Reconstructing the provenance of the hominin fossils from Trinil (Java, Indonesia) through an integrated analysis of the historical and recent excavations.

In the early 1890s at Trinil, Eugène Dubois found a hominin skullcap (Trinil 2) and femur (Trinil 3, Femur I), situated at the same level ca. 10-15 m apart. He interpreted them as representing one species, Pithecanthropus erectus (now Homo erectus) which he inferred to be a transitional form between apes and humans. Ever since, this interpretation has been questioned-as the skullcap looked archaic and the femur surprisingly modern. From the 1950s onward, chemical and morphological analyses rekindled the debate. Concurrently, (bio)stratigraphic arguments gained importance, raising the stakes by extrapolating the consequences of potential mixing of hominin remains to the homogeneity of the complete Trinil fossil assemblage. However, conclusive evidence on the provenance and age of the hominin fossils remains absent. New Trinil fieldwork yielded unmanned aerial vehicle imagery, digital elevation models, and stratigraphic observations that have been integrated here with an analysis of the historical excavation documentation. Using a geographic information system and sightline analysis, the position of the historical excavation pits and the hominin fossils therein were reconstructed, and the historical stratigraphy was connected to that of new sections and test pits. This study documents five strata situated at low water level at the excavation site. Cutting into a lahar breccia are two similarly oriented, but asynchronous pre-terrace fluvial channels whose highly fossiliferous infills are identified as the primary targets of the historical excavations (Bone-Bearing Channel 1, 830-773 ka; Bone-Bearing Channel 2, 560-380 ka), providing evidence for a mixed faunal assemblage and yielding most of the hominin fossils. These channels were incised by younger terrace-related fluvial channels (terminal Middle or Late Pleistocene) that directly intersect the historical excavations and the reconstructed discovery location of Femur I, thereby providing an explanation for the relatively modern morphology of this 'bone of contention'. The paleoanthropological implications are discussed in light of the current framework of human evolution in Southeast Asia.

Using Routinely Collected Health Records to Identify the Fine-Resolution Spatial Patterns of Soil-Transmitted Helminth Infections in Rwanda.

Background. Soil-transmitted helminths (STH) are parasitic diseases with significant public health impact. Analysis is generally based on cross-sectional prevalence surveys; outcomes are mostly aggregated to larger spatial units. However, recent research demonstrates that infection levels and spatial patterns differ between STH species and tend to be localized. Methods. Incidence data of STHs including roundworm (Ascaris lumbricoides), whipworm (Trichuris trichiura) and hookworms per primary health facility for 2008 were linked to spatially delineated primary health center service areas. Prevalence data per district for individual and combined STH infections from the 2008 nationwide survey in Rwanda were also obtained. Results. A comparison of reported prevalence and incidence data indicated significant positive correlations for roundworm (R2 = 0.63) and hookworm (R2 = 0.27). Weak positive correlations were observed for whipworm (R2 = 0.02) and the three STHs combined (R2 = 0.10). Incidence of roundworm and whipworm were found to be focalized with significant spatial autocorrelation (Moran's I > 0: 0.05−0.38 and p ≤ 0.03), with (very) high incidence rates in some focal areas. In contrast, hookworm incidence is ubiquitous and randomly distributed (Moran's I > 0: 0.006 and p = 0.74) with very low incidence rates. Furthermore, an exploratory regression analysis identified relationships between helminth infection cases and potential environmental and socio-economic risk factors. Conclusions. Findings show that the spatial distribution of STH incidence is significantly associated with soil properties (sand proportion and pH), rainfall, wetlands and their uses, population density and proportion of rural residents. Identified spatial patterns are important for guiding STH prevention and control programs.

Ten facts about land systems for sustainability.

Land use is central to addressing sustainability issues, including biodiversity conservation, climate change, food security, poverty alleviation, and sustainable energy. In this paper, we synthesize knowledge accumulated in land system science, the integrated study of terrestrial social-ecological systems, into 10 hard truths that have strong, general, empirical support. These facts help to explain the challenges of achieving sustainability in land use and thus also point toward solutions. The 10 facts are as follows: 1) Meanings and values of land are socially constructed and contested; 2) land systems exhibit complex behaviors with abrupt, hard-to-predict changes; 3) irreversible changes and path dependence are common features of land systems; 4) some land uses have a small footprint but very large impacts; 5) drivers and impacts of land-use change are globally interconnected and spill over to distant locations; 6) humanity lives on a used planet where all land provides benefits to societies; 7) land-use change usually entails trade-offs between different benefits-"win-wins" are thus rare; 8) land tenure and land-use claims are often unclear, overlapping, and contested; 9) the benefits and burdens from land are unequally distributed; and 10) land users have multiple, sometimes conflicting, ideas of what social and environmental justice entails. The facts have implications for governance, but do not provide fixed answers. Instead they constitute a set of core principles which can guide scientists, policy makers, and practitioners toward meeting sustainability challenges in land use.

