Mapping spatial distribution and geographic shifts of east African highland banana (Musa spp.) in Uganda

Open Access Journal; Published online: 17 Feb 2022East African highland banana (Musa acuminata genome group AAA-EA; hereafter referred to as banana) is critical for Uganda’s food supply, hence our aim to map current distribution and to understand changes in banana production areas over the past five decades. We collected banana presence/absence data through an online survey based on high-resolution satellite images and coupled this data with independent covariates as inputs for ensemble machine learning prediction of current banana distribution. We assessed geographic shifts of production areas using spatially explicit differences between the 1958 and 2016 banana distribution maps. The biophysical factors associated with banana spatial distribution and geographic shift were determined using a logistic regression model and classification and regression tree, respectively. Ensemble models were superior (AUC = 0.895; 0.907) compared to their constituent algorithms trained with 12 and 17 covariates, respectively: random forests (AUC = 0.883; 0.901), gradient boosting machines (AUC = 0.878; 0.903), and neural networks (AUC = 0.870; 0.890). The logistic regression model (AUC = 0.879) performance was similar to that for the ensemble model and its constituent algorithms. In 2016, banana cultivation was concentrated in the western (44%) and central (36%) regions, while only a small proportion was in the eastern (18%) and northern (2%) regions. About 60% of increased cultivation since 1958 was in the western region; 50% of decreased cultivation in the eastern region; and 44% of continued cultivation in the central region. Soil organic carbon, soil pH, annual precipitation, slope gradient, bulk density and blue reflectance were associated with increased banana cultivation while precipitation seasonality and mean annual temperature were associated with decreased banana cultivation over the past 50 years. The maps of spatial distribution and geographic shift of banana can support targeting of context-specific intensification options and policy advocacy to avert agriculture driven environmental degradation

Butterflies show different functional and species diversity in relationship to vegetation structure and land use

Aim: Biodiversity is rapidly disappearing at local and global scales also affecting the functional diversity of ecosystems. We aimed to assess whether functional diversity was correlated with species diversity and whether both were affected by similar land use and vegetation structure drivers. Better understanding of these relationships will allow us to improve our predictions regarding the effects of future changes in land use on ecosystem functions and services. Location: The Netherlands. Methods: We compiled a dataset of c. 3 million observations of 66 out of 106 known Dutch butterfly species collected across 6,075 sampling locations during a period of 7 years, together with very high-resolution maps of land use and countrywide vegetation structure data. Using a mixed-effects modelling framework, we investigated the relationship between functional and species diversity and their main land use and vegetation structure drivers. Results: We found that high species diversity does not translate into high functional diversity, as shown by their different spatial distribution patterns in the landscape. Functional and species diversity are mainly driven by different sets of structural and land use parameters (especially average vegetation height, amount of vegetation between 0.5 and 2 m, natural grassland, sandy soils vegetation, marsh vegetation and urban areas). We showed that it is a combination of both vegetation structural characteristics and land use variables that defines functional and species diversity. Main conclusions: Functional diversity and species diversity of butterflies are not consistently correlated and must therefore be treated separately. High functional diversity levels occurred even in areas with low species diversity. Thus, conservation actions may differ depending on whether the focus is on conservation of high functional diversity or high species diversity. A more integrative analysis of biodiversity at both species and trait levels is needed to infer the full effects of environmental change on ecosystem functioning