自然资源可持续开发的社会-生态熵视角

Sebastian Michel-Mata, Mónica Gómez-Salazar, Víctor Castaño, I. Santamaría-Holek
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摘要

通过引入社会生态熵产(SEEP)方法,提出了一种评估社会生态系统(SES)可持续性和弹性的创新综合建模策略。与不可逆过程的热力学熵产生类似,我们讨论了一个理论模型,该模型将能量和信息流与开发同一自然资源的不同社区的文化和认识论特性联系起来。我们方法的一个创新之处在于,可持续性是通过单一参数(SEEP)来评估的,该参数包含了参与动态的所有种群的模拟结果,而不仅仅是资源的命运。就所考虑的不同动力学的耦合所引入的非线性可能导致对小扰动的高灵敏度而言,这一点是重要的。具体来说,通过假设两种可能的技术和环境知识转移方法[直接(D)和分阶段(P)]在开发和恢复资源的两个社区中的每一个社区中,我们生成了四个数学模型,以探索由于新的认识论社区对最初可持续的资源社区SES的干预而导致的长期可持续性情景。通过探索表征技术和环境知识程度以及社会包容和知识转移率的四个关键参数的空间,我们的模拟表明,在每个案例中研究的400个场景中,P-P模型预测了第二个社区干预后资源利用的100%可持续案例。混合情景P-D和D-P预测约29%,而D-D情景仅预测23%的可持续病例。在P-D和D-P情景中,预计灾难性后果约占71%,在D-D情景中,约有77%的系统因资源和社区人口枯竭而灭绝。在这种形式下,我们的理论策略和所研究的知识转移情景可以帮助决策者找到一个先验的基于科学的标准,以解决社会生态干预可能引起的争议。
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Towards a Social-Ecological-Entropy Perspective of Sustainable Exploitation of Natural Resources
An innovative and integrative modeling strategy for assessing the sustainability and resilience of social-ecological systems (SES) is presented by introducing a social-ecological entropy production (SEEP) method. In analogy to the thermodynamic entropy production of irreversible processes, we discuss a theoretical model that relates energy and information flow with the cultural and epistemological peculiarities of different communities that exploit the same natural resource. One of the innovative aspects of our approach comes from the fact that sustainability is assessed by a single parameter (SEEP) incorporating the simulation outcomes of all the populations participating in the dynamics, and not only on the fate of the resource. This is significant as far as the non-linearities introduced by the coupling of the different dynamics considered may lead to high sensitivity to small perturbations. Specifically, by assuming two possible types of technical and environmental knowledge-transfer methods [direct (D) and phase-in (P)] within each one of the two communities that exploit and restore a resource, we generate four mathematical models to explore the long-term sustainability scenario due to the intervention, by a new epistemological community, of an initially sustainable resource-community SES. By exploring the space of four key parameters characterizing the degree of technical and environmental knowledge, as well as the rates of social inclusion and knowledge transfer, our simulations show that, from 400 scenarios studied in each case, the P-P model predicts 100% sustainable cases in the use of the resource after the intervention by the second community. The mixed scenarios P-D and D-P predict about 29%, and the D-D scenario only predicts 23% of sustainable cases. Catastrophic outcomes are predicted at about 71% in P-D and D-P scenarios, and about 77% of extinction of the system by exhaustion of the resource and community populations in the D-D scenario. In this form, our theoretical strategy and the knowledge-transfer scenarios studied may help policymakers to find a priori science-based criteria to solve possible controversies arising from social-ecological interventions.
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