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MainDB: Climate Change Impacts on Ecoregions in the Kangchenjunga Landscape of India, Bhutan, and Nepal

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Title

 Climate Change Impacts on Ecoregions in the Kangchenjunga Landscape of India, Bhutan, and Nepal

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NWPTypeOfOrganization

 Civil society

NWPGeographicRegion

 Asia

Scope of work

  

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Good practices and lessons learned
The key lessons learned include: 
  1. Local, on-the-ground partners are essential for scoping project aims and providing context for study areas;
  2. When possible, project participants should travel to study areas so as to maximize contextual understanding. However, travel was not possible during the course of this study due to the COVID-19 pandemic;
  3. Co-creation with local organizations is crucial. ICIMOD engages with a diverse number of partners and subject matter across sectors within the Hindu-Kush Himalaya (HKH) subregion, and thus is a leader in knowledge production and dissemination in the HKH region. This study greatly benefited from their expertise and input;
  4. Narrow scopes are useful and necessary to meet short timelines. However, additional work is needed to synthesize results to holistically address knowledge gaps. Thus, knowledge development should be ongoing and iterative.

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Date of submission

 18/05/2022

Abbreviation

  

Activities
 

Adaptation element

 Adaptation planning and practices; Climate scenarios; Impact assessment; Science and research

Adaptation sector/theme

 Ecosystems; Biodiversity; Ecosystem-based adaptation; Services

Climate hazard

 Erratic rainfall; Glacial retreat; Increasing temperatures; Loss of biodiversity

Country
India, Bhutan, Nepal

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Description
Climate change is causing ecoregions to shift in the Hindu Kush Himalayas, threatening both ecosystem services and biodiversity in the region. As these ecoregions shift, important ecological processes may be disrupted and species ranges may begin to move outside the protected areas that were designed to conserve them. Although transboundary landscape initiatives and adaptive management strategies exist in the HKH to mitigate these negative impacts, researchers and practitioners need methods to project how ecoregions may shift in response to the evolving conditions of climate change. 

Zomer et al. (2014) present one such method, whereby projected climate data is used to predict ecoregion distributions based on an environmental stratification method. This method was adapted to help address the priority knowledge gap identified by the Lima Adaptation Knowledge Initiative (LAKI) on the lack of methodologies and tools to quantify the impact of climate change on ecosystem services, biodiversity, and forests in HKH subregion. 

This aim was accomplished through the following steps: 
  1. modeling ecoregion shifts in the transboundary Kangchenjunga Landscape of the HKH under two Shared Socioeconomic Pathway (SSP) projected climate scenarios;
  2. increasing the transparency, replicability, and accessibility of the modeling process by providing shareable code;
  3. examining how these projected ecoregion shifts may impact biodiversity and ecosystem services in HKH protected areas. 
Researchers, academics, and practitioners can iterate, expand, and modify this method to inform management plans that protect species, people, and ecosystems from the threat of climate change.

Expected outcome
 

Further information
This report is the outcome of a graduate student capstone project at the University of Michigan’s School for Environment and Sustainability (SEAS). The graduate student team is the fourth group of students at SEAS to partner with the UNFCCC Secretariat through the UN Climate Change and Universities Partnership Programme.

NWPGeographicScope

 Subregional; Transboundary

Indicators of achievement
 

NWPInformationType

 Case study

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NWPPartner
University of Michigan

Purpose
 

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Target group

 Academics and scientists; Policy makers; Practitioners

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 NWP

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NWPOutcome
Due to the lack of methodologies for connecting climate change trends to impacts on forest, biodiversity, and ecosystem services, a GIS-based environmental stratification model was developed and captured in Python code to both identify current ecoregions in the Kangchenjunga Landscape (KL) and project future ecoregion distributions in the KL under two Shared Socioeconomic Pathway (SSP) scenarios. The steps of the model are described in an ArcGIS Story Map and all code is accessible on GitHub. 

The model found that by the year 2100, high-elevation ecoregions (3,000m - 8,586m) will either shrink or shift to higher elevations, mid-elevation ecoregions (500m - 3,000m) will expand, and low-elevation ecoregions (0m - 500m) will shrink substantially. The researchers assessed how these shifting ecoregions may impact the ability of protected areas to conserve umbrella species (i.e., snow leopard, red panda, Asian elephant, tiger) and ecosystem services as exemplified by the Rhododendron genus. 

The analysis found that suitable ecoregion area for each of these species will generally increase within protected area boundaries under both SSP scenarios. However, the realized use of suitable ecoregion area by the respective species depends on habitat connectivity, migration ability, and lack of habitat degradation. Given that this research exists within complex socio-ecological systems, the study also generated a conceptual framework for considering additional drivers of change, data inputs, and impact assessment techniques for developing comprehensive management plans and policies that promote both ecosystem and human well-being and resilience.

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Implementing partners
International Centre for Integrated Mountain Development (ICIMOD)

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SourceItemID

 2353

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NWPTypeOfKnowledge

 Technical document/report

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Attachments

Content Type: NWPSearchableItem
Created at 17/06/2022 17:26 by crmmocservices
Last modified at 20/06/2022 15:38 by Lilian Daphine Lunyolo