Landscape Fragmentation as a Risk Factor for Buruli Ulcer Disease in Ghana

Land cover and its change have been linked to Buruli ulcer (BU), a rapidly emerging tropical disease. However, it is unknown whether landscape structure affects the disease prevalence. To examine the association between landscape pattern and BU presence, we obtained land cover information for 20 villages in southwestern Ghana from high resolution satellite images, and analyzed the landscape pattern surrounding each village. Eight landscape metrics indicated that landscape patterns between BU case and reference villages were different (P < 0.05) at the broad spatial extent examined (4 km). The logistic regression models showed that landscape fragmentation and diversity indices were positively associated with BU presence in a village. Specifically, for each increase in patch density and edge density by 100 units, the likelihood of BU presence in a village increased 2.51 (95% confidence interval [CI] = 1.36–4.61) and 4.18 (95% CI = 1.63–10.76) times, respectively. The results suggest that increased landscape fragmentation may pose a risk to the emergence of BU

Estimating Root Zone Soil Moisture Across the Eastern United States with Passive Microwave Satellite Data and a Simple Hydrologic Model

Root zone soil moisture (RZSM) affects many natural processes and is an important component of environmental modeling, but it is expensive and challenging to monitor for relatively small spatial extents. Satellite datasets offer ample spatial coverage of near-surface soil moisture content at up to a daily time-step, but satellite-derived data products are currently too coarse in spatial resolution to use directly for many environmental applications, such as those for small catchments. This study investigated the use of passive microwave satellite soil moisture data products in a simple hydrologic model to provide root zone soil moisture estimates across a small catchment over a two year time period and the Eastern U.S. (EUS) at a 1 km resolution over a decadal time-scale. The physically based soil moisture analytical relationship (SMAR) was calibrated and tested with the Advanced Microwave Scanning Radiometer (AMSRE), Soil Moisture Ocean Salinity (SMOS), and Soil Moisture Active Passive (SMAP) data products. The SMAR spatial model relies on maps of soil physical properties and was first tested at the Shale Hills experimental catchment in central Pennsylvania. The model met a root mean square error (RMSE) benchmark of 0.06 cm3 cm−3 at 66% of the locations throughout the catchment. Then, the SMAR spatial model was calibrated at up to 68 sites (SCAN and AMERIFLUX network sites) that monitor soil moisture across the EUS region, and maps of SMAR parameters were generated for each satellite data product. The average RMSE for RZSM estimates from each satellite data product is <0.06 cm3 cm−3. Lastly, the 1 km EUS regional RZSM maps were tested with data from the Shale Hills, which was set aside for validating the regional SMAR, and the RMSE between the RZSM predictions and the catchment average is 0.042 cm3 cm−3. This study offers a promising approach for generating long time-series of regional RZSM maps with the same spatial resolution of soil property maps

Patch-scale selection patterns of grazing herbivores in the central basalt plains of Kruger National Park

Large herbivores form an essential component in the ecosystem, because of the impact that they have on their surrounding habitat. In this study, we aimed to evaluate some of the mechanisms behind how herbivores select forage at a patch scale. Thirty-six experimental plots were established and fitted with camera traps in Kruger National Park to test forage selectivity by grazers. Plots were manipulated by clearing with a brush cutter and the application of fertiliser. We used generalised linear models to detect trends in probability of occurrence by seven grazing herbivore species using camera trap data. Our results showed that season was a major determinant of species distribution, especially those that are not obligate grazers or feed exclusively in the 0.5 km to 2 km zone from water. We found that most selective feeding occurred in the late wet season when water would be more evenly distributed across the landscape and forage resources close to water would have had the chance to recover from depletion, as a result of dry season use. This has implications for the distribution of artificial water points across the landscape, because areas of reserve forage must be maintained to alleviate grazing pressure close to water.Appendix A: AICc model results for each species probability of presence; 1, 2 and 3 represent the three best predictive models with lowest aICc values and ‘Pred’ represents the predictive model against which general models were tested. Shortened variable names are as follow: ‘Dist’ = distance from water; ‘Fert’ = fertilised; ‘MownFert’ = mown and fertilised; ‘Pred’ = predator incidence (yes or no).The Nelson Mandela University, Fairfield tours and a DSt-NRF grant.http://www.tandfonline.com/loi/tarf202021-06-29hj2021Mammal Research Institut

The landscape‐scale drivers of herbivore assemblage distribution on the central basalt plains of Kruger National Park

