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

世界上的山区拥有一些最复杂，最具活力和多样性的生态系统。但这些环境正受到严重威胁，从当地森林砍伐和土壤退化到全球气候变化。全球气候模型预测，高海拔地区的气候变暖将更为强烈，这可能会对生态系统服务（ESS）造成灾难性后果。例如，冰川融化本身就会影响数百万人的供水，土壤退化和侵蚀会危及当地的农业做法，还会造成水质退化和下游水库淤积，同时，山区的复杂性也使预测生态系统服务未来变化的方向变得极为困难。例如，全球气候模型并不反映当地的天气模式，传统的自然和物理过程模型可能并不代表极端和特定区域的行为。在这种情况下，关于当地生态系统行为的日常信息的价值急剧增加。持续监测关键的生态系统进程变得至关重要。它使当地决策者能够灵活地改变方针，以应对意外行为和巨大的不确定性。然而，由于山区地处偏远，难以进入，监测山区环境服务系统往往落后于世界其他地区。与周围的低地相比，山区往往是贫穷和不发达社区的所在地，这也是由于地处偏远和交通不便。最后，山区往往更容易发生冲突，这进一步阻碍了人类发展，本项目将分析如何改进山区环境服务系统的监测和知识生成，并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的关注。我们将把公民科学提升到一个新的水平，将其纳入参与性数据处理、知识生成和共享的更广泛框架。我们通过采用环境虚拟观测站的概念来实现这一目标，并将其用于减贫。我们认为，EVO有潜力成为知识生成和交流的分散和开放的技术平台，使被传统机制绕过的边缘化和弱势社区能够参与。因此，在本项目中，我们将分析如何使用EVOs来产生知识和减轻4个偏远贫困山区的贫困：塔纳湖周围的埃塞俄比亚高地，吉尔吉斯斯坦的天山山脉中部，尼泊尔北方的Kaligandaki流域，以及秘鲁中部的安第斯山脉。在每个地方，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。与此同时，我们将开发一个技术工具集，以便为每个案例进行EVO开发。随后，这两个进程的结果将被汇集在一起，以实施量身定制的EVO，以支持公民科学和地方知识的生成。我们将创造新的方式与EVO互动，超越传统的互联网，专注于民族语言的传单，社区广播和移动的电话应用程序。我们将评估如何改善获得当地观察促进穷人和外部行为者之间的跨尺度联系，以及社区和边缘群体之间的联系。最后，我们将研究如何提高社区对环境变化的认识，并确定扶贫的途径。

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.