{"title":"在监测良好的生态系统中记录变量相对影响的净生态系统交换比较分析","authors":"David A. Wood","doi":"10.1016/j.ecocom.2022.100998","DOIUrl":null,"url":null,"abstract":"<div><p>Weekly averaged datasets from fourteen AmeriFlux ecosystem monitoring sites spread across the Americas, processed to the FLUXNET2015 standard, are statistically evaluated to characterize their seasonal net ecosystem exchange (NEE) trends. The sites cover wetland, cropland, woodland, grassland and tundra ecosystems. Up to twenty measured variables from the sites are variously correlated with NEE. A comparison of Pearson and Spearman correlation coefficients reveals that the variables are behaving parametrically with respect to NEE for the wetland, woodland (two out of three sites) and tundra locations, but non-parametrically for cropland and grassland sites. Multi-linear regression (MLR) analysis also distinguishes those ecosystems. MLR predicted versus calculated NEE follow <em>Y</em> ≈ <em>X</em> relationships for the wetland and tundra sites, whereas for the other ecosystems the MLR results follow Y≠X trends. Moreover, the coefficient values of the MLR optimum solutions for each ecosystem reveal quite distinct relative influences of the measured variables on the NEE predicted values. These results imply that NEE at wetland and tundra sites can be relatively easily predicted from the FLUXNET2015 set of recorded variables. On the other hand, the other three types of ecosystem sites cannot be easily predicted from those variables, implying that other factors substantially influence NEE at those sites.</p></div>","PeriodicalId":50559,"journal":{"name":"Ecological Complexity","volume":"50 ","pages":"Article 100998"},"PeriodicalIF":3.1000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Net ecosystem exchange comparative analysis of the relative influence of recorded variables in well monitored ecosystems\",\"authors\":\"David A. Wood\",\"doi\":\"10.1016/j.ecocom.2022.100998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Weekly averaged datasets from fourteen AmeriFlux ecosystem monitoring sites spread across the Americas, processed to the FLUXNET2015 standard, are statistically evaluated to characterize their seasonal net ecosystem exchange (NEE) trends. The sites cover wetland, cropland, woodland, grassland and tundra ecosystems. Up to twenty measured variables from the sites are variously correlated with NEE. A comparison of Pearson and Spearman correlation coefficients reveals that the variables are behaving parametrically with respect to NEE for the wetland, woodland (two out of three sites) and tundra locations, but non-parametrically for cropland and grassland sites. Multi-linear regression (MLR) analysis also distinguishes those ecosystems. MLR predicted versus calculated NEE follow <em>Y</em> ≈ <em>X</em> relationships for the wetland and tundra sites, whereas for the other ecosystems the MLR results follow Y≠X trends. Moreover, the coefficient values of the MLR optimum solutions for each ecosystem reveal quite distinct relative influences of the measured variables on the NEE predicted values. These results imply that NEE at wetland and tundra sites can be relatively easily predicted from the FLUXNET2015 set of recorded variables. On the other hand, the other three types of ecosystem sites cannot be easily predicted from those variables, implying that other factors substantially influence NEE at those sites.</p></div>\",\"PeriodicalId\":50559,\"journal\":{\"name\":\"Ecological Complexity\",\"volume\":\"50 \",\"pages\":\"Article 100998\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Complexity\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1476945X22000204\",\"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 Complexity","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476945X22000204","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}
Net ecosystem exchange comparative analysis of the relative influence of recorded variables in well monitored ecosystems
Weekly averaged datasets from fourteen AmeriFlux ecosystem monitoring sites spread across the Americas, processed to the FLUXNET2015 standard, are statistically evaluated to characterize their seasonal net ecosystem exchange (NEE) trends. The sites cover wetland, cropland, woodland, grassland and tundra ecosystems. Up to twenty measured variables from the sites are variously correlated with NEE. A comparison of Pearson and Spearman correlation coefficients reveals that the variables are behaving parametrically with respect to NEE for the wetland, woodland (two out of three sites) and tundra locations, but non-parametrically for cropland and grassland sites. Multi-linear regression (MLR) analysis also distinguishes those ecosystems. MLR predicted versus calculated NEE follow Y ≈ X relationships for the wetland and tundra sites, whereas for the other ecosystems the MLR results follow Y≠X trends. Moreover, the coefficient values of the MLR optimum solutions for each ecosystem reveal quite distinct relative influences of the measured variables on the NEE predicted values. These results imply that NEE at wetland and tundra sites can be relatively easily predicted from the FLUXNET2015 set of recorded variables. On the other hand, the other three types of ecosystem sites cannot be easily predicted from those variables, implying that other factors substantially influence NEE at those sites.
期刊介绍:
Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales.
Ecological Complexity will publish research into the following areas:
• All aspects of biocomplexity in the environment and theoretical ecology
• Ecosystems and biospheres as complex adaptive systems
• Self-organization of spatially extended ecosystems
• Emergent properties and structures of complex ecosystems
• Ecological pattern formation in space and time
• The role of biophysical constraints and evolutionary attractors on species assemblages
• Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory
• Ecological topology and networks
• Studies towards an ecology of complex systems
• Complex systems approaches for the study of dynamic human-environment interactions
• Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change
• New tools and methods for studying ecological complexity