dc.contributor.author | Gladys, Mosomtai | |
dc.contributor.author | Abdelmutalab, G.A. Azrag | |
dc.contributor.author | Régis, Babin | |
dc.contributor.author | Elfatih, Abdel-Rahman | |
dc.contributor.author | John, Odindi | |
dc.contributor.author | Onisimo, Mutanga | |
dc.contributor.author | Henri, E.Z. Tonnang | |
dc.contributor.author | Tobias, Landmann | |
dc.contributor.author | Guillaume, David | |
dc.date.accessioned | 2022-05-06T18:21:47Z | |
dc.date.available | 2022-05-06T18:21:47Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12562/1633 | |
dc.description | NA | en_US |
dc.description.abstract | In the Eastern Africa highlands, the gradual transformation of natural ecosystems to smallholding coffee-based agrosystems has resulted in more fragmented landscapes. Major pests of coffee find appropriate living conditions leading to high infestation rates and the need for smallholder farmers to implement pest control measures. This study aims to understand the influence of landscapes on the ecology of three major coffee pests: the coffee berry borer (CBB), Hypothenemus hampei, and the Antestia bugs Antestiopsis thunbergii (ABT) and A. facetoides (ABF). The study was conducted on a typical smallholder coffee-based landscape in central Kenya. The pest abundance was assessed monthly for two years in a network of 30 coffee plots spread across the coffee agro-ecological subzones (AEsZ), namely upper midland UM1 and UM2, and the transition zones between UM1 and UM2 and between UM2 and UM3, herein referred to as TZ1 and TZ2, respectively. Landscape metrics, viz. patch density, Euclidean nearest neighbour distance, proximity index, contagion index, interspersion and juxtaposition index were derived from a spatially explicit land cover map, based on 10 m Sentinel 2 data for nine buffer zones of radius ranging from 50 m to 1000 m around each sampled plot. Redundancy analysis (RDA) was used to establish the relationships between the observed pest abundances and landscape metrics, elevation, and AEsZ. Landscape indicators achieved the highest correlation with the pest abundances within a 300 m radius (Adjusted R2 > 0.5). Whereas beyond 300 m landscape scale, the predictor variables resulted in weak relationships (Adjusted R2 < 0.5) between the pests abundance and landscape metrics. We noted a strong influence of elevation and adjacency to cropland on Antestia bug populations. Specifically, ABF populations were negatively correlated with low elevation, whereas ABT’s were positively correlated with high elevation zone. On the other hand, CBB was strongly influenced by contiguous coffee patches, especially in UM1 and UM2. Therefore, we recommend reducing connectivity between coffee patches for the management of CBB, whereas further studies should be conducted to identify secondary hosts of Antestia bugs that should not be adjacent or within coffee stands | en_US |
dc.description.sponsorship | Check PDF for details | en_US |
dc.publisher | Agriculture, Ecosystems and Environment | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | plant pest | en_US |
dc.subject | harmful insect | en_US |
dc.subject | hypothenemus hampei | en_US |
dc.title | Functional land cover scale for three insect pests with contrasting dispersal strategies in a fragmented coffee-based landscape in Central Kenya | en_US |
dc.type | Article | en_US |
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