Global Transition Rules for Translating Land-use Change (LUH2) To Land-cover Change for CMIP6 using GLM2

Information on historical land-cover change is important for understanding human impacts on the environment. Over the last decade, global models have characterized historical land-use changes, but few have been able to relate these changes with corresponding changes in land-cover. Utilizing the latest global land-use change data, we make several assumptions about the relationship between land-use and land-cover change, and evaluate each scenario with remote sensing data to identify optimal fit. The resulting transition rule can guide the incorporation of land-cover information within earth system models

Clinical Validation of a Sensitive Test for Saliva Collected in Healthcare and Community Settings with Pooling Utility for Severe Acute Respiratory Syndrome Coronavirus 2 Mass Surveillance

The clinical performance of saliva compared with nasopharyngeal swabs (NPSs) has shown conflicting results in healthcare and community settings. In the present study, a total of 429 matched NPS and saliva sample pairs, collected in either healthcare or community setting, were evaluated. Phase-1 (protocol U) tested 240 matched NPS and saliva sample pairs; phase 2 (SalivaAll protocol) tested 189 matched NPS and saliva sample pairs, with an additional sample homogenization step before RNA extraction. A total of 85 saliva samples were evaluated with both protocols. In phase-1, 28.3% (68/240) samples tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from saliva, NPS, or both. The detection rate from saliva was lower compared with that from NPS samples (50.0% versus 89.7%). In phase-2, 50.2% (95/189) samples tested positive for SARS-CoV-2 from saliva, NPS, or both. The detection rate from saliva was higher compared with that from NPS samples (97.8% versus 78.9%). Of the 85 saliva samples evaluated with both protocols, the detection rate was 100% for samples tested with SalivaAll, and 36.7% with protocol U. The limit of detection with SalivaAll protocol was 20 to 60 copies/mL. The pooled testing approach demonstrated a 95% positive and 100% negative percentage agreement. This protocol for saliva samples results in higher sensitivity compared with NPS samples and breaks the barrier to using pooled saliva for SARS-CoV-2 testing

Disturbance distance: quantifying forests' vulnerability to disturbance under current and future conditions

Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbanceinfo:eu-repo/semantics/publishedVersio

Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity)

Recent Land Use Change to Agriculture in the U.S. Lake States: Impacts on Cellulosic Biomass Potential and Natural Lands.

Perennial cellulosic feedstocks may have potential to reduce life-cycle greenhouse gas (GHG) emissions by offsetting fossil fuels. However, this potential depends on meeting a number of important criteria involving land cover change, including avoiding displacement of agricultural production, not reducing uncultivated natural lands that provide biodiversity habitat and other valued ecosystem services, and avoiding the carbon debt (the amount of time needed to repay the initial carbon loss) that accompanies displacing natural lands. It is unclear whether recent agricultural expansion in the United States competes with lands potentially suited for bioenergy feedstocks. Here, we evaluate how recent land cover change (2008-2013) has affected the availability of lands potentially suited for bioenergy feedstock production in the U.S. Lake States (Minnesota, Wisconsin, Michigan) and its impact on other natural ecosystems. The region is potentially well suited for a diversity of bioenergy production systems, both grasses and woody biomass, due to the widespread forest economy in the north and agricultural economy in the south. Based on remotely-sensed data, our results show that between 2008 and 2013, 836,000 ha of non-agricultural open lands were already converted to agricultural uses in the Lake States, a loss of nearly 37%. The greatest relative changes occurred in the southern half that includes some of the most diverse cultivable lands in the country. We use transition diagrams to reveal gross changes that can be obscured if only net change is considered. Our results indicate that expansion of row crops (corn, soybean) was responsible for the majority of open land loss. Even if recently lost open lands were brought into perennial feedstock production, there would a substantial carbon debt. This reduction in open land availability for biomass production is closing the window of opportunity to establish a sustainable cellulosic feedstock economy in the Lake States as mandated by current Federal policy, incurring a substantial GHG debt, and displacing a range of other natural ecosystems and their services

Percentage of open land loss within each site-quality class for each year starting from 2009.

<p>Percentage of open land loss within each site-quality class for each year starting from 2009.</p

Genetic diversity of X-STR markers in Jat Sikh population of Punjab, India and its comparison with other 39 global populations

Background The Jat Sikh population is the largest endogamous group of Punjab, a state in north-west India, and has not yet been explored for genetic polymorphism based on X-STR genetic markers. In India, which is the second most populous country in the world, only two population studies based on X-STR markers have been reported so far. Aim To explore the genetic diversity of 12 X chromosomal STR genetic markers in the Jat Sikh population of Punjab and expand the X-STR polymorphism database. Subjects and methods In this study, a total of 200 Jat Sikh individuals (100 males and 100 females) residing in Punjab were investigated for 12 X-STR markers using the Investigator Argus X-12 QS Kit. Results The highest power of discrimination (PD) in females (PDf) and males (PDm) was observed to be 0.965 (DXS10135) and 0.929 (DXS10135 and DXS10148), respectively. DXS10135 was found to be the most polymorphic and discriminating locus among all the studied loci in both males and females with highest values of power of discrimination (PD) and polymorphic information content (PIC) as well. Conclusion Overall, the studied markers of the Argus 12 X-STR kit provide high polymorphic information which may prove to be an important tool in resolving issues such as missing person identification, incest, immigration disputes, kinship analysis and genealogical studies. The dataset obtained from this study will add to the present database of X-STRs

Pixels used in the “Biophysical Land Identification” analysis (Fig 2).

<p>The data have been filtered to remove single pixels and areas in public holding. Each pixel has been color-coded to indicate its site-quality class.</p