Determining the community structure of the coral Seriatopora hystrix from hydrodynamic and genetic networks

Biophysical models resolution affects coral connectivity estimates

Estimating connectivity between coral reefs is essential to inform reef conservation and restoration. Given the vastness of coral reef ecosystems, connectivity can only be simulated with biophysical models whose spatial resolution is often coarser than the reef scale. Here, we assess the impact of biophysical models resolution on connectivity estimates by comparing the outputs of five different setups of the same model with resolutions ranging from 250 m to 4 km. We show that increasing the model resolution around reefs yields more complex and less directional dispersal patterns. With a fine-resolution model, connectivity graphs have more connections but of weaker strength. The resulting community structure therefore shows larger clusters of well-connected reefs. Virtual larvae also tend to stay longer close to their source reef with a fine-resolution model, leading to an increased local retention and self-recruitment for species with a short pre-competency period. Overall, only about half of the reefs with the largest connectivity indicator values are similar for the finest and coarsest resolution models. Our results suggest that reef management recommendations should only be made at scales coarser than the model resolution. Reef-scale recommendations can hence only be made with models not exceeding about 500 m resolution.

A Bayesian Network-based risk dynamic simulation model for accidental water pollution discharge of mine tailings ponds at watershed-scale

Mine tailings ponds that contain heavy metals are sources of potential risk to human security and ecosystem health. China particularly faces challenge of accidental water pollution risk from more than 8869 mine tailings ponds in serve by 2015, some of which are close to residential areas and other important infrastructures within 1 km downstream. To address watershed-scale risk assessment of accidental water pollution from mine tailings ponds, a Bayesian Network-based Risk Dynamic Simulation (BN-RDS) model was proposed to simulate "sources/stressors-receptors-endpoints" risk routes. An accidental water pollution convection-diffusion simulation was coupled to Bayesian Networks to perform the risk dynamic simulation and risk evolution quantification at watershed-scale. This method was applied to the risk assessment of 23 tailings dams in 12 sub-watersheds covering the Guanting Reservoir basin (the major backup drinking water source for Beijing) in Zhangjiakou City, China. The result indicated that ecosystem health and property security were the endpoints at the highest risk in the overall watershed. Spatially, the combined risk distribution map showed the risk was higher in the downstream of the Guanting Reservoir Watershed and in its two tributary basins (the Qingshui River and the Longyang River). This research highlighted a probabilistic approach to accidental water pollution risk assessment of tailings ponds with verifiable and tangible results for risk managers and stakeholders.

Identifying 'firebreaks' to fragment dispersal networks of a marine parasite

Marine ecosystems are beset by disease outbreaks, and efficient strategies to control dispersal of pathogens are scarce. We tested whether introducing no-farming areas or 'firebreaks' could disconnect dispersal networks of a parasitic disease affecting the world's largest marine fish farming industry (∼1000 farms). Larval salmon lice (Lepeophtheirus salmonis) are released from and transported among salmon farms by ocean currents, creating inter-farm networks of louse dispersal. We used a state-of-the-art biophysical model to predict louse movement along the Norwegian coastline and network analysis to identify firebreaks to dispersal. At least one firebreak that fragmented the network into two large unconnected groups of farms was identified for all seasons. During spring, when wild salmon migrate out into the ocean, and louse levels per fish at farms must be minimised, two effective firebreaks were created by removing 13 and 21 farms (1.3% and 2.2% of all farms in the system) at ∼61°N and 67°N, respectively. We have demonstrated that dispersal models coupled with network analysis can identify no-farming zones that fragment dispersal networks. Reduced dispersal pathways should lower infection pressure at farms, slow the evolution of resistance to parasite control measures, and alleviate infection pressure on wild salmon populations.

On the calculation of betweenness centrality in marine connectivity studies using transfer probabilities

Betweenness has been used in a number of marine studies to identify portions of sea that sustain the connectivity of whole marine networks. Herein we highlight the need of methodological exactness in the calculation of betweenness when graph theory is applied to marine connectivity studies based on transfer probabilities. We show the inconsistency in calculating betweeness directly from transfer probabilities and propose a new metric for the node-to-node distance that solves it. Our argumentation is illustrated by both simple theoretical examples and the analysis of a literature data set.

Sex-specific graphs: Relating group-specific topology to demographic and landscape data

Sex-specific genetic structure is a commonly observed pattern among vertebrate species. Facing differential selective pressures, individuals may adopt sex-specific life history traits that ultimately shape genetic variation among populations. Although differential dispersal dynamics are commonly detected in the literature, few studies have used genetic structure to investigate sex-specific functional connectivity. The recent use of graph theoretic approaches in landscape genetics has demonstrated network capacities to describe complex system behaviours where network topology represents genetic interaction among subunits. Here, we partition the overall genetic structure into sex-specific graphs, revealing different male and female dispersal dynamics of a fisher (Pekania [Martes] pennanti) metapopulation in southern Ontario. Our analyses based on network topologies supported the hypothesis of male-biased dispersal. Furthermore, we demonstrated that the effect of the landscape, identified at the population level, could be partitioned among sex-specific strata. We found that female connectivity was negatively correlated with snow depth, whereas connectivity among males was not. Our findings underscore the potential of conducting sex-specific analysis by identifying landscape elements or configuration that differentially promotes or impedes functional connectivity between sexes, revealing processes that may otherwise remain cryptic. We propose that the sex-specific graph approach would be applicable to other vagile species where differential sex-specific processes are expected to occur.

