19 research outputs found
Modelling spatial variation and environmental impacts of land use change in the exploitation of land-based renewable bioenergy crops
Spatial factors are of particular importance to the sustainability of land based energy crops, due both to the need to minimise feedstock transport, and to the importance of cultivation site attributes in determining key environmental impacts. This study uses geographical information system (GIS) mapping to identify sites suitable for the cultivation of Miscanthus or short rotation coppiced (SRC) SRC willow for co-firing with coal or generation of combined heat and power (CHP). Modelling using an adapted version of DayCent was performed for typical sites to assess variation in yield, nitrous oxide (N2O) emissions, evapotranspiration (ET) and change in soil organic carbon (SOC) according to soil properties, hydrologic regime and previous land use.
Development of the DayCent model as part of this research gave improved simulation of the impacts of tillage on soil porosity, and resultant N2O emissions from soil, and improved simulation of growth of SRC willow following coppicing management, leading to improved yield predictions.
For land use change from arable to perennial cultivation, increased SOC was simulated, along with reduced N2O emissions, particularly on soils prone to anoxia. However, in general, benefits of cultivation of Miscanthus and SRC willow for energy are maximised when the crops are grown at sites where high yields are achieved, and used to generate CHP, since this minimises the land area required per unit energy generated. Further model development work and additional field data for model verification are necessary for firmer conclusions on the change in net greenhouse gas (GHG) emissions following land use change. Additionally, indirect land use change may negate perceived benefits, and locations are difficult to predict or identify in a complex global system.
Given the magnitude of identified variations in yields and changes in N2O emissions, spatial variation in benefits of bioenergy cultivation should be a factor in decisions to provide economic support for cultivation. However, calculations suggest that emissions offset by replacing energy generation from fossil fuels may have greater impact on GHG savings per gigajoule (GJ) than cultivation site attributes. Since total energy conversion efficiency may be in the region of 30% for electricity-only generation and up to 90% for CHP generation, planning feedstock supply chains to maximise efficiency of feedstock end use is therefore beneficial
Agricultural practices drive elevated rates of topsoil decline across Kenya, but terracing and reduced tillage can reverse this
As agricultural land area increases to feed an expanding global population, soil erosion will likely accelerate, generating unsustainable losses of soil and nutrients. This is critical for Kenya where cropland expansion and nutrient loading from runoff and erosion is contributing to eutrophication of freshwater ecosystems and desertification. We used the Revised Universal Soil Loss Equation (RUSLE) to predict soil erosion rates under present land cover and potential natural vegetation nationally across Kenya. Simulating natural vegetation conditions allows the degree to which erosion rates are elevated under current land use practices to be determined. This methodology exploits new digital soil maps and two vegetation cover maps to model topsoil (top 20 cm) erosion rates, lifespans (the mass of topsoil divided by erosion rate), and lateral nutrient fluxes (nutrient concentration times erosion rate) under both scenarios. We estimated the mean soil erosion rate under current land cover at ~5.5 t haâ1 yrâ1, ~3 times the rate estimated for natural vegetation cover (~1.8 t haâ1 yrâ1), and equivalent to ~320 Mt yrâ1 of topsoil lost nationwide. Under present erosion rates, ~8.8 Mt, ~315 Kt, and ~ 110 Kt of soil organic carbon, nitrogen and phosphorous are lost from soil every year, respectively. Further, 5.3 % of topsoils (~3.1 Mha), including at >25 % of croplands, have short lifespans (<100 years). Additional scenarios were tested that assume combinations of terracing and reduced tillage practices were adopted on croplands to mitigate erosion. Establishing bench terraces with zoned tillage could reduce soil losses by â„75 %; up to 87.1 t haâ1 yrâ1. These reductions are comparable to converting croplands to natural vegetation, demonstrating most agricultural soils can be conserved successfully. Extensive long-term monitoring of croplands with terraces and reduced tillage established is required to verify the efficacy of these agricultural support practices as indicated by our modelling
Woodland, cropland and hedgerows promote pollinator abundance in intensive grassland landscapes, with saturating benefits of flower cover
1. Pollinating insects provide economic value by improving crop yield. They are also functionally and culturally important across ecosystems outside of cropland. To understand landscape-level drivers of pollinator declines, and guide policy and intervention to reverse declines, studies must cover (a) multiple insect and plant taxa and (b) a range of agricultural and semi-natural land uses. Furthermore, in an era of woodland restoration initiatives and rewilding ideologies, the contribution of woodland and woody linear features (WLFs; e.g. hedgerows) to pollinator abundance demands further investigation.
