Jennifer M. Morris , Peter C. Esselman , Catherine M. Riseng , Ashley K. Elgin , Mark D. Rowe
{"title":"从环境特征预测休伦湖 Dreissena spp.的空间分布模式","authors":"Jennifer M. Morris , Peter C. Esselman , Catherine M. Riseng , Ashley K. Elgin , Mark D. Rowe","doi":"10.1016/j.jglr.2024.102369","DOIUrl":null,"url":null,"abstract":"<div><p>Invasive dreissenid mussels (<em>Dreissena polymorpha</em> and <em>Dreissena rostriformis bugensis</em>) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict <em>Dreissena</em> spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with <em>Dreissena</em> spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.</p></div>","PeriodicalId":54818,"journal":{"name":"Journal of Great Lakes Research","volume":"50 4","pages":"Article 102369"},"PeriodicalIF":2.4000,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Lake Huron Dreissena spp. Spatial distribution patterns from environmental characteristics\",\"authors\":\"Jennifer M. Morris , Peter C. Esselman , Catherine M. Riseng , Ashley K. Elgin , Mark D. Rowe\",\"doi\":\"10.1016/j.jglr.2024.102369\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Invasive dreissenid mussels (<em>Dreissena polymorpha</em> and <em>Dreissena rostriformis bugensis</em>) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict <em>Dreissena</em> spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with <em>Dreissena</em> spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.</p></div>\",\"PeriodicalId\":54818,\"journal\":{\"name\":\"Journal of Great Lakes Research\",\"volume\":\"50 4\",\"pages\":\"Article 102369\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Great Lakes Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0380133024001187\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Great Lakes Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0380133024001187","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Predicting Lake Huron Dreissena spp. Spatial distribution patterns from environmental characteristics
Invasive dreissenid mussels (Dreissena polymorpha and Dreissena rostriformis bugensis) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.
期刊介绍:
Published six times per year, the Journal of Great Lakes Research is multidisciplinary in its coverage, publishing manuscripts on a wide range of theoretical and applied topics in the natural science fields of biology, chemistry, physics, geology, as well as social sciences of the large lakes of the world and their watersheds. Large lakes generally are considered as those lakes which have a mean surface area of >500 km2 (see Herdendorf, C.E. 1982. Large lakes of the world. J. Great Lakes Res. 8:379-412, for examples), although smaller lakes may be considered, especially if they are very deep. We also welcome contributions on saline lakes and research on estuarine waters where the results have application to large lakes.