Restoration 
Plantations and tree crop commodities 
Enhanced nutrition and food security 
Biodiversity, safeguarding and conservation 
Nationally determined contributions 
Bioenergy and biomaterials 
Blue carbon and peatlands 
Climate change adaptation 
Landscape governance 
Gender 
Silvopastoral systems 
Market-based agroforestry-forestry 
Farm-forest policy interface 
Agroecology 
Livelihood trajectory modelling and assessment 
Inclusive finance and business models 
Innovating finance for sustainable landscapes 
Public and private commitments to zero deforestation 
Orphan tree crops 
Effectiveness of approaches to sustainable supply 
Quality of FTA research for development 
Sentinel landscapes 
Foresight 
Seeds and seedlings delivery systems 
Smallholder tree-crop commodities 
Sentinel Landscapes
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- Sentinel Landscapes
Sentinel landscapes are geographic areas or sets of areas bound by a common issue, in which a broad range of biophysical, social, economic and political data are monitored, collected with consistent methods, and interpreted over the long term.
This long-term data is essential for addressing development, resource sustainability and scientific challenges, such as linking biophysical processes to human reactions and understanding the impacts of those reactions on ecosystems.
The major justification for sentinel landscapes is the need for a common observation ground where reliable data from the biophysical and social sciences can be tracked simultaneously and over time so that long-term trends can be detected, and society can make mitigation, adaptation and best-bet choices.
At the global scale, the data generated will fit into a global analysis of networks including other (humid) sentinel landscapes while providing a “dry-land ecosystem” perspective to understand issues and processes that could be relevant to managing similar ecosystems worldwide.
To view CIFOR’s website on sentinel landscapes, click here.
FTA’s Sentinel Landscapes datasets have been peer-reviewed to ensure that they meet CGIAR’s ‘quality of research for development’ (QoR4D) framework. This framework, developed with strong methodological contributions from FTA, comprises criteria for relevance, credibility, legitimacy and effectiveness.
To read more about our peer-review process for data quality, click here.
Relevance
The Sentinel Landscapes datasets have been independently evaluated as contributing to a well-defined research question important to forests, trees and agroforestry, and to FTA’s Theory of Change. The Sentinel Landscapes datasets also contribute new knowledge on forests, trees and agroforestry.
Credibility
The credibility of the Sentinel Landscapes datasets has been externally verified. The datasets belong to FTA partners – and can be used by FTA.
The Sentinel Landscapes datasets have been generated through a rigorous research design; they are complete, curated and cleaned. The datasets, the underlying methods and related findings are robust, and sources of knowledge are dependable and sound.
Legitimacy
The Sentinel Landscapes datasets have been assessed as meeting the criteria for legitimacy. Data have been collected following both Free Prior Informed Consent (FPIC) and the research ethics guidelines of FTA, ensuring the underlying research process is fair and ethical and perceived as such, including proper representation of all involved and consideration of interests and perspectives of intended users. Gender considerations, and thus a gender lens, is reflected in the data collected.
Effectiveness
The Sentinel Landscapes datasets and related products and services are accessible and well positioned for uptake and use (by researchers and stakeholders), including capacity development and proper support to the enabling environment. Sentinel Landscapes data on the FTA website are also available and accessible on the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) interoperable repository site, Dataverse. Data are also described by sufficient metadata (CG-Core).
If you use the Sentinel Landscapes data in any way, we would be happy to hear from you and support the visibility of your work by publishing a data story on your research. To submit a data story, click here.