De Novo Assembly and Characterization of Four Anthozoan (Phylum Cnidaria) Transcriptomes

Many nonmodel species exemplify important biological questions but lack the sequence resources required to study the genes and genomic regions underlying traits of interest. Reef-building corals are famously sensitive to rising seawater temperatures, motivating ongoing research into their stress responses and long-term prospects in a changing climate. A comprehensive understanding of these processes will require extending beyond the sequenced coral genome (Acropora digitifera) to encompass diverse coral species and related anthozoans. Toward that end, we have assembled and annotated reference transcriptomes to develop catalogs of gene sequences for three scleractinian corals (Fungia scutaria, Montastraea cavernosa, Seriatopora hystrix) and a temperate anemone (Anthopleura elegantissima). High-throughput sequencing of cDNA libraries produced ~20-30 million reads per sample, and de novo assembly of these reads produced ~75,000-110,000 transcripts from each sample with size distributions (mean ~1.4 kb, N50 ~2 kb), comparable to the distribution of gene models from the coral genome (mean ~1.7 kb, N50 ~2.2 kb). Each assembly includes matches for more than half the gene models from A. digitifera (54-67%) and many reasonably complete transcripts (~5300-6700) spanning nearly the entire gene (ortholog hit ratios ≥0.75). The catalogs of gene sequences developed in this study made it possible to identify hundreds to thousands of orthologs across diverse scleractinian species and related taxa. We used these sequences for phylogenetic inference, recovering known relationships and demonstrating superior performance over phylogenetic trees constructed using single mitochondrial loci. The resources developed in this study provide gene sequences and genetic markers for several anthozoan species. To enhance the utility of these resources for the research community, we developed searchable databases enabling researchers to rapidly recover sequences for genes of interest. Our analysis of de novo assembly quality highlights metrics that we expect will be useful for evaluating the relative quality of other de novo transcriptome assemblies. The identification of orthologous sequences and phylogenetic reconstruction demonstrates the feasibility of these methods for clarifying the substantial uncertainties in the existing scleractinian phylogeny.

Developing best-practice Bayesian Belief Networks in ecological risk assessments for freshwater and estuarine ecosystems: a quantitative review

Bayesian Belief Networks (BBNs) are being increasingly used to develop a range of predictive models and risk assessments for ecological systems. Ecological BBNs can be applied to complex catchment and water quality issues, integrating multiple spatial and temporal variables within social, economic and environmental decision making processes. This paper reviews the essential components required for ecologists to design a best-practice predictive BBN in an ecological risk assessment (ERA) framework for aquatic ecosystems, outlining: (1) how to create a BBN for an aquatic ERA?; (2) what are the challenges for aquatic ecologists in adopting the best-practice applications of BBNs to ERAs?; and (3) how can BBNs in ERAs influence the science/management interface into the future? The aims of this paper are achieved using three approaches. The first is to demonstrate the best-practice development of BBNs in aquatic sciences using a simple nutrient model. The second is to discuss the limitations and challenges aquatic ecologists encounter when applying BBNs to ERAs. The third is to provide a framework for integrating best-practice BBNs into ERAs and the management of aquatic ecosystems. A quantitative review of the application and development of BBNs in aquatic science from 2002 to 2014 was conducted to identify areas where continued best-practice development is required. We outline a best-practice framework for the integration of BBNs into ERAs and study of complex aquatic systems.

Reproductive output and duration of the pelagic larval stage determine seascape-wide connectivity of marine populations

Connectivity among marine populations is critical for persistence of metapopulations, coping with climate change, and determining the geographic distribution of species. The influence of pelagic larval duration (PLD) on connectivity has been studied extensively, but relatively little is known about the influence of other biological parameters, such as the survival and behavior of larvae, and the fecundity of adults, on population connectivity. Furthermore, the interaction between the seascape (habitat structure and currents) and these biological parameters is unclear. We explore these interactions using a biophysical model of larval dispersal across the Indo-Pacific. We describe an approach that quantifies geographic patterns of connectivity from demographically relevant to evolutionarily significant levels across a range of species. We predict that at least 95% of larval settlement occurs within 155 km of the source population and within 13 days irrespective of the species' life history, yet long-distant connections remain likely. Self-recruitment is primarily driven by the local oceanography, larval mortality, and the larval precompetency period, whereas broad-scale connectivity is strongly influenced by reproductive output (abundance and fecundity of adults) and the length of PLD. The networks we have created are geographically explicit models of marine connectivity that define dispersal corridors, barriers, and the emergent structure of marine populations. These models provide hypotheses for empirical testing.