CAFNET Local knowledge studies of trees in coffee systems in East Africa
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'CAFNET research has elicited local agro-ecological knowledge from coffee growing areas within the vicinity of forest reserves in Kenya, Uganda and Rwanda. Knowledge was acquired from over 200 farmers in a stratified purposive sample, using a knowledge based systems approach.   Ranking and phenology survey  Building on the local knowledge studies and on-farm tree inventories, we designed a ranking and phenology survey to be applied across the 100 farms in the three counties to test consistency of farmer knowledge about physical attributes and phenology of trees found in coffee plots and along coffee plot boundaries' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agroforestry","Coffee","Environmental services","Local knowledge"]} <|eot_id|>
 Here is the Description of a dataset. Description:'CAFNET research has elicited local agro-ecological knowledge from coffee growing areas within the vicinity of forest reserves in Kenya, Uganda and Rwanda. Knowledge was acquired from over 200 farmers in a stratified purposive sample, using a knowledge based systems approach.   Ranking and phenology survey  Building on the local knowledge studies and on-farm tree inventories, we designed a ranking and phenology survey to be applied across the 100 farms in the three counties to test consistency of farmer knowledge about physical attributes and phenology of trees found in coffee plots and along coffee plot boundaries' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
CAFNET research has elicited local agro-ecological knowledge from coffee growing areas within the vicinity of forest reserves in Kenya, Uganda and Rwanda. Knowledge was acquired from over 200 farmers in a stratified purposive sample, using a knowledge based systems approach.   Ranking and phenology survey  Building on the local knowledge studies and on-farm tree inventories, we designed a ranking and phenology survey to be applied across the 100 farms in the three counties to test consistency of farmer knowledge about physical attributes and phenology of trees found in coffee plots and along coffee plot boundaries
Agroforestry; Coffee; Environmental services; Local knowledge