Johanna G. Kuhne , Patrick J. O’Connor , Jasmin G. Packer , Thomas A.A. Prowse
{"title":"量化温带生态系统植被状况的环境驱动因素可改善对管理影响的检测","authors":"Johanna G. Kuhne , Patrick J. O’Connor , Jasmin G. Packer , Thomas A.A. Prowse","doi":"10.1016/j.ecolind.2024.112783","DOIUrl":null,"url":null,"abstract":"<div><div>Disentangling the effects of environmental variation and management actions on vegetation condition is increasingly important given increasing efforts to tackle biodiversity loss and the advent of environmental accounting programs. The Mount Lofty Ranges (South Australia) contains temperate ecosystems supporting rich but threatened biodiversity. Using 15 years of vegetation monitoring, we quantified drivers of and trends in four indicators of vegetation health; native species richness, vegetation structure, regeneration, tree habitat quality, and two indicators of vegetation threats; grazing pressure and weed species richness. After correcting for differences between vegetation communities, we found all indicators were significantly associated with environmental variables. Seasonal effects were found for native and weed species richness and vegetation structure with peaks in spring. Significant spatial effects for native and weed species richness, vegetation structure and grazing scores reflect historic and current land use. Rainfall in the year before a survey resulted in higher native and weed species richness and higher grazing scores. To demonstrate the application of model-based correction factors when monitoring vegetation change in this system, we simulated a management-induced native species gain and tested the capacity of different before-after survey regimes to detect this gain under environmental variability. Across sites, model-based corrections increased the probability of detecting the simulated gain by c. 8% and reduced the variance in this probability approximately six-fold. Our results quantify the effects of environmental drivers on vegetation in the study region and highlight the improved capacity to detect the true effects of management actions through model-based adjustments for environmental drivers.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"168 ","pages":"Article 112783"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying environmental drivers of vegetation condition in a temperate ecosystem can improve detection of management impacts\",\"authors\":\"Johanna G. Kuhne , Patrick J. O’Connor , Jasmin G. Packer , Thomas A.A. Prowse\",\"doi\":\"10.1016/j.ecolind.2024.112783\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Disentangling the effects of environmental variation and management actions on vegetation condition is increasingly important given increasing efforts to tackle biodiversity loss and the advent of environmental accounting programs. The Mount Lofty Ranges (South Australia) contains temperate ecosystems supporting rich but threatened biodiversity. Using 15 years of vegetation monitoring, we quantified drivers of and trends in four indicators of vegetation health; native species richness, vegetation structure, regeneration, tree habitat quality, and two indicators of vegetation threats; grazing pressure and weed species richness. After correcting for differences between vegetation communities, we found all indicators were significantly associated with environmental variables. Seasonal effects were found for native and weed species richness and vegetation structure with peaks in spring. Significant spatial effects for native and weed species richness, vegetation structure and grazing scores reflect historic and current land use. Rainfall in the year before a survey resulted in higher native and weed species richness and higher grazing scores. To demonstrate the application of model-based correction factors when monitoring vegetation change in this system, we simulated a management-induced native species gain and tested the capacity of different before-after survey regimes to detect this gain under environmental variability. Across sites, model-based corrections increased the probability of detecting the simulated gain by c. 8% and reduced the variance in this probability approximately six-fold. Our results quantify the effects of environmental drivers on vegetation in the study region and highlight the improved capacity to detect the true effects of management actions through model-based adjustments for environmental drivers.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"168 \",\"pages\":\"Article 112783\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X24012408\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X24012408","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Quantifying environmental drivers of vegetation condition in a temperate ecosystem can improve detection of management impacts
Disentangling the effects of environmental variation and management actions on vegetation condition is increasingly important given increasing efforts to tackle biodiversity loss and the advent of environmental accounting programs. The Mount Lofty Ranges (South Australia) contains temperate ecosystems supporting rich but threatened biodiversity. Using 15 years of vegetation monitoring, we quantified drivers of and trends in four indicators of vegetation health; native species richness, vegetation structure, regeneration, tree habitat quality, and two indicators of vegetation threats; grazing pressure and weed species richness. After correcting for differences between vegetation communities, we found all indicators were significantly associated with environmental variables. Seasonal effects were found for native and weed species richness and vegetation structure with peaks in spring. Significant spatial effects for native and weed species richness, vegetation structure and grazing scores reflect historic and current land use. Rainfall in the year before a survey resulted in higher native and weed species richness and higher grazing scores. To demonstrate the application of model-based correction factors when monitoring vegetation change in this system, we simulated a management-induced native species gain and tested the capacity of different before-after survey regimes to detect this gain under environmental variability. Across sites, model-based corrections increased the probability of detecting the simulated gain by c. 8% and reduced the variance in this probability approximately six-fold. Our results quantify the effects of environmental drivers on vegetation in the study region and highlight the improved capacity to detect the true effects of management actions through model-based adjustments for environmental drivers.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.