Applying genomic data to seagrass conservation

Abstract

Although genomic diversity is increasingly recognised as a key component of biodiversity, it is seldom used to inform conservation planning. Estuaries and keystone species such as the southern African seagrass, Zostera capensis, are under severe anthropogenic pressure and are often poorly protected. In this study we integrated SNP data generated from populations of Z. capensis across the South African coastline into the spatial prioritisation tool Marxan. We included different measures of genomic variation to account for genomic diversity, distinctness and evolutionary potential to explore spatial planning scenarios. We investigated how conservation priority areas identified by targeting only habitat type, differed from those identified by also including genomic measures; further we assessed how different genetic diversity metrics change prioritisation outcomes. All scenarios targeting genomic variation identified unique conservation prioritisation areas compared to scenarios only targeting habitat type. As such, omitting these estuaries from regional MPA networks risks the loss of evolutionarily important populations, threatening resilience and persistence of associated estuarine communities and their ecosystem services. We also observed a high degree of overlap between prioritisation outcomes across targeted measures of genomic variation. As such, by including even single measures of genomic variation, it may be possible to sufficiently represent the evolutionary processes behind the patterns of variation, while simplifying the conservation prioritisation procedure.

Comparative phylogeography in a marine biodiversity hotspot provides novel insights into evolutionary processes across the Atlantic‐Indian Ocean transition

“…Identifying multispecies patterns of genetic differentiation is particularly relevant for understanding regional processes that structure populations, and to disentangle the determinants of connectivity and gene flow in the marine environment at larger scales (Kuo & Avise, 2005; Manel et al, 2020). Furthermore, integrating community‐level genetic diversity and differentiation into spatial conservation plans and management is central to ensuring the success of long‐term conservation objectives (Nielsen et al, 2017; Phair et al, 2021; Thomson et al, 2021; von der Heyden, 2017).…”

Evaluating the evidence for ecological effectiveness of South Africa’s marine protected areas

“…However, we found that only 41% of the 41 MPAs occur within a 20-km radius of each other, with 32% within a 10-km radius. Such a rule-of-thumb comparison for the distribution of MPAs from each other naturally generalises, and does not take into account factors such as the oceanographic conditions of the South African seascape, including the effects of advection and retention by currents on larval dispersal and the implications for MPA effectiveness (Gaines et al 2003), or biogeographical barriers to genetic connectivity (von der Heyden 2009; Teske et al 2011;Phair et al 2021). However, it does underline challenges regarding MPA connectivity that have been previously highlighted (e.g.…”

Variation in genomic vulnerability to climate change across temperate populations of eelgrass (Zostera marina)

“…A more recent chromosome-level assembly using long-read sequencing improved the assembly length to 260.5Mb across six chromosomes and several unmapped scaffolds, with 21,483 annotated genes (Ma et al 2021). Poolseq has been successfully applied in other seagrasses such as Z. capensis (Phair et al 2019(Phair et al , 2021 using the Z. marina genome as a reference, with applications in habitat modelling and conservation.…”

“…To conserve distinct and isolated populations of Z. capensis , Phair et al (2021) integrated various measures of genomic diversity interpolated across geographic space with habitat type for conservation planning, finding that genetic variation was not captured by representativity of habitat alone. Phair et al (2021) concluded that omitting unique populations from the regional Marine Protected Area network could lead to the loss of evolutionarily significant populations and ultimately lead to reduced resilience across its range.…”

“…To conserve distinct and isolated populations of Z. capensis , Phair et al (2021) integrated various measures of genomic diversity interpolated across geographic space with habitat type for conservation planning, finding that genetic variation was not captured by representativity of habitat alone. Phair et al (2021) concluded that omitting unique populations from the regional Marine Protected Area network could lead to the loss of evolutionarily significant populations and ultimately lead to reduced resilience across its range. Complementing work to evaluate representativity and conservation of adaptive variation, analyses that associate environmental condition with genetic markers can be leveraged to predict the genomic vulnerability or offset (the difference between current and required genomic composition to adapt) of a species to predicted environmental change (Nielsen et al 2021, Rellstab et al, 2021.…”