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Essential environmental variables to include in a stratified sampling design for a national-level invasive alien tree survey

dc.contributor.authorKotze , Johann D. F.en_ZA
dc.contributor.authorBeukes , Hein B.en_ZA
dc.contributor.authorSeifert , Thomasen_ZA
dc.date.accessioned2021-01-15T07:48:59Z
dc.date.available2021-01-15T07:48:59Z
dc.date.issued2020
dc.identifier.citationKotze , J. D. F., Beukes, H. B. & Seifert, T. 2019. Essential environmental variables to include in a stratified sampling design for a national-level invasive alien tree survey. iForest: Biogeosciences and Forestry, 12(5):418-426, doi:10.3832/ifor2767-012  
dc.identifier.issn1971-7458 (online)
dc.identifier.otherdoi:10.3832/ifor2767-012  
dc.identifier.urihttp://hdl.handle.net/10019.1/108991
dc.descriptionCITATION: Kotze , J. D. F., Beukes, H. B. & Seifert, T. 2019. Essential environmental variables to include in a stratified sampling design for a national-level invasive alien tree survey. iForest: Biogeosciences and Forestry, 12(5):418-426, doi:10.3832/ifor2767-012.
dc.descriptionThe original publication is available at http://iforest.sisef.org
dc.description.abstractENGLISH ABSTRACT: There is a direct relationship between the abundance of biological invasions and their impact, which means that it is important to capture spatial patterns in their abundance and use this information to focus management actions. However, protocols to objectively determine invasive alien plant (IAP) distributions and abundance are lacking at a national level, resulting in the inability to determine and monitor changes in spatial extent and density over time. A complete inventory of IAP spatial distribution across an extensive area such as South Africa is not possible and so requires an efficient sampling approach. A simple random sampling design would not be efficient, so monitoring of IAP species at a national level requires an appropriate sampling design such as a stratified sampling. The selection of environmental variables to be included in such a stratification should be based on the relationship between IAP species and their physical environment to successfully summarize variance in their abundance within the different strata. A further objective is to obtain all possible combinations of environmental variables or a full rank design in the stratification to allow for the comparison of different strata based on actual field sampled data. This raises the question of which predictive environmental variables as well as how many to include in the stratification. For this purpose, three invasive tree species, namely Acacia cyclops, Acacia mearnsii and Prosopis glandulosa were selected as they cover the maximum possible area at the highest density with the least amount of geographic overlap. A total of 26 environmental variables that included climatic, soil and topographic type variables were tested with linear regressions against correlations with the abundance of those tree species. The results showed that a combination of average precipitation, soil depth, clay content in the B-horizon and terrain morphological units will serve as a suitable stratification at a national level to explain IAP abundance variation sufficiently well whilst retaining a full rank design. These results will be applied as the first phase in the formation of a regional level IAP monitoring programme for South Africa on a scientific basis.en_ZA
dc.description.urihttps://iforest.sisef.org/abstract/?id=ifor2767-012
dc.format.extent9 pagesen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherItalian Society of Silviculture and Forest Ecologyen_ZA
dc.subjectInvasive alien planten_ZA
dc.subjectBiological invasionsen_ZA
dc.subjectInvasive alien speciesen_ZA
dc.subjectSeeds -- Stratification -- Monitoringen_ZA
dc.subjectVernalization -- Samplingen_ZA
dc.titleEssential environmental variables to include in a stratified sampling design for a national-level invasive alien tree surveyen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderItalian Society of Silviculture and Forest Ecologyen_ZA


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