Agro-environmental Research Research Articles

Tools for an efficient witness

Expectations that research should not only generate real-world impacts but do so in a way that provides “value-for-money” pervade academia and the contemporary knowledge economy. In agricultural research for development, this imperative has spawned “tools” that promise rapidly scalable scientific knowledge on everything from gender inequality to environmental degradation. This promise of speed and scale relies on formal protocols that attempt to deskill data collection so that it can be done by anyone. Drawing ethnography of an agro-environmental research institute in southwest China into conversation with the idea of the scientist as “modest witness,” I show that as well as marginalizing qualitative research, imperatives for efficiency suffocate space for the unspoken informal practices that undergird the ostensibly formal methods of agricultural and environmental scientists. I demonstrate, moreover, how efficient research extends hierarchies of epistemological worth that undermine the contributions of administrative and nonfaculty staff to universities and the sciences.

Simultaneous Calibration of Grapevine Phenology and Yield with a Soil–Plant–Atmosphere System Model Using the Frequentist Method

Reliable estimations of parameter values and associated uncertainties are crucial for crop model applications in agro-environmental research. However, estimating many parameters simultaneously for different types of response variables is difficult. This becomes more complicated for grapevines with different phenotypes between varieties and training systems. Our study aims to evaluate how a standard least square approach can be used to calibrate a complex grapevine model for simulating both the phenology (flowering and harvest date) and yield of four different variety–training systems in the Douro Demarcated Region, northern Portugal. An objective function is defined to search for the best-fit parameters that result in the minimum value of the unweighted sum of the normalized Root Mean Squared Error (nRMSE) of the studied variables. Parameter uncertainties are estimated as how a given parameter value can determine the total prediction variability caused by variations in the other parameter combinations. The results indicate that the best-estimated parameters show a satisfactory predictive performance, with a mean bias of −2 to 4 days for phenology and −232 to 159 kg/ha for yield. The corresponding variance in the observed data was generally well reproduced, except for one occasion. These parameters are a good trade-off to achieve results close to the best possible fit of each response variable. No parameter combinations can achieve minimum errors simultaneously for phenology and yield, where the best fit to one variable can lead to a poor fit to another. The proposed parameter uncertainty analysis is particularly useful to select the best-fit parameter values when several choices with equal performance occur. A global sensitivity analysis is applied where the fruit-setting parameters are identified as key determinants for yield simulations. Overall, the approach (including uncertainty analysis) is relatively simple and straightforward without specific pre-conditions (e.g., model continuity), which can be easily applied for other models and crops. However, a challenge has been identified, which is associated with the appropriate assumption of the model errors, where a combination of various calibration approaches might be essential to have a more robust parameter estimation.

Impact, theory of change, and the horizons of scientific practice.

Demands for research to generate impact, along with proliferating institutional regimes for evaluating impact, are a ubiquitous aspect of contemporary scientific practice. Based on participant observation at an agro-environmental research institute in southwest China, this article explores three iterations of a tool for planning and evaluating impactful science called 'theory of change' (TOC). Despite their ostensible common grounding in TOC, I show how an impact scientist's framework, a donor's monitoring and evaluation regime, and a communication consultant's branding strategy each suggest very different normative structures for scientific practice. These structures entail: particular horizons towards which scientific research is to be practiced, precise points in time at which the future effects of research are to be anticipated, and specific assumptions about how scientists' agency should play out across time. Taking the peculiar sensibilities of TOC as a comparative framework, I illuminate IFF scientists' implicit imaginations of how contemporary science does and should generate effects in the world.

Mapping LUCAS topsoil chemical properties at European scale using Gaussian process regression

This paper presents the second part of the mapping of topsoil properties based on the Land Use and Cover Area frame Survey (LUCAS). The first part described the physical properties (Ballabio et al., 2016) while this second part includes the following chemical properties: pH, Cation Exchange Capacity (CEC), calcium carbonates (CaCO3), C:N ratio, nitrogen (N), phosphorus (P) and potassium (K). The LUCAS survey collected harmonised data on changes in land cover and the state of land use for the European Union (EU). Among the 270,000 land use and cover observations selected for field visit, approximately 20,000 soil samples were collected in 24 EU Member States in 2009 together with more than 2000 samples from Bulgaria and Romania in 2012. The chemical properties maps for the European Union were produced using Gaussian process regression (GPR) models. GPR was selected for its capacity to assess model uncertainty and the possibility of adding prior knowledge in the form of covariance functions to the model.The derived maps will establish baselines that will help monitor soil quality and provide guidance to agro-environmental research and policy developments in the European Union.

Expansion of pistachio cultivation in the Iberian Peninsula: keys to the future

Only 15 years ago pistachio was an almost unknown crop in Spain and Portugal. However, nowadays pistachio production has become a benchmark in terms of profitability of agricultural products. Currently the cultivated area is larger than 15,000 ha and the growth rate is over 40% year-1. The reasons for this are: firstly, the good prices at the point of origin, (with a continuous growth during the last 6 years), and secondly, because of the good adaptation of pistachio tree to the agroclimatic conditions in the interior of the Iberian Peninsula. As well, these conditions have favored the production of organic pistachio, which has a very important demand and a high difference with the conventional pistachio price (> € 2 kg-1). “El Chaparrillo”, an Agro-Environmental Research Center (CAC) has led this change, thanks to the research, experimentation and agricultural outreach done by it. Particularly relevant for the spreading of technical knowledge are two governmental initiatives; the first one is the virtual community for professionals involved in pistachio production, which includes news and events from sector and a public forum to solve technical questions. And the other is the operational group for the sustainable production of quality pistachio, included in the European Association for Innovation in Productivity and Agricultural Sustainability, (EAI-AGRI), with EU financial support.

