人为火灾的全球行为模型:陆地火灾系统的时空分布

Oliver Perkins, Sarah Matej, K. Erb, J. Millington
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引用次数: 1

摘要

景观火情是通过社会生态过程产生的,但在目前的全球模型中,人为影响对火情的表征仅限于从GDP和人口密度等粗略测量中得出的简单函数。因此,火灾激活的动态全球植被模型(dgvm)重现观测到的火灾模式的能力有限,预测价值有限。这一挑战的核心是未能代表人类的能动性和与火灾有关的决策。本文概述了全球行为模型的进展,该模型捕捉了不同社会生态背景下不同土地利用目标引起的人类火灾使用和管理的分类差异。我们提出了一个模拟的全球时空分布,我们称之为“陆地火灾系统”(LFSs),这是一个结合了土地利用系统和人为火灾制度的分类。我们的模型通过一种新的自举分类树方法模拟lfs之间的竞争,该方法对参考多项式回归表现良好。我们用净初级生产(HANPP)框架的人类占用来评估模型产出,并发现了良好的总体一致性。我们讨论了我们的方法的局限性,以及在dgvm和相关的模型相互比较协议中集成行为建模的剩余挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a global behavioural model of anthropogenic fire: The spatiotemporal distribution of land-fire systems
Landscape fire regimes are created through socio-ecological processes, yet in current global models the representation of anthropogenic impacts on fire regimes is restricted to simplistic functions derived from coarse measures such as GDP and population density. As a result, fire-enabled dynamic global vegetation models (DGVMs) have limited ability to reproduce observed patterns of fire, and limited prognostic value. At the heart of this challenge is a failure to represent human agency and decision-making related to fire. This paper outlines progress towards a global behavioural model that captures the categorical differences in human fire use and management that arise from diverse land use objectives under varying socio-ecological contexts. We present a modelled global spatiotemporal distribution of what we term ‘land-fire systems’ (LFSs), a classification that combines land use systems and anthropogenic fire regimes. Our model simulates competition between LFSs with a novel bootstrapped classification tree approach that performs favourably against reference multinomial regressions. We evaluate model outputs with the human appropriation of net primary production (HANPP) framework and find good overall agreement. We discuss limitations to our methods, as well as remaining challenges to the integration of behavioural modelling in DGVMs and associated model-intercomparison protocols.
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