Search Results
Management-induced changes in soil organic carbon on global croplands
Soil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975-2010, this SOC debt continued to expand by 5 GtC (0.14 GtCyr-1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtCyr-1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement - also within computationally demanding integrated (land use) assessment modeling.
Planned relocation in Peru: advancing from well-meant legislation to good practice
Along Peru’s rainforest rivers, rising flood extremes are increasingly exceeding coping capacities of vulnerable households. Peru has detailed legislation that embraces planned relocation as a strategic solution to such situations and various relocation projects are underway across the country. This research brief analyzes well-being consequences for two communities requesting relocation, using qualitative data collected from experts and 30 affected people. Initial results emphasize that weak governance, poverty, third-party involvement, and community action have influenced relocation outcomes. Delays and fragmented implementation have threatened people’s well-being. One community, waiting for land to relocate since 2015, has suffered from continued hazard exposure, deteriorated material conditions, and reduced subjective well-being. The second community achieved relocation only after a decade in detrimental limbo. Although livelihood challenges persist, its inhabitants now benefit from better market access and decreased exposure, leading to higher subjective well-being. With rising needs for relocation worldwide, the cases highlight that detailed legislation is not sufficient to safeguard people’s well-being. Advancing from well-meant legislation to good practice requires adequate institutional capacity, effective mechanisms for oversight and accountability, better engagement of third parties, and dedicated efforts to strengthen community agency.
Tackling unresolved questions in forest ecology: The past and future role of simulation models
Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.
Quantifying the road‐effect zone for a critically endangered primate
The global road network is expanding at an unprecedented rate, threatening the persistence of many species. Yet, even for the most endangered wildlife, crucial information on the distance up to which roads impact species abundance is lacking. Here we use ecological threshold analysis to quantify the road-effect zone (REZ) for the critically endangered western chimpanzee (Pan troglodytes verus). We found: (1) the REZ extends 5.4 km (95% CI [4.9–5.8 km]) from minor roads and 17.2 km (95% CI [15.8–18.6]) from major roads, the latter being more than three times wider than a previous estimate of the average REZ for mammals; and (2) only 4.3% of the chimpanzees’ range is not impacted by existing roads. These findings reveal the high sensitivity and susceptibility of nonhuman primates to roads across West Africa, a region undergoing rapid development, and can inform the implementation of more effective guidelines to mitigate road impacts.
Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests
A variety of modelling studies have suggested tree rooting depth as a key variable to explain evapotranspiration rates, productivity and the geographical distribution of evergreen forests in tropical South America. However, none of those studies have acknowledged resource investment, timing and physical constraints of tree rooting depth within a competitive environment, undermining the ecological realism of their results. Here, we present an approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 (Lund-Potsdam-Jena managed Land) dynamic global vegetation model (DGVM) and apply it to tropical and sub-tropical South America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulation of intra-annual productivity and evapotranspiration and consequently of forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and below-ground biomass across the study region. Our findings support the hypothesis that the ability of evergreen trees to adjust their rooting systems to seasonally dry climates is crucial to explaining the current dominance, productivity and evapotranspiration of evergreen forests in tropical South America.
Brain Mechanisms of COVID-19-Sleep Disorders
2020 and 2021 have been unprecedented years due to the rapid spread of the modified severe acute respiratory syndrome coronavirus around the world. The coronavirus disease 2019 (COVID-19) causes atypical infiltrated pneumonia with many neurological symptoms, and major sleep changes. The exposure of people to stress, such as social confinement and changes in daily routines, is accompanied by various sleep disturbances, known as ‘coronasomnia’ phenomenon. Sleep disorders induce neuroinflammation, which promotes the blood–brain barrier (BBB) disruption and entry of antigens and inflammatory factors into the brain. Here, we review findings and trends in sleep research in 2020–2021, demonstrating how COVID-19 and sleep disorders can induce BBB leakage via neuroinflammation, which might contribute to the ‘coronasomnia’ phenomenon. The new studies suggest that the control of sleep hygiene and quality should be incorporated into the rehabilitation of COVID-19 patients. We also discuss perspective strategies for the prevention of COVID-19-related BBB disorders. We demonstrate that sleep might be a novel biomarker of BBB leakage, and the analysis of sleep EEG patterns can be a breakthrough non-invasive technology for diagnosis of the COVID-19-caused BBB disruption.