2. We demonstrate fine-scale analysis of high-quality, co-located measurements from a national environmental survey. We relate pollinator transect counts to ground-truth habitat and WLF maps across 300 1 km squares in Wales, UK. We look at effects of habitat type, flower cover, WLF density and habitat diversity on summer abundance (July and August) of eight insect groups, representing three insect orders (Lepidoptera, Hymenoptera and Diptera).
3. Compared with improved grassland (the dominant habitat in Wales), pollinator abundance is consistently higher in cropland and woodlandâespecially broadleaved woodland. For mining bees and two hoverfly groups, abundance is predicted to be at least 1.5Ă higher in woodland ecosystems than elsewhere. Furthermore, we estimate contributions of WLFs to abundance in agriculturally improved habitats to be up to 14% for honeybees and up to 21% for hoverflies.
4. The abundance of all insect groups increases with flower cover, which is a key mechanism through which woodland, cropland and grassland support pollinators. Importantly, we observe diminishing returns of increasing flower cover for abundance of non-Apis pollinator groups, expecting roughly twice the increase in abundance per % flower cover from 0% to 5%, as compared with 10% to 15%. However, the shape of the relationship was inverted for honeybees, which showed steeper increases in abundance at higher flower cover.
4. Synthesis and applications: We provide a holistic view of the drivers of pollinator abundance in Wales, in which flower cover, woodland, hedgerows and cropland are critical. We propose a key role for woodland creation, hedge-laying and farmland heterogeneity within future land management incentive schemes. Finally, we suggest targeting of interventions to maximise benefits for non-Apis pollinators. Specifically, increasing floral provision in areas where existing flower cover is lowâfor example, in flower-poor improved grasslandsâcould effectively increase pollinator abundance and diversity while prioritising wild over managed species
Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure
Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies
Detectable clonal mosaicism and its relationship to aging and cancer
In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 Ă 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 Ă 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases
Children, Television Viewing, and Weight Status: Summary and Recommendations from an Expert Panel Meeting
Zones of influence for soil organic matter dynamics: a conceptual framework for data and models
Soil organic matter (SOM) is an indicator of sustainable land management as stated in the global indicator framework of the United Nations Sustainable Development Goals (SDG Indicator 15.3.1). Improved forecasting of future changes in SOM is needed to support the development of more sustainable land management under a changing climate. Current models fail to reproduce historical trends in SOM both within and during transition between ecosystems. More realistic spatioâtemporal SOM dynamics require inclusion of the recent paradigm shift from SOM recalcitrance as an âintrinsic propertyâ to SOM persistence as an âecosystem interactionâ. We present a soil profile, or pedonâexplicit, ecosystemâscale framework for data and models of SOM distribution and dynamics which can better represent land use transitions. Ecosystemâscale drivers are integrated with pedonâscale processes in two zones of influence. In the upper vegetation zone, SOM is affected primarily by plant inputs (aboveâ and belowground), climate, microbial activity and physical aggregation and is prone to destabilization. In the lower mineral matrix zone, SOM inputs from the vegetation zone are controlled primarily by mineral phase and chemical interactions, resulting in more favourable conditions for SOM persistence. Vegetation zone boundary conditions vary spatially at landscape scales (vegetation cover) and temporally at decadal scales (climate). Mineral matrix zone boundary conditions vary spatially at landscape scales (geology, topography) but change only slowly. The thicknesses of the two zones and their transport connectivity are dynamic and affected by plant cover, land use practices, climate and feedbacks from current SOM stock in each layer. Using this framework, we identify several areas where greater knowledge is needed to advance the emerging paradigm of SOM dynamicsâimproved representation of plantâderived carbon inputs, contributions of soil biota to SOM storage and effect of dynamic soil structure on SOM storageâand how this can be combined with robust and efficient soil monitoring