The distribution and abundance of herbivores in African savannas are constrained by interactions between abiotic and biotic factors. At the species-level, herbivores face trade-offs among foraging requirements, vegetation structure and the availability of surface water that change over spatial and temporal scales. Characterizing herbivore requirements is necessary for the management of the environment in which they occur, as conservation management interventions such as fencing and artificial water provision consequently have effects on how herbivores address these trade-offs. We tested the effects of environmental attributes on the probability of presence of herbivore functional types at different distances to water in the Satara section of Kruger National Park over the period of a year. Hypotheses about species’ relative distribution and abundance were developed through a literature review of forage and water availability constraints on feeding preference and body size of herbivore. We expected strong seasonal relationships between vegetation biomass and quality, and biomass of water-dependent herbivores with increasing distance to water. Our analyses of herbivore distribution across the region confirmed broad-scale descriptions of interactions between forage requirements and water availability across a set of species which differ in functional traits.Nelson Mandela University, Fairfield Tours and DST-NRF.https://www.cambridge.org/core/journals/journal-of-tropical-ecologyhj2020Mammal Research Institut

Carbon stocks and biodiversity of coastal lowland forests in South Africa: implications for aligning sustainable development and carbon mitigation initiatives

Indigenous forests represent South Africa’s smallest biome, yet they are critical spaces for aligning sustainable development goals with carbon mitigation activities and conservation. The objectives of this study were to quantify the productivity and biodiversity of coastal lowland forests in the Dwesa Cwebe nature reserve in the Eastern Cape Province and characterize how estimates differed among alternative allometric equations. Using a complete tree census across six plots in the reserve, a total of 1489 trees were inventoried in 2011 and again in 2016. Aboveground tree carbon averaged 99.8 Mg C ha−1 (range 77.2–126.9 Mg C ha−1) using locally derived equations and 214.6 Mg C ha−1 using generalized equations. Tree aboveground net primary productivity averaged 1041.8 g C m−2 y−1. Forty-eight tree species were identified, including many species important to the livelihoods of local communities for medicinal, ceremonial, and other provisioning services. Overall, this study shows that current conservation activities are concomitant with high tree productivity and high levels of C stocks and biodiversity, including species of local and regional significance. Sustaining forest productivity and biodiversity in the future will be critical for maintaining ecosystem services and enhancing stewardship of forest resources in the region

Improving the Representation of Roots in Terrestrial Models

Root biomass, root production and lifespan, and root-mycorrhizal interactions govern soil carbon fluxes and resource uptake and are critical components of terrestrial models. However, limitations in data and confusions over terminology, together with a strong dependence on a small set of conceptual frameworks, have limited the exploration of root function in terrestrial models. We review the key root processes of interest to both field ecologists and modelers including root classification, production, turnover, biomass, resource uptake, and depth distribution to ask (1) what are contemporary approaches for modeling roots in terrestrial models? and (2) can these approaches be improved via recent advancements in field research methods? We isolate several emerging themes that are ready for collaboration among field scientists and modelers: (1) alternatives to size-class based root classifications based on function and the inclusion of fungal symbioses, (2) dynamic root allocation and phenology as a function of root environment, rather than leaf demand alone, (3) improved understanding of the treatment of root turnover in models, including the role of root tissue chemistry on root lifespan, (4) better estimates of root stocks across sites and species to parameterize or validate models, and (5) dynamic interplay among rooting depth, resource availability and resource uptake. Greater attention to model parameterization and structural representation of roots will lead to greater appreciation for belowground processes in terrestrial models and improve estimates of ecosystem resilience to global change drivers

Grassland productivity in response to nutrient additions and herbivory is scale-dependent

Vegetation response to nutrient addition can vary across space, yet studies that explicitly incorporate spatial pattern into experimental approaches are rare. To explore whether there are unique spatial scales (grains) at which grass response to nutrients and herbivory is best expressed, we imposed a large (∼3.75 ha) experiment in a South African coastal grassland ecosystem. In two of six 60 × 60 m grassland plots, we imposed a scaled sampling design in which fertilizer was added in replicated sub-plots (1 × 1 m, 2 × 2 m, and 4 × 4 m). The remaining plots either received no additions or were fertilized evenly across the entire area. Three of the six plots were fenced to exclude herbivory. We calculated empirical semivariograms for all plots one year following nutrient additions to determine whether the scale of grass response (biomass and nutrient concentrations) corresponded to the scale of the sub-plot additions and compared these results to reference plots (unfertilized or unscaled) and to plots with and without herbivory. We compared empirical semivariogram parameters to parameters from semivariograms derived from a set of simulated landscapes (neutral models). Empirical semivariograms showed spatial structure in plots that received multi-scaled nutrient additions, particularly at the 2 × 2 m grain. The level of biomass response was predicted by foliar P concentration and, to a lesser extent, N, with the treatment effect of herbivory having a minimal influence. Neutral models confirmed the length scale of the biomass response and indicated few differences due to herbivory. Overall, we conclude that interpretation of nutrient limitation in grasslands is dependent on the grain used to measure grass response and that herbivory had a secondary effect

