Farm Diversification in Relation to Landscape Properties

Current European Common Agricultural Policy (CAP) has been moving from production support subsidies to direct decoupled income support. The emergence in policy making of the concept of multifunctional agriculture leads to the recognition that a farmer produces more than food: he produces jointly both commodity and non-commodity goods. Environmental contracts were developed in order to encourage the provision of non-commodity goods such as landscape or biodiversity. Next to these contracts, other activities as for example recreation can be observed. They are the result of farm diversification. The role of location in farmers’ decision making to diversify is pointed out in literature but geographical information is generally reduced to the location within a political delimitation unit the empirical work. Objective of this paper is two-fold. Firstly, it addresses the role of location, in term of site specific natural conditions as well as neighbouring emerging dynamics in farmer’s decision making to diversify. Attention is paid to number of activities as well as the specific types of activities, notably green services, daily recreation and other farm-linked services. Secondly, this paper introduces income from agriculture explicitly allowing testing short term price sensitivity. It was found that attractive landscape is a driver for diversification as these landscape offer more opportunities. Furthermore, diversification is responsive to price. Thirdly, role of density of past multifunctional activities in the neighborhood influences farm diversification: multifunctional activities create an externality effects as new activities emerge next to already existing ones. This dynamic may lead to the emergence of ‘multifunctional hotspots’ in landscape.Farmer diversification, landscape services, location, Farm Management, Land Economics/Use,

Ideotyping integrated aquaculture systems to balance soil nutrients

Due to growing land scarcity and lack of nutrient inputs, African farmers switched from shifting cultivation to continuous cropping and extended crop area by bringing fragile lands such as river banks and hill slopes into production. This accelerated soil fertility decline caused by erosion, harvesting and insufficient nutrient replenishment. We explored the feasibility to reduce nutrient depletion by increasing nutrient utilization efficiencies, while diversifying and increasing food production through the development of integrated aquaculture – agriculture (IAA). Considering the climatic conditions prevailing in Kenyan highlands, aquaculture production scenarios were ideotyped per agro-ecological zone. These aquaculture production scenarios were integrated into existing NUTrient MONitoring (NUTMON) farm survey data for the area. The nutrient balances and flows of the resulting IAA-systems were compared to present land use. The effects of IAA development on nutrient depletion and total food production were evaluated. With the development of IAA systems, nutrient depletion rates dropped by 23–35%, agricultural production increased by 2–26% and overall farm food production increased by 22–70%. The study demonstrates that from a bio-physical point of view, the development of IAA-systems in Africa is technically possible and could raise soil fertility and total farm production. Further studies that evaluate the economic feasibility and impacts on the livelihood of farming households are recommended

Exploring the challenges with soil data in regional land use analysis

Over recent decades, environmental models have gradually replaced traditional, qualitative land evaluation in regional land use analysis (RLUA). This changed the data requirements as the environmental models require quantitative, high resolution and spatially exhaustive data. As resources to collect new data are limited, RLUA often relies on already existing data. These data often do not meet the data requirements for the environmental models. Hence, a gap developed between the supply and demand of data in RLUA. This study aims to explore and analyse the effect of using different soil datasets in a case study for Machakos and Makueni counties (Kenya). Six soil datasets were available for the study area and showed large differences. For example, average clay percentages varied between 11.7% and 44.4%. The soil datasets were developed under different assumptions on e.g., soil variability. Four assumptions were verified using a field survey. An ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, was taken as a case study to analyse the effect of using different soil datasets. The GYGA project aims to assess yield gaps defined as the difference between potential or water-limited yields and actual yields. Rain-fed maize is the dominating cropping system in Machakos and Makueni counties. The GYGA project uses soil data for the selection of the most dominant maize growing areas and to simulate water-limited maize yields. The protocols developed by the GYGA project were applied to the six soil datasets. This resulted in the selection of six different maize-growing areas and different water-limited maize yields. Our study clearly demonstrates the large differences between soil datasets. Main challenges with soil data in RLUA are: i) understand the assumptions in soil datasets, ii) create soil datasets that meet the requirements for regional land use analysis, iii) not only rely on legacy soil data but also collect new soil data and iv) validate soil datasets

CDC2/SPDY transiently associates with endoplasmic reticulum exit sites during oocyte maturation