Does Federal Crop Insurance Make Environmental Externalities from Agriculture Worse?

Farmers dramatically increased their use of federal crop insurance in the 2000s. From 2000 to 2013, premium subsidies increased sevenfold and acres enrolled increased by 77%. Although designed for nonenvironmental goals, subsidized insurance may affect the use of land, fertilizer, and agrochemicals and, therefore, environmental externalities from agriculture. Using novel panel data, we examine farmer responses to changes in coverage with an empirical approach that exploits program limits on coverage that were more binding for some farmers than for others. Estimates indicate that expanded coverage had little effect on the share of farmland harvested, crop specialization, productivity, or fertilizer and chemical use. More broadly, we construct and describe a new nationwide, farm-level panel data set with nearly 32,500 farms observed at least twice over the 2000–2013 period, a resource that should enrich US agro-environmental research.

Analysis of Big Data technologies for use in agro-environmental science

Recent developments like the movements of open access and open data and the unprecedented growth of data, which has come forward as Big Data, have shifted focus to methods to effectively handle such data for use in agro-environmental research. Big Data technologies, together with the increased use of cloud based and high performance computing, create new opportunities for data intensive science in the multi-disciplinary agro-environmental domain. A theoretical framework is presented to structure and analyse data-intensive cases and is applied to three case studies, together covering a broad range of technologies and aspects related to Big Data usage. The case studies indicate that most persistent issues in the area of data-intensive research evolve around capturing the huge heterogeneity of interdisciplinary data and around creating trust between data providers and data users. It is therefore recommended that efforts from the agro-environmental domain concentrate on the issues of variety and veracity.

An Evaluation of the Introduction of Modified Cropping Practices in Yunnan Province, China, Using Surveys of Farmers' Households

Problems associated with land degradation are serious in China. Sloping land in South China has experienced a decline in crop productivity by 30-60% due to soil erosion and it has been predicted that most topsoil will be lost within the next 100 years if current erosion rates continue. Considering these situations, an agro-environmental research and development project (Sustainable Highland Agriculture in South-East Asia – SHASEA) was conducted in a catchment in Yunnan Province, China, to address the objectives of increasing crop productivity in sustainable and environmentally-friendly ways. A range of cropping practices was developed and implemented in a rural upland catchment (Wang Jia). At the end of the project, farmers were surveyed to evaluate project effectiveness. All farmers from Wang Jia Catchment, who were involved in project implementation, were surveyed. A sample of farmers working in an adjacent catchment (not associated with the project) was surveyed for comparative purposes. Farmers had different perceptions of the cropping practices employed. Contour cultivation was preferred and likely to be adopted. Others practices such as straw mulching and intercropping were seen as less appropriate and unlikely to be adopted. Polythene mulch was recognized as effective, but likely to be adopted only if financial returns were favourable. The availability of relevant information had an important impact on the extent of technology testing by farmers and their willingness to adopt the practices in the future.

Modeling water temperature in a rice paddy for agro-environmental research

Water temperature in rice paddies ( Oryza sativa L.) is one of the most important factors affecting the growth and yield of rice, and also influences CH 4 emission from paddy fields. We developed a simple model of the daily mean water temperature in a rice paddy. The model has two steps for evaluating the paddy water temperature. In the first step, the daily mean water temperature of a non-vegetated water surface ( T ¯ w 0 ) is evaluated from meteorological data (air temperature, specific humidity, wind speed, solar radiation, and downward longwave radiation) by daily 24-h mean or daytime (nighttime) 12-h mean heat balance equations. The bulk heat transfer coefficient at the water surface is a key parameter for evaluating T ¯ w 0 . Next, the daily mean water temperature in a rice paddy ( T ¯ w ) is evaluated by adding a correction term to T ¯ w 0 . Here, the correction term is described as a function of the leaf area index (LAI), solar radiation, and wind speed, and the formula was determined empirically. The model simulated fairly well the daily mean water temperature of rice paddies with root mean square errors of 0.81–0.85 °C. This study also demonstrated the important result that the influence of a plant canopy on water temperature depends not only on canopy density (LAI), but also on solar radiation and wind speed. T ¯ w was usually lower than T ¯ w 0 , but in rice paddies with LAI = 0.5–1.5, T ¯ w was higher than T ¯ w 0 under strong wind conditions in sunny weather. These characteristics were incorporated into the model developed in this study.

The Role of Action Research (AR) in Environmental Research: Learning from a Local Organic Food and Farming Research Project

We expand on the FMA model of inquiry elucidated by Checkland and Holwell (Syst Pract Act Res 11:9, 1998) and identify three kinds of research: interactive Action Research (AR), extractive participatory research, and traditional science, that were integrated into an interdisciplinary agro-environmental research project involving researchers from eight countries around the Baltic Sea. The research project held the goal of creating scientific understanding of the ecological, economic and social effects of the sustainable development of local food systems, while also having the explicit goal of implementing change in the studied systems. Based on our experience working as action researchers in the project, we highlight the role that normative goals and facilitation process competence play in complex interdisciplinary research projects. Our reflections focus on project design, including the relation between AR and other kinds of research when employed in a single project, and includes reflections on preconditions for stakeholder participation in AR projects.

Development of Database System Related to Agro-Environmental Research Information

Development of Database System Related to Agro-Environmental Research Information