•The impact of grazing on SOC is climate-dependent.•Grazing increases SOC for C4 but decreases it for C3 and C3-C4 mixed grasslands.•Grazing increases TN and BD but has no effect on soil pH.
...Livestock grazing intensity (GI) is thought to have a major impact on soil organic carbon (SOC) storage and soil quality indicators in grassland agroecosystems. To critically investigate this, we conducted a global review and meta-analysis of 83 studies of extensive grazing, covering 164 sites across different countries and climatic zones. Unlike previous published reviews we normalized the SOC and total nitrogen (TN) data to a 30cm depth to be compatible with IPCC guidelines. We also calculated a normalized GI and divided the data into four main groups depending on the regional climate (dry warm, DW; dry cool, DC; moist warm, MW; moist cool, MC). Our results show that taken across all climatic zones and GIs, grazing (below the carrying capacity of the systems) results in a decrease in SOC storage, although its impact on SOC is climate-dependent. When assessed for different regional climates, all GI levels increased SOC stocks under the MW climate (+7.6%) whilst there were reductions under the MC climate (−19%). Under the DW and DC climates, only the low (+5.8%) and low to medium (+16.1%) grazing intensities, respectively, were associated with increased SOC stocks. High GI significantly increased SOC for C4-dominated grassland compared to C3-dominated grassland and C3-C4 mixed grasslands. It was also associated with significant increases in TN and bulk density but had no effect on soil pH. To protect grassland soils from degradation, we recommend that GI and management practices should be optimized according to climate region and grassland type (C3, C4 or C3-C4 mixed).
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further ...to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Quantifying changes in thermokarst lake extent is of importance for understanding the permafrost‐related carbon budget, including the potential release of carbon via lake expansion or sequestration ...as peat in drained lake basins. We used high spatial resolution remotely sensed imagery from 1950/51, 1978, and 2006/07 to quantify changes in thermokarst lakes for a 700 km2 area on the northern Seward Peninsula, Alaska. The number of water bodies larger than 0.1 ha increased over the entire observation period (666 to 737 or +10.7%); however, total surface area decreased (5,066 ha to 4,312 ha or −14.9%). This pattern can largely be explained by the formation of remnant ponds following partial drainage of larger water bodies. Thus, analysis of large lakes (>40 ha) shows a decrease of 24% and 26% in number and area, respectively, differing from lake changes reported from other continuous permafrost regions. Thermokarst lake expansion rates did not change substantially between 1950/51 and 1978 (0.35 m/yr) and 1978 and 2006/07 (0.39 m/yr). However, most lakes that drained did expand as a result of surface permafrost degradation before lateral drainage. Drainage rates over the observation period were stable (2.2 to 2.3 per year). Thus, analysis of decadal‐scale, high spatial resolution imagery has shown that lake drainage in this region is triggered by lateral breaching and not subterranean infiltration. Future research should be directed toward better understanding thermokarst lake dynamics at high spatial and temporal resolution as these systems have implications for landscape‐scale hydrology and carbon budgets in thermokarst lake‐rich regions in the circum‐Arctic.
Key Points
Landscape scale assessment of thermokarst lake expansion and drainage rates
Widespread drainage of thermokarst lakes in the continuous permafrost zone
Thermokarst lake dynamics impact the northern high latitude carbon cycle
This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also ...coupled to a fast 'climate analogue model', based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate-carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra-tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The authors show that the diverse mutations in
CALR
that occur in nonmutated
JAK2
myeloproliferative diseases all introduce frameshift mutations that alter the C-terminal part of the protein and ...affect its distribution within cells.
The myeloproliferative neoplasms are chronic myeloid cancers that are characterized by the overproduction of mature blood cells, and that may evolve into acute myeloid leukemia.
1
,
2
In addition to chronic myeloid leukemia with the
BCR-ABL
fusion gene, the three most common myeloproliferative neoplasms are essential thrombocythemia, polycythemia vera, and myelofibrosis.
Many patients with a
BCR-ABL–
negative myeloproliferative neoplasm carry a Janus kinase 2 (
JAK2
) V617F mutation.
3
–
6
The
JAK2
V617F mutation or
JAK2
exon 12 mutations are found in most patients with polycythemia vera,
7
,
8
whereas the
JAK2
V617F mutation is found in only 50 to 60% of . . .
The promise of “personalized medicine” guided by an understanding of each individual's genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant ...information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision‐support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health‐care provider, identification of relevant genetic variations for implementation, assay reliability, point‐of‐care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point‐of‐care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.
Clinical Pharmacology & Therapeutics (2012); 92 1, 87–95. doi:10.1038/clpt.2011.371
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Realised ES are a product of the potential service and specified beneficiaries.•Natural capital (NC) and human-derived capital (HDC) are both essential for ES.•HDC plays a role even at the stage of ...potential ecosystem services.•It is possible but not always easy to separate the contribution of NC and HDC to ES.•Sustainable management should identify critical NC and HDC for each service.
