Daniel Gonzalez-Aragon , Richard Muñoz , Henry Houskeeper , Kyle Cavanaugh , Wirmer García-Tuñon , Laura Farías , Carlos Lara , Bernardo R. Broitman
{"title":"Seasonal and inter-annual dynamics of a Macrocystis pyrifera forest in Concepcion Bay, Chile","authors":"Daniel Gonzalez-Aragon , Richard Muñoz , Henry Houskeeper , Kyle Cavanaugh , Wirmer García-Tuñon , Laura Farías , Carlos Lara , Bernardo R. Broitman","doi":"10.1016/j.ecoinf.2025.103103","DOIUrl":null,"url":null,"abstract":"<div><div>Kelp forest are foundation species that deliver key ecosystem services for coastal habitats. Chile is one of the largest exporters of kelp biomass, which relies on the harvesting of wild populations. The vast and rugged coastline of Chile hinders field-based studies of the seasonal and spatial dynamics of kelp biomass, yet remote sensing approaches can provide an effective tool to study temporal patterns of kelp distribution and biomass. Our study aimed to establish the basic patterns of variation in the surface area and biomass of a <em>Macrocystis pyrifera</em> forest off Concepcion Bay, Central Chile. Using archival data from the Landsat series we constructed a long-term series of annual kelp canopy cover and assessed patterns of interannual, and a seasonal variation with the more recent Sentinel 2 data using Google Earth Engine. We validated satellite observations of the kelp forest in the field by recording local temperature and nutrient concentrations and through a sample of blades and stipes, which we used to estimate whole-individual <em>in situ</em> biomass through allometric relationships. Finally, we related decadal to interannual changes in canopy cover to local and regional drivers using data from public repositories. Our 24-year annual time series revealed large year-to-year variability in kelp forest area that did not show a significant association with different El Niño-Southern Oscillation indices, but the deviance explained increased notably with a 1-year lag. The seasonal time series exhibited clear seasonal patterns with cover peaking during summer. We found a significant influence of local environmental variables such as temperature, wave height, nitrate concentration, and solar radiation on kelp forest area. Furthermore, blade counts appeared as the most reliable metric for estimating <em>M. pyrifera</em> biomass. Interestingly, we found no evidence of temperature or nutrient stress during the summer biomass peak, hence seasonal variation in <em>M. pyrifera</em> abundance appears to be primarily influenced by solar radiation and wave activity in our study population. Our results provide a basis to derive seasonal time series across Chile’s kelp forests and suggest that understanding local stressors is key to ensure harvesting practices that promote the sustainable management of these key habitats. As ongoing climate change and overexploitation threaten kelp forest habitats, remote sensing emerges as a promising tool for the monitoring and management of extensive and remote coastlines.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"87 ","pages":"Article 103103"},"PeriodicalIF":5.8000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954125001128","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Kelp forest are foundation species that deliver key ecosystem services for coastal habitats. Chile is one of the largest exporters of kelp biomass, which relies on the harvesting of wild populations. The vast and rugged coastline of Chile hinders field-based studies of the seasonal and spatial dynamics of kelp biomass, yet remote sensing approaches can provide an effective tool to study temporal patterns of kelp distribution and biomass. Our study aimed to establish the basic patterns of variation in the surface area and biomass of a Macrocystis pyrifera forest off Concepcion Bay, Central Chile. Using archival data from the Landsat series we constructed a long-term series of annual kelp canopy cover and assessed patterns of interannual, and a seasonal variation with the more recent Sentinel 2 data using Google Earth Engine. We validated satellite observations of the kelp forest in the field by recording local temperature and nutrient concentrations and through a sample of blades and stipes, which we used to estimate whole-individual in situ biomass through allometric relationships. Finally, we related decadal to interannual changes in canopy cover to local and regional drivers using data from public repositories. Our 24-year annual time series revealed large year-to-year variability in kelp forest area that did not show a significant association with different El Niño-Southern Oscillation indices, but the deviance explained increased notably with a 1-year lag. The seasonal time series exhibited clear seasonal patterns with cover peaking during summer. We found a significant influence of local environmental variables such as temperature, wave height, nitrate concentration, and solar radiation on kelp forest area. Furthermore, blade counts appeared as the most reliable metric for estimating M. pyrifera biomass. Interestingly, we found no evidence of temperature or nutrient stress during the summer biomass peak, hence seasonal variation in M. pyrifera abundance appears to be primarily influenced by solar radiation and wave activity in our study population. Our results provide a basis to derive seasonal time series across Chile’s kelp forests and suggest that understanding local stressors is key to ensure harvesting practices that promote the sustainable management of these key habitats. As ongoing climate change and overexploitation threaten kelp forest habitats, remote sensing emerges as a promising tool for the monitoring and management of extensive and remote coastlines.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.