Planning for optimal conservation of geographical genetic variability within species

Abstract

Systematic Conservation Planning (SCP) involves a series of steps that should be accomplished to determine the most cost-effective way to invest in conservation action. Although SCP has been usually applied at the species level (or hierarchically higher), it is possible to use alleles from molecular analyses at the population level as basic units for analyses. Here we demonstrate how SCP procedures can be used to establish optimum strategies for in situ and ex situ conservation of a single species, using Dipteryx alata (a Fabaceae tree species widely distributed and endemics to Brazilian Cerrado) as a case study. Data for the analyses consisted in 52 alleles from eight microsatellite loci coded for a total of 644 individual trees sampled in 25 local populations throughout species' geographic range. We found optimal solutions in which seven local populations are the smallest set of local populations of D. alata that should be conserved to represent the known genetic diversity. Combining these several solutions allowed estimating the relative importance of the local populations for conserving all known alleles, taking into account the current land-use patterns in the region. A germplasm collection for this species already exists, so we also used SCP approach to identify the smallest number of populations that should be further collected in the field to complement the existing collection, showing that only four local populations should be sampled for optimizing the species ex situ representation. The initial application of the SCP methods to genetic data showed here can be a useful starting point for methodological and conceptual improvements and may be a first important step towards a comprehensive and balanced quantitative definition of conservation goals, shedding light to new possibilities for in situ and ex situ designs within species.

Demographic history and the low genetic diversity in Dipteryx alata (Fabaceae) from Brazilian Neotropical savannas

“…Under the present scenario of low gene flow, low genetic diversity and high population differentiation, decisions made on the conservation of D. alata should include allelic diversity and regional patterns of landscape fragmentation to establish corridors and improve connectivity among populations and potentially increasing effective population size (Diniz-Filho et al, 2012). Because allelic richness tends to decrease with distance from West Brazil, where one can find populations with the highest levels of allelic richness (for example, AMS, AQMS, CAMT, RAMT, SMS, Table 1), this region should be a priority in conservation planning, together with the RAGO and RAMT populations, where the vegetation is continuous.…”

“…Because allelic richness tends to decrease with distance from West Brazil, where one can find populations with the highest levels of allelic richness (for example, AMS, AQMS, CAMT, RAMT, SMS, Table 1), this region should be a priority in conservation planning, together with the RAGO and RAMT populations, where the vegetation is continuous. These populations have also been included in systematic conservation planning, to establish optimum strategies for in situ conservation of D. alata, as the smallest set of local population that should be conserved to represent the known genetic diversity (Diniz-Filho et al, 2012).…”

Exhaustive search for conservation networks of populations representing genetic diversity

“…However, there have also been discussions on how to conserve intraspecific genetic diversity, which began with the debate regarding the definitions of "evolutionarily significant units" and management units Telles, 2002, 2006). More recently, Diniz-Filho et al (2012) applied SCP reasoning to define a set of priorities at the population level using alleles from microsatellite loci as variables, where the goal was to establish the smallest number of local populations required to represent all known genetic diversity of the species (alleles). Schlottfeldt et al (2015a,b) developed a more complex model based on a set of multi-objective algorithms, which also allowed several properties of the populations to be optimized simultaneously.…”

Multi-objective optimization for plant germplasm collection conservation of genetic resources based on molecular variability

“…That study was pioneer in the use of information about allele frequency, heterozygosity, and Hardy-Weinberg equilibrium as objectives for simultaneous optimization. Diniz-Filho et al (2012b) used a mono-objective approach (in particular, simulated annealing) to find the Observe that for points B and C, it is not possible to obtain an improvement in one objective without a degradation of the other objective, i.e., f 1B < f 1C , f 2B > f 2C . The solutions (points) A, B, C, and D are optimal when f 1 and f 2 are considered.…”