<p>Abstract</p> <p>Background</p> <p>Mammalian oocytes acquire competence to be fertilized during meiotic maturation. The protein kinase CDC2 plays a pivotal role in several key maturation events, in part through controlled changes in CDC2 localization. Although CDC2 is involved in initiation of maturation, a detailed analysis of CDC2 localization at the onset of maturation is lacking. In this study, the subcellular distribution of CDC2 and its regulatory proteins cyclin B and SPDY in combination with several organelle markers at the onset of pig oocyte maturation has been investigated.</p> <p>Results</p> <p>Our results demonstrate that CDC2 transiently associates with a single domain, identified as a cluster of endoplasmic reticulum (ER) exit sites (ERES) by the presence of SEC23, in the cortex of maturing porcine oocytes prior to germinal vesicle break down. Inhibition of meiosis resumption by forskolin treatment prevented translocation of CDC2 to this ERES cluster. Phosphorylated GM130 (P-GM130), which is a marker for fragmented Golgi, localized to ERES in almost all immature oocytes and was not affected by forskolin treatment. After removal of forskolin from the culture media, the transient translocation of CDC2 to ERES was accompanied by a transient dispersion of P-GM130 into the ER suggesting a role for CDC2 in redistributing Golgi components that have collapsed into ERES further into the ER during meiosis. Finally, we show that SPDY, rather than cyclin B, colocalizes with CDC2 at ERES, suggesting a role for the CDC2/SPDY complex in regulating the secretory pathway during oocyte maturation.</p> <p>Conclusion</p> <p>Our data demonstrate the presence of a novel structure in the cortex of porcine oocytes that comprises ERES and transiently accumulates CDC2 prior to germinal vesicle breakdown. In addition, we show that SPDY, but not cyclin B, localizes to this ERES cluster together with CDC2.</p

Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)

The effects of tillage on soil properties, crop productivity, and global greenhouse gas emissions have been discussed in the last decades. Global ecosystem models have limited capacity to simulate the various effects of tillage. With respect to the decomposition of soil organic matter, they either assume a constant increase due to tillage or they ignore the effects of tillage. Hence, they do not allow for analysing the effects of tillage and cannot evaluate, for example, reduced tillage or no tillage (referred to here as “no-till”) practises as mitigation practices for climate change. In this paper, we describe the implementation of tillage-related practices in the global ecosystem model LPJmL. The extended model is evaluated against reported differences between tillage and no-till management on several soil properties. To this end, simulation results are compared with published meta-analyses on tillage effects. In general, the model is able to reproduce observed tillage effects on global, as well as regional, patterns of carbon and water fluxes. However, modelled N fluxes deviate from the literature values and need further study. The addition of the tillage module to LPJmL5 opens up opportunities to assess the impact of agricultural soil management practices under different scenarios with implications for agricultural productivity, carbon sequestration, greenhouse gas emissions, and other environmental indicators

The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage

No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund–Potsdam–Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions

A method for evaluating climate change adaptation strategies for small-scale farmers using survey, experimental and modeled data

Sub-Saharan Africa (SSA) is predicted to experience considerable negative impacts of climate change. The IPCC Fourth Assessment emphasizes that adaptation strategies are essential. Addressing adaptation in the context of small-scale, semi-subsistence agriculture raises special challenges. High data demands including site-specific bio-physical and economic data are an important constraint. This paper applies a new approach to impact assessment, the Tradeoff Analysis model for Multi-Dimensional impact assessment (TOA-MD), which simulates technology adoption and associated economic, environmental and social outcomes in a heterogeneous farm population for a regional impact assessment. The methodology uses the kinds of survey, experimental and modeled data that are typically available in countries where semi-subsistence systems are important, combined with future socio-economic scenarios based on new scenario pathway concepts being developed by the climate change and impact assessment modeling communities. Characteristics of current and future agricultural systems, including land use, output, output price, cost of production, and farm and household size are analyzed and compared for both current and projected future climate (2030), with and without adaptation, and for different socio-economic scenarios. The methodology is applied to two study areas in Kenya. These case studies show the potential of this approach to provide a flexible, generic framework that can use available and modeled data to evaluate climate impact and adaptation strategies under a range of socio-economic scenarios.This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/agricultural-systems/.Keywords: East Africa, Climate change, Adaptation, TOA-MD model, Socio-economic scenarios, Impact assessmentKeywords: East Africa, Climate change, Adaptation, TOA-MD model, Socio-economic scenarios, Impact assessmen