Display omitted
There is growing interest in the role that natural capital plays in underpinning ecosystem services. Yet, there remain differences and inconsistencies in the conceptualisation of capital and ecosystem services and the role that humans play in their delivery. Using worked examples in a stocks and flows systems approach, we show that both natural capital (NC) and human-derived (produced, human, social, cultural, financial) capital (HDC) are necessary to create ecosystem services at many levels. HDC plays a role at three stages of ecosystem service delivery. Firstly, as essential elements of a combined social-ecological system to create a potential ecosystem service. Secondly, through the beneficiaries in shaping the demand for that service. Thirdly, in the form of additional capital required to realise the ecosystem service flow. We show that it is possible, although not always easy, to separately identify how these forms of capital contribute to ecosystem service flow. We discuss how applying a systems approach can help identify critical natural capital and critical human-derived capital to guide sustainable management of the stocks and flows of all forms of capital which underpin provision of multiple ecosystem services. The amount of realised ecosystem service can be managed in several ways: via the NC & HDC which govern the potential service, and via factors which govern both the demand from the beneficiaries, and the efficiency of use of the potential service by those beneficiaries.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
▶ Tomato leaves were infected with bacterial leaf spot of tomato. ▶ Leaves were rated for disease severity and leaf reflectance was measured. ▶ Significant wavelengths were identified using ...chemometric methods. ▶ The best model predicted the disease severity with a RMSD of 4.9% and
R
2 of 0.82.
Ultraviolet, visible, and near-infrared reflectance spectroscopy was used to determine the disease severity of tomato (
Lycopersicon esculentum) leaves infected with
Xanthomonas perforans, the causal agent of bacterial leaf spot of tomato. Chemometric methods were used to identify significant wavelengths and create spectral-based prediction models. Significant wavelengths were identified through analysis of the
B-matrix from partial least squares (PLS) regression, analysis of a correlation coefficient spectrum, and through the use of a stepwise multiple linear regression (SMLR) procedure. These analysis methods revealed several significant regions wavelengths and produced predictive models of disease severity based on absorbance spectra. The best model predicted the disease severity of the validation data set with a root mean square difference (RMSD) of 4.9% and a coefficient of determination (
R
2) of 0.82. The results of this initial study indicate the potential for the use of spectral technology to detect bacterial leaf spot of tomato in the field.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The effects of land-use changes on climate are assessed using specified-concentration simulations complementary to the representative concentration pathway 2.6 (RCP2.6) and RCP8.5 scenarios performed ...for phase 5 of the Coupled Model Intercomparison Project (CMIP5). This analysis focuses on differences in climate and land–atmosphere fluxes between the ensemble averages of simulations with and without land-use changes by the end of the twenty-first century. Even though common land-use scenarios are used, the areas of crops and pastures are specific for each Earth system model (ESM). This is due to different interpretations of land-use classes. The analysis reveals that fossil fuel forcing dominates land-use forcing. In addition, the effects of land-use changes are globally not significant, whereas they are significant for regions with land-use changes exceeding 10%. For these regions, three out of six participating models—the Second Generation Canadian Earth System Model (CanESM2); Hadley Centre Global Environmental Model, version 2 (Earth System) (HadGEM2-ES); and Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM)—reveal statistically significant changes in mean annual surface air temperature. In addition, changes in land surface albedo, available energy, and latent heat fluxes are small but significant for most ESMs in regions affected by land-use changes. These climatic effects are relatively small, as land-use changes in the RCP2.6 and RCP8.5 scenarios are small in magnitude and mainly limited to tropical and subtropical regions. The relative importance of the climatic effects of land-use changes is higher for the RCP2.6 scenario, which considers an expansion of biofuel croplands as a climate mitigation option. The underlying similarity among all models is the loss in global land carbon storage due to land-use changes.
Full text
Available for:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To limit global warming to <2 °C we must reduce the net amount of CO2 we release into the atmosphere, either by producing less CO2 (conventional mitigation) or by capturing more CO2 (negative ...emissions). Here, using state-of-the-art carbon-climate models, we quantify the trade-off between these two options in RCP2.6: an Intergovernmental Panel on Climate Change scenario likely to limit global warming below 2 °C. In our best-case illustrative assumption of conventional mitigation, negative emissions of 0.5-3 Gt C (gigatonnes of carbon) per year and storage capacity of 50-250 Gt C are required. In our worst case, those requirements are 7-11 Gt C per year and 1,000-1,600 Gt C, respectively. Because these figures have not been shown to be feasible, we conclude that development of negative emission technologies should be accelerated, but also that conventional mitigation must remain a substantial part of any climate policy aiming at the 2-°C target.
PDF
