Adaptive governance of mountain ecosystem services for poverty alleviation enabled by environmental virtual observatories (MOUNTAIN-EVO)

世界上的山脉拥有一些最复杂、最具活力和最多样化的生态系统。但这些环境正面临严重的威胁，从当地的森林砍伐和土壤退化到全球气候变化。全球气候模型预测，高海拔地区的变暖程度会更强，可能对其生态系统服务造成灾难性后果（ESS）。例如，仅冰川融化就会影响数百万人的供水，而土壤退化和侵蚀使当地的农业生产方式处于危险之中，而且还会导致水质退化和下游水库淤积。与此同时，山区的复杂性也使得预测未来生态系统服务变化的方向变得极其困难。例如，全球气候模式无法捕捉当地的天气模式，传统的自然和物理过程模式可能无法代表极端和特定区域的行为。这导致了未来对山地ESS的预测存在很大的不确定性。在这种情况下，关于当地生态系统如何运作的日常信息的价值急剧增加。对关键生态系统过程的持续监测变得至关重要。它使当地决策者能够灵活地改变路线，以应对意外行为和巨大的不确定性。然而，由于地处偏远和难以进入，山区的环境监测往往落后于世界其他地区。与周围的低地相比，同样的偏远和缺乏通道也是山区倾向于接纳贫穷和不发达社区的原因。最后，山区往往更容易发生冲突，这进一步抑制了人类的发展。该项目将分析如何改善山区环境可持续发展的监测和知识创造，并将其用于支持以减贫为重点的适应性多中心治理进程。为此，我们将把适应性治理的前沿概念与技术突破相结合。廉价和强大的传感器和通信技术的可用性为公民科学提供了巨大的机会：自下而上，面向用户的数据收集侧重于当地关注的问题。我们将把公民科学提升到一个新的水平，将其整合到参与式数据处理、知识生成和共享的更广泛框架中。为此，我们采用了环境虚拟观测站（EVOs）的概念，并利用它来减轻贫困。我们认为，evo有潜力成为知识生成和交流的去中心化开放技术平台，使边缘化和弱势群体能够绕过传统机制参与其中。因此，在本项目中，我们将分析如何利用evo在四个偏远贫困山区产生知识和减轻贫困：埃塞俄比亚塔纳湖周围的高地、吉尔吉斯斯坦的天山中部山脉、尼泊尔北部的卡利甘达基流域和秘鲁中部的安第斯山脉。在每个地点，我们将收集有关ESS的当地决策过程及其当地社会经济背景的证据。同时，我们将开发一个技术工具集，以便针对每种情况进行EVO开发。随后，这两个过程的结果将结合起来，实施量身定制的evo，以支持公民科学和本地知识的产生。除了传统的互联网之外，我们还将创造新的方式与evo互动，重点是使用国语的传单、社区广播和移动电话应用程序。我们将评估改善获得当地观察结果的机会如何促进穷人与外部行动者之间以及社区与边缘群体之间的跨规模联系。最后，我们将调查这如何能提高社区对环境变化的认识，并确定减轻贫困的途径。

The world's mountains host some of the most complex, dynamic, and diverse ecosystems. But these environments are under severe threats, ranging from local deforestation and soil degradation to global climate change. Global climate models project stronger warming at high elevations, with potentially disastrous consequences for its ecosystems services (ESS). For instance, melting glaciers alone will affect the water supply of millions people, while soil degradation and erosion put local agricultural practices in danger, but also cause water quality degradation and siltation of downstream reservoirs.At the same time, the complexity of mountains also makes predicting the direction of future changes in ecosystem services extremely difficult. For instance, global climate models do not capture the local weather patterns, and traditional models of the natural and physical processes may not represent the extreme and region specific behaviour. This leads to large uncertainties in future predictions about mountain ESS.Under such conditions, the value of day-to-day information about how local ecosystems behave increases sharply. Continuous monitoring of crucial ecosystem processes becomes paramount. It allows local decision-makers to flexibly change course in response to unexpected behaviour and large uncertainties. However, because of their remote location and difficult access, monitoring ESS in mountain regions tends the lag behind the rest of the world. The same remoteness and lack of access are also responsible for the propensity of mountain regions to host poor and underdeveloped communities compared to the surrounding lowlands. Lastly, mountain regions tend to be more prone to conflict, which further inhibits human development.This project will analyse how monitoring and knowledge generation of ESS in mountain regions can be improved, and used to support a process of adaptive, polycentric governance focused on poverty alleviation. For this, we will blend cutting-edge concepts of adaptive governance with technological breakthroughs. The availability of cheap and robust sensors and communication technologies provides great opportunities for citizen science: bottom-up, user oriented data collection focused on local concerns. We will take citizen science to a next level, by integrating it in a broader framework of participatory data processing, knowledge generation and sharing. We do this by adopting the concept of Environmental Virtual Observatories (EVOs) and leverage it for poverty alleviation. We see the potential of EVOs to be decentralised and open technology platforms for knowledge generation and exchange that enable participation of marginalised and vulnerable communities bypassed by the traditional mechanisms. Therefore, in this project we will analyse how EVOs can be used to generate knowledge and to alleviate poverty in 4 remote and poor mountain regions: the Ethiopian highlands around lake Tana, the Central Tien Shan Mountains of Kyrgyzstan, the Kaligandaki watershed in Northern Nepal, and the Andes of central Peru. In each location, we will collect evidence on the local decision-making processes on ESS and their local socio-economic context. At the same time, we will develop a technology toolset to enable EVO development for each case. Subsequently, the results of both processes will be brought together to implement tailored EVOs to support citizen science and local knowledge generation. We will create novel ways to interact with EVOs beyond the traditional Internet focussing on leaflets in the national language, community radios, and mobile phone applications. We will evaluate how the improved access to local observations fosters cross-scale linkages between the poor and external actors, as well as linkages between communities and marginal groups. Lastly, we will investigate how this can lead to better community awareness of environmental change and identification of pathways for poverty alleviation.