Climate, Fire and Carbon: Tipping Points and Landscape Vulnerability in the Greater Yellowstone Ecosystem

More frequent fires under climate warming are likely to alter terrestrial carbon (C) stocks by reducing the amount of C stored in biomass and soil. However, the thresholds of fire frequency that could shift landscapes from C sinks to C sources under future climates and whether these are likely to be exceeded during the coming century are not known. We used the Greater Yellowstone Ecosystem (GYE) as a case study to explore the conditions under which future climate and fire regimes would result in tipping points of C source/sink dynamics. We asked: (1) How great a change in climate and fire regime would be required to shift each of the dominant vegetation communities in the GYE from a net C sink to a net C source? (2) Do current projections indicate that changes of this magnitude are likely to occur in the next century, and if so, where in the GYE do they occur? and (3) What are the integrated effects of changing climate, vegetation, and fire on spatial patterns of C flux across the GYE landscape as a whole? To answer these questions, we developed downscaled climate projections for the GYE for three general circulation models and used these projections in dynamic and statistical modeling approaches. Using the CENTURY ecosystem model, we simulated C storage for individual forest stands under three fire-event pathways (fires at 90, 60 or every 30 years) to year 2100 compared to a reference simulation (no fire, representing the historical fire interval) under both future and current climate scenarios. Our results show that fire intervals would need to be less than 90 years for lodgepole pine (Pinus contorta var. latifolia) forest stands to shift from a net C sink to a net C source because the time between fires would be less than the time required to recover 85% of the C lost to fire (Question 1). We also developed new statistical models to relate monthly climate data to the occurrence of large fires (\u3e 200 ha) and area burned, evaluated these for the 1972-1999 time period, and then used these relationships to predict fire occurrence and area burned in the GYE through 2100 given the downscaled climate projections. Results showed that anticipated climate changes are likely to increase fire frequency and annual area burned over the next century compared to the observational record. However, the timing of these changes and the probability of future largescale 1988-type fires depended on the type of climate-fire model that was used, the accuracy of the simulated future climates, and to a small degree, the specific climate simulation. The climatefire frequency and climate-fire size models are extremely sensitive to temperature differences between the projected future climate and the 1961-1990 base period because the two large fire years that occurred in the 1972-1999 climate-fire model calibration period had relatively small temperature anomalies (0.5 to 1 °C) and the small sample size of the large fire years in the time series makes model building a challenge. Between now and 2050, where we have the most confidence in the model, all climate scenarios and both fire-climate model formulations projected at least two 1988 sized fires (range 2-6, fires projected to be \u3e 300,000 ha). After 2050, climatic conditions are sufficiently outside the historic range of variability used to estimate statistical fire models that those models cannot be used to characterize the magnitude of extreme fire years. However, extreme fire years from 2050-2100 will almost certainly become more common then projected for 2010-2050, because temperature is projected to continue to increase while precipitation is projected to remain at historical levels. We note, however, that projected changes in temperature by the climate scenarios only reach the historical differences in temperature between a subalpine forest (with an historical fire return interval of \u3e 100 years) and a montane forest (with an historical fire return interval of \u3c 30 years) by the end of this century (5-6 °C). In the northern Rocky Mountains, large fire years have been driven historically by extreme climate conditions. Our results imply that fuel availability would become increasingly important for fire as weather conditions conducive to large fires become common. The capacity for fast post-fire regeneration of lodgepole pine from an aerial seedbank (serotinous cones) and the projected increase in lodgepole pine productivity under warmer climate conditions are unlikely to counter the anticipated reductions in fire-return interval. In all future climate scenarios, decreases in fire-return interval are likely to reduce the potential of the GYE landscape to store C (Question 3). The magnitude of this shift will depend on the future distribution of forest and nonforest ecosystems across the landscape, other constraints on fire patterns not considered here (fuels, ignition factors, and landscape management), and the accuracy of the fire-climate model as future climate diverges increasingly from the past. If past climate-fire relationships can predict the future, soon after 2050 climate conditions projected by all three general circulation models would likely result in more fire than the current conifer forest ecosystem in the GYE could sustain. Forest managers should be considering the potential for qualitative shifts in forest distribution and regional C storage to occur before 2100