Evaluating the grassland NPP dynamics in response to climate change in Tanzania
Livestock is important for livelihoods of millions of people across the world and yet climate change risk and impacts assessments are predominantly on cropping systems. Climate change has significant impacts on Net Primary Production (NPP) which is a grassland dynamics indicator. This study aimed to analyze the spatio-temporal changes of NPP under climate scenario RCP2.6 and RCP8.5 in the grassland of Tanzania by 2050 and link this to potential for key livestock species. To this end, a regression model to estimate NPP was developed based on temperature (T), precipitation (P) and evapotranspiration (ET) during the period 2001–2019. NPP fluctuation maps under future scenarios were produced as difference maps of the current (2009–2019) and future (2050). The vulnerable areas whose NPP is mostly likely to get affected by climate change in 2050 were identified. The number of livestock units in grasslands was estimated according to NPP in grasslands of Tanzania at the Provincial levels. The results indicate the mean temperature and evapotranspiration are projected to increase under both emission scenarios while precipitation will decrease. NPP is significantly positively correlated with Tmax and ET and projected increases in these variables will be beneficial to NPP under climate change. Increases of 17% in 2050 under RCP8.5 scenario are projected, with the southern parts of the country projected to have the largest increase in NPP. The southwest areas showed a decreasing trend in mean NPP of 27.95% (RCP2.6) and 13.43% (RCP8.5). The highest decrease would occur in the RCP2.6 scenario in Ruvuma Province, by contrast, the mean NPP value in the western, eastern, and central parts would increase in 2050 under both Scenarios, the largest increase would observe in Kilimanjaro, Dar-Es-Salaam and Dodoma Provinces. It was found that the number of grazing livestock such as cattle, sheep, and goats will increase in the Tanzania grasslands under both climate scenarios. As the grassland ecosystems under intensive exploitation are fragile ecosystems, a combination of improving grassland productivity and grassland conservation under environmental pressures such as climate change should be considered for sustainable grassland management.
Global and country-level data of the biodiversity footprints of 175 crops and pasture
The destruction of natural habitat for cropland and pasture represents a major threat to global biodiversity. Despite widespread societal concern about biodiversity loss associated with food production, consumer access to quantitative estimates of the impact of crop production on the world's species has been very limited compared to assessments of other environmental variables such as greenhouse gas emissions or water use. Here, we present a consistent dataset of the biodiversity footprints of pasture and 175 crops at the global and national level. The data were generated by combining maps of the global distribution of agricultural areas in the year 2000 with spatially explicit estimates of the biodiversity loss associated with the conversion of natural habitat to farmland. Estimates were derived for three common alternative measures of biodiversity - species richness, threatened species richness, and range rarity - of the world's mammals, birds, and amphibians. Our dataset provides important quantitative information for food consumers and policy makers, allowing them to take evidence-based decisions to reduce the biodiversity footprint of global food production.
Avenues of archetype analysis: roots, achievements, and next steps in sustainability research
Recent years have seen a proliferation of studies that use archetype analysis to better understand and to foster transitions toward sustainability. This growing literature reveals a common methodological ground, as well as a variety of perspectives and practices. In this paper, we provide an historical overview of the roots of archetype analysis from ancient philosophy to recent sustainability science. We thereby derive core features of the archetype approach, which we frame by eight propositions. We then introduce the Special Feature, “Archetype Analysis in Sustainability Research,” which offers a consolidated understanding of the approach, a portfolio of methods, and quality criteria, as well as cutting-edge applications. By reflecting on the Special Feature’s empirical and methodological contributions, we hope that the showcased advances, exemplary applications, and conceptual clarifications will help to design future research that contributes to collaborative learning on archetypical patterns leading toward sustainability. The paper concludes with an outlook highlighting central directions for the next wave of archetype analyses.
Bioenergy for climate change mitigation: Scale and sustainability
Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of bioenergy, often used in conjunction with carbon capture and storage. We review the literature on bioenergy use for climate change mitigation, including studies that use top-down integrated assessment models or bottom-up modelling, and studies that do not rely on modelling. We summarize the state of knowledge concerning potential co-benefits and adverse side effects of bioenergy systems and discuss limitations of modelling studies used to analyse consequences of bioenergy expansion. The implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and how bioenergy alters energy systems and land use. Depending on previous land use, widespread deployment of monoculture plantations may contribute to mitigation but can cause negative impacts across a range of other sustainability criteria. Strategic integration of new biomass supply systems into existing agriculture and forest landscapes may result in less mitigation but can contribute positively to other sustainability objectives. There is considerable variation in evaluations of how sustainability challenges evolve as the scale of bioenergy deployment increases, due to limitations of existing models, and uncertainty over the future context with respect to the many variables that influence alternative uses of biomass and land. Integrative policies, coordinated institutions and improved governance mechanisms to enhance co-benefits and minimize adverse side effects can reduce the risks of large-scale deployment of bioenergy. Further, conservation and efficiency measures for energy, land and biomass can support greater flexibility in achieving climate change mitigation and adaptation.