine and oak forests, 22% tropical evergreen forest, 17% low deciduous forest, and 8% montane cloud forests. The fact that different groups of species require the same proportion of habitat types suggests that the pine and oak forests support the highest proportion of endemic and threatened species and should therefore be given priority over other types of vegetation for inclusion in the protected areas of southeastern Mexico.
Representing biodiversity: Data and procedures for identifying priority areas for conservation
Journal of Biosciences, 2002
Biodiversity priority areas together should represent the biodiversity of the region they are situated in. To achieve this, biodiversity has to be measured, biodiversity goals have to be set and methods for implementing those goals have to be applied. Each of these steps is discussed. Because it is impossible to measure all of biodiversity, biodiversity surrogates have to be used. Examples are taxa subsets , species assemblages and environmental domains. Each of these has different strengths and weaknesses, which are described and evaluated. In real-world priority setting, some combination of these is usually employed. While a desirable goal might be to sample all of biodiversity from genotypes to ecosystems, an achievable goal is to represent, at some agreed level, each of the biodiversity features chosen as surrogates. Explicit systematic procedures for implementing such a goal are described. These procedures use complementarity, a measure of the contribution each area in a region makes to the conservation goal, to estimate irreplaceability and flexibility, measures of the extent to which areas can be substituted for one another in order to take competing land uses into account. Persistence and vulnerability, which also play an important role in the priority setting process, are discussed briefly.
How well do the existing and proposed reserve networks represent vertebrate species in Chile?
Diversity and Distributions, 2007
Increasingly, biogeographical knowledge and analysis are playing a fundamental role in assessing the representativeness of biodiversity in protected areas, and in identifying critical areas for conservation. With almost 20% of the country assigned to protected areas, Chile is well above the conservation target (i.e. 10-12%) proposed by many international conservation organizations. Moreover, the Chilean government has recently proposed new conservation priority sites to improve the current protected area network. Here, we used all 653 terrestrial vertebrate species present in continental Chile to assess the performance of the existing and proposed reserve networks. Using geographical information systems, we overlaid maps of species distribution, current protected areas, and proposed conservation priority sites to assess how well each species is represented within these networks. Additionally, we performed a systematic reserve selection procedure to identify alternative conservation areas for expanding the current reserve system. Our results show that over 13% of the species are not covered by any existing protected area, and that 73% of Chilean vertebrate species can be considered partial gaps, with only a small fraction of their geographical ranges currently under protection. The coverage is also deficient for endemic (species confined to Chile) and threatened species. While the proposed priority sites do increase coverage, we found that there are still several gaps and these are not the most efficient choices. Both the gap analysis and the reserve selection analysis identified important areas to be added to the existing reserve system, mostly in northern and central Chile. This study underscores the need for a systematic conservation planning approach to redefine the conservation priority sites in order to maximize the representation of species, particularly endemic and threatened species.