Searching for seadragons: predicting micro-habitat use for the common (weedy) seadragon (Phyllopteryx taeniolatus) based on habitat and prey.
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ABSTRACT:
SUBMITTER: Allan SJ
PROVIDER: S-EPMC9311067 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The common or weedy seadragon, Phyllopteryx taeniolatus, is an iconic and endemic fish found across temperate reefs of southern Australia. Despite its charismatic nature, few studies have been published, and the extent of population sub-structuring remains poorly resolved. Here we used 7462 single nucleotide polymorphisms (SNPs) to identify the extent of population structure in the weedy seadragon along the temperate southeast coast of Australia. We identified four populations, with strong genetic structure (FST = 0.562) between them. Both Discriminant Analysis of Principle Components (DAPC) and Bayesian clustering analyses support four distinct genetic clusters (north to south: central New South Wales, southern NSW, Victoria and Tasmania). In addition to these genetic differences, geographical variation in external morphology was recorded, with individuals from New South Wales shaped differently for a few measurements to those from the Mornington Peninsula (Victoria). We posit that these genetic and morphological differences suggest that the Victorian population of P. taeniolatus was historically isolated by the Bassian Isthmus during the last glacial maximum and should now be considered at least a distinct population. We also recorded high levels of genetic structure among the other locations. Based on the genomic and to a degree morphological evidence presented in this study, we recommend that the Victorian population be managed separately from the eastern populations (New South Wales and Tasmania).
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Project description:MOTIVATION: The prediction of biologically active compounds is of great importance for high-throughput screening (HTS) approaches in drug discovery and chemical genomics. Many computational methods in this area focus on measuring the structural similarities between chemical structures. However, traditional similarity measures are often too rigid or consider only global similarities between structures. The maximum common substructure (MCS) approach provides a more promising and flexible alternative for predicting bioactive compounds. RESULTS: In this article, a new backtracking algorithm for MCS is proposed and compared to global similarity measurements. Our algorithm provides high flexibility in the matching process, and it is very efficient in identifying local structural similarities. To predict and cluster biologically active compounds more efficiently, the concept of basis compounds is proposed that enables researchers to easily combine the MCS-based and traditional similarity measures with modern machine learning techniques. Support vector machines (SVMs) are used to test how the MCS-based similarity measure and the basis compound vectorization method perform on two empirically tested datasets. The test results show that MCS complements the well-known atom pair descriptor-based similarity measure. By combining these two measures, our SVM-based model predicts the biological activities of chemical compounds with higher specificity and sensitivity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Project description:Seadragons are a remarkable lineage of teleost fishes in the family Syngnathidae, renowned for having evolved male pregnancy. Comprising three known species, seadragons are widely recognized and admired for their fantastical body forms and coloration, and their specific habitat requirements have made them flagship representatives for marine conservation and natural history interests. Until recently, a gap has been the lack of significant genomic resources for seadragons. We have produced gene-annotated, chromosome-scale genome models for the leafy and weedy seadragon to advance investigations of evolutionary innovation and elaboration of morphological traits in seadragons as well as their pipefish and seahorse relatives. We identified several interesting features specific to seadragon genomes, including divergent noncoding regions near a developmental gene important for integumentary outgrowth, a high genome-wide density of repetitive DNA, and recent expansions of transposable elements and a vesicular trafficking gene family. Surprisingly, comparative analyses leveraging the seadragon genomes and additional syngnathid and outgroup genomes revealed striking, syngnathid-specific losses in the family of fibroblast growth factors (FGFs), which likely involve reorganization of highly conserved gene regulatory networks in ways that have not previously been documented in natural populations. The resources presented here serve as important tools for future evolutionary studies of developmental processes in syngnathids and hold value for conservation of the extravagant seadragons and their relatives.
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Project description:Predation risk is a strong driver of prey distribution and movement. However, fitness-influencing behaviours, such as mating, can alter risk and influence predator-prey space-use dynamics. In tree crickets, Oecanthus henryi, mate searching involves acoustic signalling by immobile males and phonotactic movement by females. Space-use patterns in tree crickets relative to their primary predators, green lynx spiders (Peucetia viridans), should therefore depend on their current mate-searching state; whether males are calling or non-calling and whether females are phonotactic or non-phonotactic. We first measured the degree of spatial anchoring of crickets to specific bushes in the field and determined whether that influenced the probability of broad-scale spatial overlap with spiders. In the absence of spiders, all crickets, independent of sex or male calling status, were found to be spatially anchored to specific types of bushes and not uniformly distributed on the landscape. At the broad spatial scale, spiders were more likely to be found on bushes with female crickets and, to a lesser degree, calling male crickets. At a finer spatial scale within a bush, movement strategies of crickets not only varied depending on the presence or absence of a spider, but also on their current mate-searching state. Phonotactic females showed clear predator avoidance, whereas calling and non-calling males moved towards the spider instead of away, similar to predator inspection behaviour seen in many taxa. As the strongly selected sex, males are more likely to undertake risky mate-searching activities, which includes inspection of predator positions. Overall, we found that all crickets were predictably anchored at the landscape scale, but their sex and mate-seeking behaviour influenced the degree of overlap with predators and their antipredator movement strategies. Reproductive strategies within a prey species, therefore, can alter predator-prey space race at multiple spatial scales.
