Is the central-marginal hypothesis a general rule? Evidence from three distributions of an expanding mangrove species, Avicennia germinans (L.) L.
Kennedy, John Paul; Preziosi, Richard; Rowntree, Jennifer; Feller, Ilka (2020), Is the central-marginal hypothesis a general rule? Evidence from three distributions of an expanding mangrove species, Avicennia germinans (L.) L., Dryad, Dataset, https://doi.org/10.5061/dryad.69p8cz8xh
The central-marginal hypothesis (CMH) posits that range margins exhibit less genetic diversity and greater inter-population genetic differentiation compared to range cores. CMH predictions are based on long-held ‘abundant-centre’ assumptions of a decline in ecological conditions and abundances towards range margins. Although much empirical research has confirmed CMH, exceptions remain almost as common. We contend that mangroves provide a model system to test CMH that alleviates common confounding factors and may help clarify this lack of consensus. Here, we document changes in black mangrove (Avicennia germinans) population genetics with 12 nuclear microsatellite loci along three replicate coastlines in the United States (only 2 of 3 conform to underlying ‘abundant-centre’ assumptions). We then test an implicit prediction of CMH (reduced genetic diversity may constrain adaptation at range margins) by measuring functional traits of leaves associated with cold tolerance, the climatic factor that controls these mangrove distributional limits. CMH predictions were confirmed only along the coastlines that conform to ‘abundant-centre’ assumptions and, in contrast to theory, range margin A. germinans exhibited functional traits consistent with greater cold tolerance compared to range cores. These findings support previous accounts that CMH may not be a general rule across species and that reduced neutral genetic diversity at range margins may not be a constraint to physiological adaptation to context-specific environmental factors.
Genotype data - 1,083 Avicennia germinans (black mangrove) trees from 41 collection sites across the United States were genotyped at 12 nuclear microsatellite loci. Samples from East Florida (EFL) were collected in January 2015, from West Florida (WFL) in September-October 2015, and from Texas and Louisiana (TX-LA) in October 2015. Samples for two sites (code: TB, SFL) were obtained from preserved leaves collected in 2011. Collection sites with fewer samples (n = 9–11) were collected opportunistically between 2015 and 2016.
Functional trait data - 342 Avicennia germinans trees from 33 collection sites in East Florida (n = 18 sites), West Florida (n = 8 sites), and Texas and Louisiana (n = 7 sites) were sampled to measure five functional traits of leaves (area, length, width, ratio length:width, and specific leaf area). These trees are a subset of the same trees in the accompanying genotype data set. Traits were measured for 10 leaves per tree and the mean value for each tree is presented in the data set.
Genotype data - column 1: geographic region (TX-LA, Texas and Lousiana; WFL, West Florida; SFL, South Florida; EFL, East Florida); column 2: site (identification code for collection site); column 3: ID (identification code for sampled individual); column 4: lat (latitude at central point for each collection site); column 5: c_m (collection site classified as range core or range margin); column 6-29: multi-locus microsatellite genotype (12-loci). *NOTE: blank cells are missing data
Functional trait data - column 1: geographic region (TX-LA, Texas and Lousiana; WFL, West Florida; EFL, East Florida); column 2: site (identification code for collection site); column 3: lat (latitude at central point for each collection site); column 4: c_m (collection site classified as range core or range margin); column 5: area (leaf area, cm2); column 6: length (leaf length, cm); column 7: width (leaf width, cm); column 8: l_w (ratio of leaf length:width); column 9: dry (leaf dry weight, g); column 10: SLA (specific leaf area, cm2 g-1)
NASA Climate and Biological Response, Award: NX11AO94G
NSF MacroSystems Biology Program, Award: EF1065821