Douchan Hanuise , Thomas Dobbelaere , Severine Choukroun , Michael A. Rasheed , Jonathan Lambrechts , Paul H. York , Timothy M. Smith , Robert G. Coles , Emmanuel Hanert , Alana Grech
{"title":"将种间特征整合到海草扩散的生物物理模型中","authors":"Douchan Hanuise , Thomas Dobbelaere , Severine Choukroun , Michael A. Rasheed , Jonathan Lambrechts , Paul H. York , Timothy M. Smith , Robert G. Coles , Emmanuel Hanert , Alana Grech","doi":"10.1016/j.ecolmodel.2025.111329","DOIUrl":null,"url":null,"abstract":"<div><div>The resilience of seagrass meadows strongly depends on the dispersal of their propagules, which fosters recovery and replenishment after disturbances. However, predicting dispersal patterns across dynamic coastal environments and large spatial and temporal scales remains challenging due to the lack of empirical observations. Biophysical models, integrating oceanic and atmospheric drivers with species-specific traits such as buoyancy and lifespan, are commonly used to simulate propagule transport. Yet, few studies account for the interspecific and interannual variability inherent in tropical seagrass ecosystems. Here we present a high-resolution seagrass biophysical dispersal model applied to 11 tropical seagrass species across the entire Great Barrier Reef World Heritage Area (GBRWHA), Australia, and run this model over a 6-year period (2011–2016). We use this model to assess how the interspecific variability in the buoyancy and windage of seagrass propagules affect their dispersal patterns and how these patterns further vary both seasonally and interannually. Our results reveal that species-specific factors such as their windage and buoyancy, as well as the season and region in which they disperse had the largest influence on dispersal distance. <em>H. spinulosa</em> and <em>S. isoetifolium</em> showed the greatest dispersal in the Whitsunday region, while the wet season promoted higher local retention due to lower wind speeds. From a management perspective, this highlights the need to account for species-specific information when devising seagrass management strategies. The outcomes of this research reveal the inherent complexities of predicting multi-species dispersal over large spatial and temporal scales, with broader implications for predicting dispersal in complex coastal ecosystems.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"510 ","pages":"Article 111329"},"PeriodicalIF":3.2000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating interspecific traits into biophysical models of seagrass dispersal\",\"authors\":\"Douchan Hanuise , Thomas Dobbelaere , Severine Choukroun , Michael A. Rasheed , Jonathan Lambrechts , Paul H. York , Timothy M. Smith , Robert G. Coles , Emmanuel Hanert , Alana Grech\",\"doi\":\"10.1016/j.ecolmodel.2025.111329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The resilience of seagrass meadows strongly depends on the dispersal of their propagules, which fosters recovery and replenishment after disturbances. However, predicting dispersal patterns across dynamic coastal environments and large spatial and temporal scales remains challenging due to the lack of empirical observations. Biophysical models, integrating oceanic and atmospheric drivers with species-specific traits such as buoyancy and lifespan, are commonly used to simulate propagule transport. Yet, few studies account for the interspecific and interannual variability inherent in tropical seagrass ecosystems. Here we present a high-resolution seagrass biophysical dispersal model applied to 11 tropical seagrass species across the entire Great Barrier Reef World Heritage Area (GBRWHA), Australia, and run this model over a 6-year period (2011–2016). We use this model to assess how the interspecific variability in the buoyancy and windage of seagrass propagules affect their dispersal patterns and how these patterns further vary both seasonally and interannually. Our results reveal that species-specific factors such as their windage and buoyancy, as well as the season and region in which they disperse had the largest influence on dispersal distance. <em>H. spinulosa</em> and <em>S. isoetifolium</em> showed the greatest dispersal in the Whitsunday region, while the wet season promoted higher local retention due to lower wind speeds. From a management perspective, this highlights the need to account for species-specific information when devising seagrass management strategies. The outcomes of this research reveal the inherent complexities of predicting multi-species dispersal over large spatial and temporal scales, with broader implications for predicting dispersal in complex coastal ecosystems.</div></div>\",\"PeriodicalId\":51043,\"journal\":{\"name\":\"Ecological Modelling\",\"volume\":\"510 \",\"pages\":\"Article 111329\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Modelling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304380025003151\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380025003151","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Integrating interspecific traits into biophysical models of seagrass dispersal
The resilience of seagrass meadows strongly depends on the dispersal of their propagules, which fosters recovery and replenishment after disturbances. However, predicting dispersal patterns across dynamic coastal environments and large spatial and temporal scales remains challenging due to the lack of empirical observations. Biophysical models, integrating oceanic and atmospheric drivers with species-specific traits such as buoyancy and lifespan, are commonly used to simulate propagule transport. Yet, few studies account for the interspecific and interannual variability inherent in tropical seagrass ecosystems. Here we present a high-resolution seagrass biophysical dispersal model applied to 11 tropical seagrass species across the entire Great Barrier Reef World Heritage Area (GBRWHA), Australia, and run this model over a 6-year period (2011–2016). We use this model to assess how the interspecific variability in the buoyancy and windage of seagrass propagules affect their dispersal patterns and how these patterns further vary both seasonally and interannually. Our results reveal that species-specific factors such as their windage and buoyancy, as well as the season and region in which they disperse had the largest influence on dispersal distance. H. spinulosa and S. isoetifolium showed the greatest dispersal in the Whitsunday region, while the wet season promoted higher local retention due to lower wind speeds. From a management perspective, this highlights the need to account for species-specific information when devising seagrass management strategies. The outcomes of this research reveal the inherent complexities of predicting multi-species dispersal over large spatial and temporal scales, with broader implications for predicting dispersal in complex coastal ecosystems.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).