| S-EPMC7542816 | biostudies-literature
Project description:The processes promoting disease in wild animal populations are highly complex, yet identifying these processes is critically important for conservation when disease is limiting a population. By combining field studies with epidemiologic tools, we evaluated the relationship between key factors impeding southern sea otter (Enhydra lutris nereis) population growth: disease and resource limitation. This threatened population has struggled to recover despite protection, so we followed radio-tagged sea otters and evaluated infection with 2 disease-causing protozoal pathogens, Toxoplasma gondii and Sarcocystis neurona, to reveal risks that increased the likelihood of pathogen exposure. We identified patterns of pathogen infection that are linked to individual animal behavior, prey choice, and habitat use. We detected a high-risk spatial cluster of S. neurona infections in otters with home ranges in southern Monterey Bay and a coastal segment near San Simeon and Cambria where otters had high levels of infection with T. gondii. We found that otters feeding on abalone, which is the preferred prey in a resource-abundant marine ecosystem, had a very low risk of infection with either pathogen, whereas otters consuming small marine snails were more likely to be infected with T. gondii. Individual dietary specialization in sea otters is an adaptive mechanism for coping with limited food resources along central coastal California. High levels of infection with protozoal pathogens may be an adverse consequence of dietary specialization in this threatened species, with both depleted resources and disease working synergistically to limit recovery.
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Project description:The dynamics of fish communities at tropical and sub-tropical rocky reefs are influenced in many cases by predation activity and predator-prey interactions. These processes usually follow specific diel patterns in reef areas with higher rates of these interactions occurring during the crepuscular periods. However, other factors such as habitat complexity and species-specific behavior may alter these patterns, increasing variability in species interactions. A better understanding of the dynamics of these patterns and processes would allow us to manage and monitor fish communities in these productive and vulnerable areas more efficiently. We investigated behavioral changes of predators and prey fish in sub-tropical "live-bottom" (sandstone) reefs at Gray's Reef National Marine Sanctuary (GRNMS), located 20 nautical miles off the coast of Georgia, USA, using fisheries acoustic methods in association with visual census and direct observation using SCUBA. Changes in co-location and habitat preferences of predators and prey over time throughout the diel cycle were investigated using species distribution models (MAXENT) based on habitat predictors and by means of spatial statistics. The results indicate that predator and prey distribution patterns changed considerably throughout the day. Prey and predator species exhibited complex spatial dynamics and behavior over diel periods, with prey modifying patterns of habitat use and spatial distribution, likely as a response of their interactions with predators. Crepuscular periods were confirmed to be the most active phases in terms of predator-prey interactions and consequently the most variable. The combination of tools and approaches used in this study provided valuable sources of information that support the inferences of predation risk-driven habitat selection of prey in this sub-tropical reef system.
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Project description:Algae-produced long-chain polyunsaturated fatty acids (LC-PUFA; with ≥20 carbon atoms) are key biomolecules for consumer production and animal health. They are transferred to higher trophic levels and accumulated in food chains. However, LC-PUFA accumulation in consumers and their trophic transfer vary with the diet quality and the physiological demand for LC-PUFA of consumers. The goal of this study was to investigate spatial and taxonomic differences in LC-PUFA retention of coastal fish predators that potentially differ in their habitat use (benthic versus pelagic) and prey quality. We analyzed the fatty acid (FA) composition of common fish species, namely roach and European perch, as well as their potential prey from benthic and pelagic habitats in three bays of the northern Baltic Sea. We then assessed whether the fish LC-PUFA retention differed between species and among the study bays with different diet quality, that is, LC-PUFA availability. Our data indicated taxon-specific differences in the retention of LC-PUFA and their precursor FA in fish (i.e., short-chain PUFA with <20 carbon atoms). Perch did not show any spatial variation in the retention of all these FA, while roach showed spatial differences in the retention of docosahexaenoic acid (DHA) and their precursor FA, but not eicosapentaenoic acid (EPA). Data suggest that diet quality and trophic reliance on benthic prey underlay the DHA retention differences in roach. Although the PUFA supply might differ among sites, the low spatial variation in LC-PUFA content of perch and roach indicates that both fishes were able to selectively retain dietary LC-PUFA. Climate change together with other existing human-caused environmental stressors are expected to alter the algal assemblages and lower their LC-PUFA supply for aquatic food webs. Our findings imply that these stressors will pose heterogeneous impacts on different fish predators. We advocate further investigations on how environmental changes would affect the nutritional quality of the basal trophic level, and their subsequent impacts on LC-PUFA retention, trophic ecology, and performance of individual fish species.
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Project description:BackgroundTandem mass spectrometry-based database searching has become an important technology for peptide and protein identification. One of the key challenges in database searching is the remarkable increase in computational demand, brought about by the expansion of protein databases, semi- or non-specific enzymatic digestion, post-translational modifications and other factors. Some software tools choose peptide indexing to accelerate processing. However, peptide indexing requires a large amount of time and space for construction, especially for the non-specific digestion. Additionally, it is not flexible to use.ResultsWe developed an algorithm based on the longest common prefix (ABLCP) to efficiently organize a protein sequence database. The longest common prefix is a data structure that is always coupled to the suffix array. It eliminates redundant candidate peptides in databases and reduces the corresponding peptide-spectrum matching times, thereby decreasing the identification time. This algorithm is based on the property of the longest common prefix. Even enzymatic digestion poses a challenge to this property, but some adjustments can be made to this algorithm to ensure that no candidate peptides are omitted. Compared with peptide indexing, ABLCP requires much less time and space for construction and is subject to fewer restrictions.ConclusionsThe ABLCP algorithm can help to improve data analysis efficiency. A software tool implementing this algorithm is available at http://pfind.ict.ac.cn/pfind2dot5/index.htm.
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Project description:Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 839 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory [corrected]. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors.
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Project description:The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations.
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