Reef monitoring programmes often focus on limited sites, predominantly on reef slope areas, which do not capture compositional variability across zones. This study assessed spatial and temporal changes in hard coral cover at four hierarchical spatial scales. ~ 55,000, geo-referenced photoquadrats were collected annually from 2002 to 2018 and analysed using artificial intelligence for 31 sites across reef flat and reef slope zones on Heron Reef, Southern Great Barrier Reef, Australia. Trends in hard coral cover were examined at three spatial scales: (1) “reef scale”, all data; (2) “geomorphic zone scale”—north/south reef slope, inner/outer reef flat; and (3) “site scale”—31 sites. Coral cover trajectories were also examined at: (4) “sub-site scale”—sub-division of sites into 567 sub-sites, to estimate variability in coral cover trajectories via spatial statistical modelling. At reef scale coral cover increased over time to 25.6 ± 0.4 SE % in 2018 but did not recover following disturbances caused by disease (2004–2008), cyclonic conditions (2009) or severe storms (2015) to the observed pre-disturbance level (44.0 ± 0.7 SE %) seen in 2004. At geomorphic zone scale, the reef slope had significantly higher coral cover than the reef flat. Trends of decline and increase were visible in the slope zones, and the southern slope recovered to pre-decline levels. Variable coral cover trends were visible at site scale. Furthermore, sub-site spatial modelling captured eight years of coral recovery that occurred at different times and magnitudes across the four geomorphic zones, effectively estimating variability in the trajectory of the reef’s coral community. Derived spatial predictions for the entire reef show patchy coral recovery, particularly on the southern slope, and that recovery hotspots are distributed across the reef. These findings suggest that to fully understand and interpret coral decline or recovery on a reef, more accurate assessment can be achieved by examining sites distributed within different geomorphic zones to capture variation in exposure, depth and consolidation.
The migration-selection balance often governs the evolution of lineages, and speciation with gene flow is now considered common across the tree of life. Ecological speciation is a process that can facilitate divergence despite gene flow due to strong selective pressures caused by ecological differences; however, the exact traits under selection are often unknown. The transition from freshwater to saltwater habitats provides strong selection targeting traits with osmoregulatory function. Several lineages of North American watersnakes (Nerodia spp.) are known to occur in saltwater habitat and represent a useful system for studying speciation by providing an opportunity to investigate gene flow and evaluate how species boundaries are maintained or degraded. We use double digest restriction-site associated DNA sequencing to characterize the migration-selection balance and test for evidence of ecological divergence within the Nerodia fasciata-clarkii complex in Florida. We find evidence of high intraspecific gene flow with a pattern of isolation-by-distance underlying subspecific lineages. However, we identify genetic structure indicative of reduced gene flow between inland and coastal lineages suggesting divergence due to isolation-by-environment. This pattern is consistent with observed environmental differences where the amount of admixture decreases with increased salinity. Furthermore, we identify significantly enriched terms related to osmoregulatory function among a set of candidate loci, including several genes that have been previously implicated in adaptation to salinity stress. Collectively, our results demonstrate that ecological differences, likely driven by salinity, cause strong divergent selection which promotes divergence in the N. fasciata-clarkii complex despite significant gene flow. 相似文献
Recent technical advances combined with novel computational approaches have promised the acceleration of our understanding of the tree of life. However, when it comes to hyperdiverse and poorly known groups of invertebrates, studies are still scarce. As published phylogenies will be rarely challenged by future taxonomists, careful attention must be paid to potential analytical bias. We present the first molecular phylogenetic hypothesis for the family Chalcididae, a group of parasitoid wasps, with a representative sampling (144 ingroups and seven outgroups) that covers all described subfamilies and tribes, and 82% of the known genera. Analyses of 538 Ultra‐Conserved Elements (UCEs) with supermatrix (RAx ML and IQTREE) and gene tree reconciliation approaches (ASTRAL, ASTRID) resulted in highly supported topologies in overall agreement with morphology but reveal conflicting topologies for some of the deepest nodes. To resolve these conflicts, we explored the phylogenetic tree space with clustering and gene genealogy interrogation methods, analyzed marker and taxon properties that could bias inferences and performed a thorough morphological analysis (130 characters encoded for 40 taxa representative of the diversity). This joint analysis reveals that UCEs enable attainment of resolution between ancestry and convergent/divergent evolution when morphology is not informative enough, but also shows that a systematic exploration of bias with different analytical methods and a careful analysis of morphological features is required to prevent publication of artifactual results. We highlight a GC content bias for maximum‐likelihood approaches, an artifactual mid‐point rooting of the ASTRAL tree and a deleterious effect of high percentage of missing data (>85% missing UCEs) on gene tree reconciliation methods. Based on the results we propose a new classification of the family into eight subfamilies and ten tribes that lay the foundation for future studies on the evolutionary history of Chalcididae. 相似文献
Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban–agricultural and rural agricultural sites in central Ohio, USA. In cross‐validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine‐grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes. 相似文献
Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ . 相似文献