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

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2024-11-01 DOI:10.1016/j.ecolind.2024.112783
Johanna G. Kuhne , Patrick J. O’Connor , Jasmin G. Packer , Thomas A.A. Prowse
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引用次数: 0

摘要

随着解决生物多样性丧失问题的力度不断加大以及环境核算计划的出现,厘清环境变化和管理措施对植被状况的影响变得越来越重要。南澳大利亚洛福迪山脉(Mount Lofty Ranges)的温带生态系统支持着丰富但濒临灭绝的生物多样性。通过 15 年的植被监测,我们量化了四项植被健康指标(本地物种丰富度、植被结构、植被再生、树木栖息地质量)和两项植被威胁指标(放牧压力和杂草物种丰富度)的动因和趋势。在对植被群落间的差异进行校正后,我们发现所有指标都与环境变量有显著关联。在原生物种和杂草物种丰富度以及植被结构方面,我们发现季节效应在春季达到高峰。本地物种和杂草物种丰富度、植被结构和放牧评分的空间效应显著,反映了历史和当前的土地利用情况。调查前一年的降雨导致更高的本地物种和杂草物种丰富度以及更高的放牧评分。为了证明基于模型的校正因子在监测该系统植被变化时的应用,我们模拟了由管理引起的本地物种增加,并测试了不同的前后调查制度在环境变化下检测这种增加的能力。在各个地点,基于模型的校正将检测到模拟增殖的概率提高了约 8%,并将这一概率的方差缩小了约六倍。我们的结果量化了环境驱动因素对研究区域植被的影响,并强调了通过基于模型的环境驱动因素调整,提高了检测管理行动真实影响的能力。
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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.
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
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.
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