Modeling schistosomiasis spatial risk dynamics over time in Rwanda using zero-inflated Poisson regression.

The recorded clinical cases of S. mansoni at primary health facility level contain an excessive number of zero records. This could mean that no S. mansoni infection occurred (a true zero) in the health facility service area but it could also that at least one infection occurred but none were reported or diagnosed (a false zero). Standard statistical analysis, using exploratory or confirmatory spatial regression, fail to account for this type of data insufficiency. This study developed a zero-inflated Poisson model to explore the spatiotemporal variation in schistosomiasis risk at a fine spatial scale. We used environmental data generated at primary health facility service area level as explanatory variables affecting transmission risk. Identified risk factors were subsequently used to project the spatial variability of S. mansoni infection risk for 2050. The zero-inflated Poisson model shows a considerable increase of relative risk of the schistosomiasis over one decade. Furthermore, the changes between the risk in 2009 and forecasted risk by 2050 indicated both persistent and emerging areas with high relative risk of schistosomiasis infection. The risk of schistosomiasis transmission is 69%, 29%, and 50% higher in areas with rice cultivation, proximity to rice farms, and proximity to a water body respectively. The prediction and forecasting maps provide a valuable tool for monitoring schistosomiasis risk in Rwanda and planning future disease control initiatives in wetland ecosystem development context.

Spatio-temporal dynamics of schistosomiasis in Rwanda between 2001 and 2012: impact of the national Neglected Tropical Disease control programme.

Schistosomiasis is recognised as a major public health problem in Rwanda. We aimed to identify the spatio-temporal dynamics of its distribution at a fine-scale spatial resolution and to explore the impact of control programme interventions. Incidence data of Schistosoma mansoni infection at 367 health facilities were obtained for the period 2001-2012. Disease cluster analyses were conducted using spatial scan statistics and geographic information systems. The impact of control interventions was assessed for three distinct sub-periods. Findings demonstrated persisting, emerging and re-emerging clusters of schistosomiasis infection across space and time. The control programme initially caused an abrupt increase in incidence rates during its implementation phase. However, this was followed by declining and disappearing clusters when the programme was fully in place. The findings presented should contribute to a better understanding of the dynamics of schistosomiasis distribution to be used when implementing future control activities, including prevention and elimination efforts.

Modelling potential landscape sediment delivery due to projected soybean expansion: a scenario study of the Balsas sub-basin, Cerrado, Maranhão state, Brazil.

In Brazil, agriculture expansion is taking place primarily in the Cerrado ecosystems. With the aim of supporting policy development and protecting the natural environment at relevant hotspots, a scenario study was conducted that concerned not only land-use change, but also the resulting effects on erosion and deposition. This coupled approach helped to evaluate potential landscape impacts of the land-use scenarios. In the study area, the Balsas sub-basin in Maranhão State, a model chain was used to model plausible future soybean expansion locations (CLUE-S model) and resulting sediment mobilization patterns (LAPSUS model) for a business-as-usual scenario. In the scenario, more erosion occurred in areas where the conversion of natural vegetation into soybean cultivation is likely to take place, but the generated sediments tended to accumulate mainly within the conversion areas, thus limiting the offsite effects of the increased erosion. These results indicated that when agricultural expansion is kept away from rivers, Cerrado conversion will have only a limited impact on the sediment loads of local rivers. Where land-use changes are most concentrated are coincident with areas where more new sediments are generated (higher erosion) and where more sediments are re-deposited.

Improving national-scale carbon stock inventories using knowledge on land use history.

National-scale inventories of soil organic carbon (SOC) and forest floor carbon (FFC) stocks have a high uncertainty. Inventories are often based on the interpolation of sampled information, often using a number of covariables to help such interpolation. The rationale for the choice of these covariables is not always documented, despite the fact that many local-scale studies have identified the factors explaining spatial variability of SOC and FFC stocks. These studies indicate, among others the importance of long-term land use history. Despite this, information on the effects of land use history has never been used to explain variability of carbon stocks in national-scale inventories. We designed an alternative method to improve national-scale inventories of SOC and FCC for the Dutch sand area that takes stock of the findings of detailed case studies. Determinants for SOC and FFC stocks derived from landscape-scale case studies were used to map national-scale spatial variability and to calculate national totals. The resulting national-scale spatial distribution was compared with the SOC stock map from the current Dutch greenhouse gas inventory. Using land use history to explain SOC variability decreased the error of the SOC stock estimate in 60 % of the area. The error in FFC stocks decreased in half of the forest area after including soil fertility, tree species, and forest age as explanatory factors. Estimates with reduced uncertainty will make land use and land management a more attractive and acceptable mitigation option to reduce emissions of greenhouse gases for the LULUCF sector.