Spatio-temporal invasion dynamics of Maesopsis eminii in Amani Nature Forest Reserve, Tanzania

This research article published by Elsevier B.V., 2020Globally, invasive plant species cause negative impacts to human livelihoods and natural ecosystems, particularly in biodiversity hotspots. Maesopsis eminii invasion in Amani Nature Forest Reserve, Tanzania, was considered an ecological disaster in the 1980s. After >50 years have elapsed since the species was first introduced in the reserve, there is yet little information available on its invasion progress. We assessed spatio-temporal invasion dynamics using forest inventory data collected in 1998 and resurveyed 60 (20 m × 50 m) sample plots in 2018. Among resurveyed plots, 30 had been invaded by M. eminii in 1998 and other 30 sample plots as control, which had no M. eminii in the year 1998. We also assessed vegetation cover change over a 20 year period between 1998 and 2018 using Landsat satellite images. Over the last 20 years, 23% of control plots were newly invaded by M. eminii. Tree species richness was 25% lower in invaded versus control plots (U = 1490, z = 2.9, p = 0.04). Large trees (DBH ≥ 31–50 cm) of Maesopsis eminii were most abundant (62%) in invaded plots whereas small trees (DBH ≤ 10 cm) were most abundant (>50%) in control plots, indicating that the tree species might be prone to self-thinning. Woody species diversity was significantly lower in invaded (1.63 ± 0.49) vs control plots (1.87 ± 0.35; t(58) = −2.19, p = 0.03). The number of M. eminii individuals ha−1 was positively associated with higher altitudes ranging above 800 masl (ρ = 0.33, P = 0.011) but there was no correlation with distance away from the forest reserve boundary (ρ = 0.11, P = 0.394;) nor with distance away from village centers (ρ = −0.08, P = 0.502). Change detection analysis indicated about 1,108 ha of non-forest vegetation had regrown into forest over the last 20 years, particularly in the south - western region of the reserve. The region included 4 sample plots newly invaded by M. eminii. We conclude that there is an increase in spatial distribution of M. eminii individuals between the year 1998 and 2018. Furthermore, M. eminii has low regeneration potential in already invaded sites of high invasive density and only slowly invading gaps in uninvaded sites

Comparison of multi-source remote sensing data for estimating and mapping above-ground biomass in the West Usambara tropical montane forests

Above-ground biomass (AGB) estimation is important to better understand the carbon cycle and improve the efficiency of forest policy and management activities. AGB estimation models, using a combination of field data and remote sensing data, can largely replace traditional survey methods for measuring AGB. There are, however, critical steps for mapping AGB based on satellite data with an acceptable degree of accuracy, such as choice of remote sensing data, the proper statistical modelling method, and remote sensing predictor variables, at known field locations. This study sought to identify the optimal optical and synthetic aperture radar (SAR) remote sensing imagery from five sensors (PlanetScope, Sentinel-2, Landsat 8 OLI, ALOS-2/PALSAR-2, and Sentinel-1) to model 159 field-based AGB values from two montane forests under semiparametric (Generalized Additive Model; GAM) and non-parametric (eXtreme Gradient Boosting; XGB) approaches using information from four groups of predictor variables (spectral bands/polarizations, vegetation indices, textures, and a combination of all). The study's results showed that PlanetScope (rRMSE = 69.19%; R2 = 0.161) was the most precise optical sensor while ALOS-2/PALSAR-2 (rRMSE = 70.76; R2 = 0.165) was the most precise amongst the SAR sensors. XGB models generally resulted in those with lower prediction errors as compared to GAMs for the five sensors. Models having textures of vegetation indices and polarization bands achieved greater accuracy than models that incorporated spectral bands/polarizations and vegetation indices only. The study recommends that PlanetScope and ALOS-2/PALSAR-2 remote sensing data using the XGB-based technique is an appropriate approach for accurate local and regional estimation of tropical forest AGB particularly for complex montane forest ecosystems

Effect of seasonality and light levels on seed germination of the invasive tree Maesopsis eminii in Amani Nature Forest Reserve, Tanzania

This research article published by Elsevier B.V.Studies on germination behavior are important tools for understanding how environmental factors affect geographic distribution and colonization of invasive plants. Particularly seedlings of invasive plant species benefit from high light intensity, as often found in disturbed areas of low canopy cover. We investigated the effect of various shade levels on seed germination and early growth of the invasive tree Maesopsis eminii at the nursery of a biodiversity hotspot, the Amani Nature Forest Reserve, Tanzania. Shade houses provided forest-like sun flecks of four categories (0%, 50%, 65% and 85% shade), representing light regimes found in tropical natural forests throughout the entire growing season. The average germination rate across the four different shade levels differed significantly during the dry season (F3,12 = 48.74, P < 0.001) but not in the wet season (F3,12 = 3.49, P = 0.051). Final germination percentage at 0% shade was 1.5 times higher compared to that under 85% shade during the wet season. In both dry and wet seasons, stem diameter, shoot height, total fresh and dry biomass significantly decreased with an increase in shade levels. During the dry season, leaf chlorophyll contents were three times higher at 85% and 65% shade than at 0% shade. Both seasonality and shade levels as well as their interactions influenced most germination parameters but not growth parameters except stem diameter. The conclude that M. eminii seed germination is fostered by light as it prefers colonizing in forest gaps, and lower light levels might act as a barrier to its invasive capacity, particularly during the dry season. Hence, management strategies of M. eminii should include the provision of unfavorable light regimes and take seasonality into account