Co-occurrence and abundance of pollinators and pests in horticultural systems in Africa using an integrated Earth observation-based approach
Creators: name: Aduvukha, Grace Rebecca
name: Abdel-Rahman, Elfatih M.
name: Mudereri, Bester Tawona
name: Sichangi, Arthur W.
name: Makokha, Godfrey Ouma
name: Lattorff, H. Michael G.
name: Mohamed, Samira A.
name: Landmann, Tobias
name: Tonnang, Henri E. Z.
name: Dubois, Thomas
Publisher: name: Taylor & Francis
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Plant Biology

description: Flower-visiting insects that are pollinators play a critical role in promoting biodiversity in agroecosystems and agricultural food production through their pollination ecosystem service. However, several factors affect the survival of these pollinators and flower visitors, including the heavy and indiscriminate application of agrochemicals to control crop insect pests, which is impacted by various cropping patterns in a landscape and by shifting environmental conditions. Thus, this study focused on investigating the influence of cropping patterns on the spatial distribution of pollinators (<i>Apis mellifera</i>, Hymenoptera other than <i>A. mellifera</i>, and Syrphidae), flower visitors (Calliphoridae), and pests, i.e. fruit fly (<i>Bactrocera dorsalis</i>) and false codling moth (<i>Thaumatotibia leucotreta</i>) of the avocado, a pollinator-dependent crop. Cropping patterns, earth observation data and relevant environmental variables were used as the predictor variables for modeling the potential distribution and abundance of avocado pollinators, flower visitors and pests in one of the leading regions in avocado production in Kandara, Maragua, and Gatanga sub-Counties in Murang’a County, Kenya. In specific, species distribution modeling (SDM) and species abundance modeling (SAM) techniques, i.e. the maximum entropy (MaxEnt) model (presence-only data) and negative binomial (NB) distribution in a generalized linear model (GLM) (abundance data) were used, respectively. Additionally, the spatial distribution probability of the co-occurrence of the pollinators, flower visitors and pests was also analyzed. This study revealed that cropping patterns was the most consistent influential predictor variables for the distribution of avocado pollinators, flower visitors and pests. A large area of Kandara and some parts of Maragua and Gatanga sub-Counties showed a high spatial distribution probability of the studied avocado pollinators, flower visitors and pests. However, only the majority of Kandara sub-County had a high spatial distribution probability score of the potential co-occurrence of the avocado pollinators, flower visitors and pests. Further, <i>A. mellifera</i> was the most abundant flower-visiting pollinator compared with the other studied pollinators, while <i>B. dorsalis</i> was the most abundant avocado pest compared with <i>T. leucotreta</i>. In addition, GLM analysis indicated that no environmental variable was significant in explaining the abundance of the studied avocado pollinators, whereas precipitation and elevation derivatives of aspect and hillshade were statistically significant (<i>p</i> ≤ 0.05) in explaining the abundance of <i>B. dorsalis</i>. Solar radiation was significant in explaining only the abundance of <i>T. leucotreta</i>. Our study revealed that SDM and SAM modeling outputs can be used to inform decision-making for the implementation of sustainable management efforts regarding pollinators, flower visitors, and insect pests.