Assessing the ecological complexity and uncertainty of predicting forest ecosystem services under climate change

IF 3.1 3区 环境科学与生态学 Q2 ECOLOGY
Marc Djahangard , Han Zhang , Rasoul Yousefpour
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引用次数: 0

Abstract

Climate change affects Central European forest ecosystems in different ways and, consequently, these changes result in different feedbacks on the provision of forest ecosystem services. Regarding the complexity and the variability in climate-forest interactions outcome, forest decision makers necessitate reliable information about changes in the forest ecosystem services for planning and adaptation purposes. However, forest productivity predictions incorporate multiple levels of uncertainty that have to be regarded to ensure building realistic expectations in forest decision-making. Besides the chosen forest simulation model, uncertainties come from the climate change data represented by a set of representative concentration pathways (RCP), within the underlying ensemble of global circulation and regional climate models (GCM-RCM), and further in the treatment of the CO2-fertilization effect. We considered the mentioned uncertainties in a framework on simulating forest growth and water services for two forest sites, a Sessile oak and a Scots pine stand in Rhineland-Palatine, Germany. The framework revealed a high variability in future forest ecosystem services. Particularly, the variability among the selected GCM-RCM models within the same Representative Concentration Pathway (RCP) was higher than the variability among different RCPs (RCP2.6 and RCP8.5 representing the low and high CO2-emission scenarios, respectively). Sessile oak productivity increased under all scenarios, whereas Scots pine growth declined in the lower end of the RCP8.5 scenario. Water services remained mostly stable at both sites. Moreover, we applied a panel data model to estimate what climate indices caused changes in the forest ecosystem services. We found that Scots pine is more sensitive to a multitude of climate indices, such as temperature changes and Sessile oak showed strong response to the CO2-fertilization. We propose applying this framework to evaluate forest management options under climate change.

Abstract Image

评估预测气候变化下森林生态系统服务的生态复杂性和不确定性
气候变化以不同的方式影响着中欧森林生态系统,因此,这些变化对森林生态系统服务的提供产生了不同的反馈作用。鉴于气候与森林相互作用结果的复杂性和多变性,森林决策者需要获得有关森林生态系统服务变化的可靠信息,以便进行规划和适应。然而,森林生产力预测包含多个层面的不确定性,必须加以考虑,以确保在森林决策中建立现实的预期。除了所选的森林模拟模型外,不确定性还来自于全球环流和区域气候模型(GCM-RCM)基础集合中一组代表性浓度路径(RCP)所代表的气候变化数据,以及对二氧化碳施肥效应的进一步处理。我们在模拟德国莱茵兰-帕拉廷地区的无柄栎和苏格兰松林这两个林地的森林生长和水服务的框架中考虑了上述不确定性。该框架揭示了未来森林生态系统服务的高度可变性。特别是,在同一代表性浓度途径(RCP)中,所选 GCM-RCM 模型之间的变异性高于不同 RCP(RCP2.6 和 RCP8.5,分别代表低和高二氧化碳排放情景)之间的变异性。在所有情景下,无梗橡树的生产力都有所提高,而在 RCP8.5 的低端情景下,苏格兰松树的生长则有所下降。两个地点的水服务基本保持稳定。此外,我们还采用面板数据模型来估算哪些气候指数会导致森林生态系统服务发生变化。我们发现,苏格兰松树对温度变化等多种气候指数更为敏感,而无柄橡树则对二氧化碳施肥表现出强烈的反应。我们建议应用这一框架来评估气候变化下的森林管理方案。
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来源期刊
Ecological Complexity
Ecological Complexity 环境科学-生态学
CiteScore
7.10
自引率
0.00%
发文量
24
审稿时长
3 months
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
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