Marine Biodiversity in the Caribbean: Regional Estimates and Distribution Patterns

This paper provides an analysis of the distribution patterns of marine biodiversity and summarizes the major activities of the Census of Marine Life program in the Caribbean region. The coastal Caribbean region is a large marine ecosystem (LME) characterized by coral reefs, mangroves, and seagrasses, but including other environments, such as sandy beaches and rocky shores. These tropical ecosystems incorporate a high diversity of associated flora and fauna, and the nations that border the Caribbean collectively encompass a major global marine biodiversity hot spot. We analyze the state of knowledge of marine biodiversity based on the geographic distribution of georeferenced species records and regional taxonomic lists. A total of 12,046 marine species are reported in this paper for the Caribbean region. These include representatives from 31 animal phyla, two plant phyla, one group of Chromista, and three groups of Protoctista. Sampling effort has been greatest in shallow, nearshore waters, where there is relatively good coverage of species records; offshore and deep environments have been less studied. Additionally, we found that the currently accepted classification of marine ecoregions of the Caribbean did not apply for the benthic distributions of five relatively well known taxonomic groups. Coastal species richness tends to concentrate along the Antillean arc (Cuba to the southernmost Antilles) and the northern coast of South America (Venezuela – Colombia), while no pattern can be observed in the deep sea with the available data. Several factors make it impossible to determine the extent to which these distribution patterns accurately reflect the true situation for marine biodiversity in general: (1) highly localized concentrations of collecting effort and a lack of collecting in many areas and ecosystems, (2) high variability among collecting methods, (3) limited taxonomic expertise for many groups, and (4) differing levels of activity in the study of different taxa

Preliminary Analyses

All statistical analyses will be performed using Statistical Package for the Social Sciences (SPSS, Version 25.0) software. Time will be coded as 0, 1, 2, and 4 to reflect surveys given at baseline, three months post-transplant, six months post-transplant, and twelve months post-transplant to account for the unequal amount of time between timepoints. Preliminary analyses will be completed to identify any missing data or outliers. The data will be evaluated for all assumptions related to the planned analyses including linear mixed models, Pearson r correlations, and Cox proportional hazard models. The following assumptions will be tested for linear mixed models. First, linearity will be tested by plotting the model residuals by the predictors (social support and treatment adherence). If the pattern in the plot is random, the assumption is met. However, if the pattern is non-random and follows a trend, predictors will be transformed. Next, homoscedasticity will be examined using scatter plots of the residual values. The assumption is met if the points are equally distributed linearly. QQ plots will test the assumption of normally distributed residuals in the model. The assumption is met if the residuals follow a linear pattern and do not deviate from the expected normal line. If the assumption is not met, log/ln transformations will be used to improve the normality of the data. The data will be evaluated for a linear relationship between the social support and treatment adherence trajectories by plotting a scatterplot for the slopes of both trajectories. The assumption is met if there is a straight-line relationship between the two variables. The proportional hazards assumption will be tested for Cox proportional hazard models. The proportional hazards assumption posits that the hazard ratio between two groups must remain constant over time and will be examined using Kaplan-Meier curves. If the curves cross, or the overall test of proportional hazards is significant, the proportional hazards assumption has been violated. Gender and age may be included as possible covariates in all analyses, given that they may explain variations in social support, treatment adherence, and survival. To determine if gender or age should be included as a covariate, bivariate correlation analyses will be performed between both potential covariates, gender and age, and the outcome variables, social support, treatment adherence, and longevity. If the possible covariates are correlated with the dependent variables at a large Pearson correlation greater than .5, they will be included in all analyses as covariates. However, if the Pearson correlation is not large, covariates will not be included in analyses

Vitamin D Supplementation Improves Mood in Women with Type 2 Diabetes

Objective. The aim of this study was to determine the effect of vitamin D supplementation on improving mood (depression and anxiety) and health status (mental and physical) in women with type 2 diabetes mellitus (T2DM). Methods. Fifty women with T2DM and significant depressive symptomology were enrolled into the “Sunshine Study,” where weekly vitamin D supplementation (ergocalciferol, 50,000 IU) was given to all participants for six months. The main outcomes included (1) depression (Center for Epidemiologic Studies Depression, CES-D, and Patient Health Questionnaire, PHQ-9), (2) anxiety (State-Trait Anxiety), and (3) health status (Short Form, SF-12). Results. Forty-six women (92%) completed all visits. There was a significant decrease in depression (CES-D and PHQ-9, p<0.001) and anxiety (state and trait, p<0.001). An improvement in mental health status (SF-12, p<0.001) was also found. After controlling for covariates (race, season of enrollment, baseline vitamin D, baseline depression (PHQ-9), and body mass index), the decline in depression remained significant (CES-D, p<0.001). There was a trend for a better response to supplementation for women who were not taking medications for mood (antidepressants or anxiolytics) (p=0.07). Conclusions. Randomized trials to confirm that vitamin D supplementation can improve mood and health status in T2DM women are needed

Montastraea annularis microsatellite data

Genotype data for 6 microsatellite loci for 871 samples of Montastraea annularis collected from 26 sites across the wider Caribbean are provided. Montastraea samples were collected in the field between 2004 and 2008. Sample ID, region and site name are supplied for each individual. Column headings are detailed in the ReadMe file

Data from: Connectivity of Caribbean coral populations: complementary insights from empirical and modelled gene flow

Understanding patterns of connectivity among populations of marine organisms is essential for the development of realistic, spatially explicit models of population dynamics. Two approaches, theoretical and empirical population genetic models, have been used to estimate levels of evolutionary connectivity among marine populations but rarely have their potentially-complementary insights been combined. Here, a spatially-realistic Lagrangian model of larval dispersal and a theoretical genetic model are integrated with the most extensive study of gene flow in a Caribbean marine organism. The 871 genets collected from 26 sites spread over the wider Caribbean sub-sampled 45.8% of the 1900 potential unique genets in the model. At a coarse scale, significant consensus between modelled estimates of genetic structure and empirical genetic data for populations of the reef-building coral Montastraea annularis is observed. However, modelled and empirical data differ in their estimates of connectivity among northern Mesoamerican reefs indicating that processes other than dispersal may dominate here. Further, the geographic location and porosity of the previously described east-west barrier to gene flow in the Caribbean is refined. A multi-prong approach, integrating genetic data and spatially-realistic models of larval dispersal and genetic projection, provides complementary insights into the processes underpinning population connectivity in marine invertebrates on evolutionary timescales