Replication data for: Correspondence in forest species composition between the Vegetation Map of Africa and higher resolution maps for seven African countries
<|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:'Question: How well does the forest classification systemof the 1:5,000,000 vegetation map of Africa developed by Frank White correspond with classification systems and more extensive information on species assemblages of higher resolution maps developed for Ethiopia, Kenya,Malawi, Rwanda, Tanzania, Uganda and Zambia? Methods: We reviewed various national and sub-national vegetation maps for their potential in increasing the resolution of the African map. Associated documentation was consulted to compile species assemblages, and to identify indicator species, for national forest vegetation types. Indicator species were identified for each regional forest type by selecting those species that, among all the species listed for the same phytochorion (regional centre of endemism),were listed only for that forest type. For each of the national' . 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" : ["beta-sim distance","FrankWhite","Indicator species","Kulczynski distance","Phytochorion"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Question: How well does the forest classification systemof the 1:5,000,000 vegetation map of Africa developed by Frank White correspond with classification systems and more extensive information on species assemblages of higher resolution maps developed for Ethiopia, Kenya,Malawi, Rwanda, Tanzania, Uganda and Zambia? Methods: We reviewed various national and sub-national vegetation maps for their potential in increasing the resolution of the African map. Associated documentation was consulted to compile species assemblages, and to identify indicator species, for national forest vegetation types. Indicator species were identified for each regional forest type by selecting those species that, among all the species listed for the same phytochorion (regional centre of endemism),were listed only for that forest type. For each of the national' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Question: How well does the forest classification systemof the 1:5,000,000 vegetation map of Africa developed by Frank White correspond with classification systems and more extensive information on species assemblages of higher resolution maps developed for Ethiopia, Kenya,Malawi, Rwanda, Tanzania, Uganda and Zambia? Methods: We reviewed various national and sub-national vegetation maps for their potential in increasing the resolution of the African map. Associated documentation was consulted to compile species assemblages, and to identify indicator species, for national forest vegetation types. Indicator species were identified for each regional forest type by selecting those species that, among all the species listed for the same phytochorion (regional centre of endemism),were listed only for that forest type. For each of the national
beta-sim distance; FrankWhite; Indicator species; Kulczynski distance; Phytochorion