Is ground cover a useful indicator of grazing land condition?

IF 1.2 4区 环境科学与生态学 Q4 ECOLOGY
Rangeland Journal Pub Date : 2021-09-14 DOI:10.1071/rj21018
T. Beutel, R. Shepherd, R. Karfs, B. Abbott, T. Eyre, T. Hall, Emily Barbi
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引用次数: 3

Abstract

Remotely sensed ground cover data play an important role in Australian rangelands research development and extension, reflecting broader global trends in the use of remotely sensed data. We tested the relationship between remotely sensed ground cover data and field-based assessments of grazing land condition in the largest quantitative analysis of its type to date. We collated land condition data from 2282 sites evaluated between 2004 and 2018 in the Burdekin and Fitzroy regions of Queensland. Condition was defined using the Grazing Land Management land condition framework that ranks grazing land condition on a four point ordinal scale based on dimensions of vegetation composition, ground cover level and erosion severity. Nine separate ground cover derived indices were then calculated for each site. We found that all indices significantly correlated with grazing land condition on corresponding sites. Highest correlations occurred with indices that benchmarked ground cover at the site against regional ground cover assessed over several years. These findings provide some validation for the general use of ground cover data as an indicator of rangeland health/productivity. We also constructed univariate land condition models with a subset of these indices. Our models predicted land condition significantly better than random assignment though only moderately well; no model correctly predicted land condition class on >40% of sites. While the best models predicted condition correctly at >60% of A and D condition sites, condition at sites in B and C condition sites was poorly predicted. Several factors limit how well ground cover levels predict land condition. The main challenge is modelling a multidimensional value (grazing land condition) with a unidimensional ground cover measurement. We suggest that better land condition models require a range of predictors to address this multidimensionality but cover indices can make a substantial contribution in this context.
地面覆盖是牧场状况的有用指标吗?
遥感地面覆盖数据在澳大利亚牧场研究的发展和推广中发挥着重要作用,反映了遥感数据使用的更广泛的全球趋势。我们在迄今为止最大规模的定量分析中测试了遥感地面覆盖数据与牧场状况实地评估之间的关系。我们整理了2004年至2018年间在昆士兰州Burdekin和Fitzroy地区评估的2282个地点的土地状况数据。条件是使用牧场管理土地条件框架来定义的,该框架基于植被组成、地面覆盖水平和侵蚀严重程度的维度,以四点顺序对牧场条件进行排名。然后为每个场地计算了9个独立的地面覆盖物衍生指数。研究发现,各指标均与相应地点的牧场状况显著相关。最高的相关性出现在以现场地面覆盖物为基准的指数与几年来评估的区域地面覆盖物之间。这些发现为地面覆盖数据作为牧场健康/生产力指标的普遍使用提供了一些验证。我们还用这些指数的子集构建了单变量土地状况模型。我们的模型预测的土地状况明显好于随机分配,尽管只是适度好;没有一个模型能够正确预测超过40%的场地的土地状况等级。虽然最佳模型在>60%的A和D条件位点正确预测了条件,但在B和C条件位点的条件预测较差。有几个因素限制了地面覆盖水平对土地状况的预测。主要挑战是用一维地面覆盖测量对多维值(牧场条件)进行建模。我们认为,更好的土地状况模型需要一系列的预测因素来解决这种多维性,但覆盖指数在这种情况下可以做出重大贡献。
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来源期刊
Rangeland Journal
Rangeland Journal 环境科学-生态学
CiteScore
2.90
自引率
8.30%
发文量
14
审稿时长
>36 weeks
期刊介绍: The Rangeland Journal publishes original work that makes a significant contribution to understanding the biophysical, social, cultural, economic, and policy influences affecting rangeland use and management throughout the world. Rangelands are defined broadly and include all those environments where natural ecological processes predominate, and where values and benefits are based primarily on natural resources. Articles may present the results of original research, contributions to theory or new conclusions reached from the review of a topic. Their structure need not conform to that of standard scientific articles but writing style must be clear and concise. All material presented must be well documented, critically analysed and objectively presented. All papers are peer-reviewed. The Rangeland Journal is published on behalf of the Australian Rangeland Society.
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