Sensitivity of discharge and flood frequency to twenty-first century and late Holocene changes in climate and land use (River Meuse, northwest Europe)

We used a calibrated coupled climate–hydrological model to simulate Meuse discharge over the late Holocene (4000–3000 BP and 1000–2000 AD). We then used this model to simulate discharge in the twenty-first century under SRES emission scenarios A2 and B1, with and without future land use change. Mean discharge and medium-sized high-flow (e.g. Q99) frequency are higher in 1000–2000 AD than in 4000–3000 BP; almost all of this increase can be attributed to the conversion of forest to agriculture. In the twentieth century, mean discharge and the frequency of medium-sized high-flow events are higher than in the nineteenth century; this increase can be attributed to increased (winter half-year) precipitation. Between the twentieth and twenty-first centuries, anthropogenic climate change causes a further increase in discharge and medium-sized high-flow frequency; this increase is of a similar order of magnitude to the changes over the last 4,000 years. The magnitude of extreme flood events (return period 1,250-years) is higher in the twenty-first century than in any preceding period of the time-slices studied. In contrast to the long-term influence of deforestation on mean discharge, changes in forest cover have had little effect on these extreme floods, even on the millennial timescale

Assessing spatial uncertainties of land allocation using the scenario approach and sensitivity analysis

The paper assess uncertainty of future spatial allocation of agricultural land in Europe. To assess the possible future development of agricultural production and land for the period 2000 – 2030, two contrasting scenarios are constructed. The scenarios storylines lead to different measurable assumptions concerning scenario specific drivers (variables) and parameters. Many of them are estimations and thus include a certain level of uncertainty regarding their true values. This leads to uncertainty of the scenario outcomes. In this study we use sensitivity analysis to estimate the uncertainty of agricultural land use.spatial uncertainty, scenario approach, sensitivity analysis., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

Landbouw en kleinschaligheid kunnen samengaan

De kleinschaligheid en het groene karakter van de Nationale Landschappen op de hoge zandgronden komen onder druk te staan bij een voortschrijdende schaalvergroting in de landbouw. Het opruimen van begroeiingen van percelen is hiervan de belangrijkste oorzaak. Een versterking van de multifuncionele landbouw biedt mogelijkheden de effecten van schaalvergroting te beperken, maar goede financieringsconstructies zijn dan wel nodig

The overlooked spatial dimension of climate-smart agriculture

Climate-smart agriculture (CSA) and sustainable intensification (SI) are widely claimed to be high-potential solutions to address the interlinked challenges of food security and climate change. Operationalization of these promising concepts is still lacking and potential trade-offs are often not considered in the current continental- to global-scale assessments. Here we discuss the effect of spatial variability in the context of the implementation of climate-smart practices on two central indicators, namely yield development and carbon sequestration, considering biophysical limitations of suggested benefits, socioeconomic and institutional barriers to adoption, and feedback mechanisms across scales. We substantiate our arguments by an illustrative analysis using the example of a hypothetical large-scale adoption of conservation agriculture (CA) in sub-Saharan Africa. We argue that, up to now, large-scale assessments widely neglect the spatially variable effects of climate-smart practices, leading to inflated statements about co-benefits of agricultural production and climate change mitigation potentials. There is an urgent need to account for spatial variability in assessments of climate-smart practices and target those locations where synergies in land functions can be maximized in order to meet the global targets. Therefore, we call for more attention toward spatial planning and landscape optimization approaches in the operationalization of CSA and SI to navigate potential trade-offs

How will land degradation neutrality change future land system patterns?:A scenario simulation study

Land degradation is a major global issue and achieving a land degradation-neutral world is one of the Sustainable Development Goals. However, striving for land degradation neutrality (LDN) is challenged by increasing claims on land resources and could result in major land use conflicts. The aim of this study is to demonstrate how LDN can be implemented in land system modelling and how achieving LDN alongside sufficient supplies of food, timber and shelter could affect future land system patterns, using the Republic of Turkey as a case study. We developed a LDN scenario with full implementation of the guidelines and a business-as-usual scenario without pursuing LDN, and compared the resulting differences in land system changes. Additionally, the influence of different elements of the LDN framework on the land use projections was tested. Our results show that although it is possible to achieve LDN in the context of increasing demands for resources and housing, it might require a considerable re-organization of the land systems. Intensification of annual cropland systems was the main driver of new land degradation, which was in the LDN scenario primarily counterbalanced by large areas of afforestation, while other land improvement options only played a minor role. To achieve a no-net-loss, about 20% of Turkey’s territory was afforested in our scenario, mainly claiming extensively used annual cropland (~70%) and grassland (~30%). All individual LDN principles had a substantial impact on the final land system patterns meaning that the final outcome is not the result of just one of the principles, it is affected by all. Our findings suggest that pursuing LDN under growing demands for land-based products could stimulate a land sparing approach which might have trade-offs with other sustainability dimensions. This highlights the need for local support and new solutions for rural areas, thereby avoiding poverty, migration and illegal use of restoration areas

The environmental benefits of investment in agricultural science and technology: an application of global spatial benefit transfer

Food security is a major current and future policy concern. The world population is projected to reach 9 billion by 2050 and continuing growth in economic output and incomes is expected to result in changing food consumption patterns. In particular the wider adoption of ‘Western’ diets will result in both higher calorie intake and greater meat consumption. Continuing climate change is expected to add further pressures to agricultural production. This paper presents the results of a global analysis funded by the TEEB study on the environmental benefits of investment in agricultural knowledge, science and technology, specifically in terms of closing the gaps between developing and developed country agricultural productivity. The results show that by easing pressures on land use change on terrestrial biomes (forests and grasslands), and the ecosystem services they provide, investment in agricultural science and technology provides environmental benefits of US$161.3bn per annum in 2050. Between 2000 and 2050 these benefits amount to US$2,964bn in addition to US$6,343bn in carbon benefits and compare to costs of US$5,68bnResearch and Development/Tech Change/Emerging Technologies,

A global assessment of gross and net land change dynamics for current conditions and future scenarios

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth System Models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models, by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5-degree grid cells were substantially larger than net changes in all parts of the world. As 0.5- degree grid cells are a standard resolution of Earth System Models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50% more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as empirical database for land change dynamics that can be applied in Earth System Models and Integrated Assessment Model

Expanding the toolbox : Assessing methods for local outdoor recreation planning

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