Pytrik Reidsma

Regional Farm Diversity Can Reduce Vulnerability of Food Production to Climate Change

Food production must adapt in the face of climate change. In Europe, projected vulnerability of food production to climate change is particularly high in Mediterranean regions. Increasing agricultural diversity has been suggested as an adaptation strategy, but empirical evidence is lacking. We analyzed the relationship between regional farm diversity (i.e., diversity among farm types) and the effects of climate variability on regional wheat ( Triticum spp.) productivity. An extensive data set with information from more than 50 000 farms from 1990 to 2003 was analyzed, along with observed weather data. Our results suggest that the diversity in farm size and intensity, particularly high in Mediterranean regions, reduces vulnerability of regional wheat yields to climate variability. Accordingly, increasing regional farm diversity can be a strategy through which regions in Europe can adapt to unfavorable conditions, such as higher temperatures and associated droughts.

Scenarios of long-term farm structural change for application in climate change impact assessment

Towards 2050, climate change is one of the possible drivers that will change the farming landscape, but market, policy and technological development may be at least equally important. In the last decade, many studies assessed impacts of climate change and specific adaptation strategies. However, adaptation to climate change must be considered in the context of other driving forces that will cause farms of the future to look differently from today’s farms. In this paper we use a historical analysis of the influence of different drivers on farm structure, complemented with literature and stakeholder consultations, to assess future structural change of farms in a region under different plausible futures. As climate change is one of the drivers considered, this study thus puts climate change impact and adaptation into the context of other drivers. The province of Flevoland in the north of The Netherlands was used as case study, with arable farming as the main activity. To account for the heterogeneity of farms and to indicate possible directions of farm structural change, a farm typology was developed. Trends in past developments in farm types were analyzed with data from the Dutch agricultural census. The historical analysis allowed to detect the relative importance of driving forces that contributed to farm structural changes. Simultaneously, scenario assumptions about changes in these driving forces elaborated at global and European levels, were downscaled for Flevoland, to regional and farm type level in order to project impacts of drivers on farm structural change towards 2050. Input from stakeholders was also used to detail the downscaled scenarios and to derive historical and future relationships between drivers and farm structural change. These downscaled scenarios and future driver-farm structural change relationships were used to derive quantitative estimations of farm structural change at regional and farm type level in Flevoland. In addition, stakeholder input was used to also derive images of future farms in Flevoland. The estimated farm structural changes differed substantially between the two scenarios. Our estimations of farm structural change provide a proper context for assessing impacts of and adaptation to climate change in 2050 at crop and farm level.

The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands

Abstract The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter.

Participatory impact assessment of agricultural practices using the land use functions framework: case study from India

What do different stakeholders think of the changing trends in agricultural practices and related policies? We answer this and related questions with respect to Karnataka, an Indian state showing signs of agrarian distress. Using the participatory impact assessment (PIA) method involving farmers, researchers and voluntary workers, we assess the impact of recent policy-driven farming practices. The land use functions (LUFs) framework, which resembles the ecosystem services framework, was adapted in the PIA to address multidimensional sustainability in agricultural landscapes. During the PIAs, participants ranked LUFs in the order of their perceived importance and projected the impact of different practice–policy scenarios on chosen indicators corresponding to each LUF. Three farming scenarios, namely organic, conventional (chemically intensive) and mixed input practices were assessed for their projected impacts on selected indicators of each LUF. The LUF ranking reveals that while stakeholder priorities vary, they remain contrasting to the common policy focus of profit and productivity maximisation. Farmers value familys health and water access the most and financial services the least as functions of their land. Indicator scoring in the PIA revealed that participants rated organic practices as the most beneficial, conventional scenario as detrimental and the now prevailing mixed inputs scenario as having little impact.

Impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China: a multi-scale cause–effect approach considering multiple land-use functions

This paper aims to assess the impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China, and to identify possible conservation strategies. We used the mean species abundance (MSA) approach, building on simple cause–effect relationships between environmental drivers and biodiversity impacts at the global level. Our assessment estimated that 21% of the original species in the undisturbed ecosystem were present in 2000. We also analysed and reviewed agricultural pressures at different spatial scales to enable the development of conservation strategies at regional and farm levels. This analysis showed, first, that intensive crop management is reflected by the amount of fertilisers applied. Policies and technologies aiming to reduce environmental impacts have been ineffective. Second, the abundance of semi-natural elements was found to be low and the fragmentation high. To link agricultural pressures to the MSA approach, we propose a multi-scale cause–effect approach, which can be linked to other land uses. This approach is useful to provide a quick scan of biodiversity status and identify conservation strategies. Training farmers to use site-specific nutrient management should be stimulated. Furthermore, acknowledging multiple land-use functions will help to develop biodiversity conservation strategies that are acceptable to farmers and policymakers.

What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers.

As the sustainability of agricultural citizen science projects depends on volunteer farmers who contribute their time, energy and skills, understanding their motivation is important to attract and retain participants in citizen science projects. The objectives of this study were to assess 1) farmers’ motivations to participate as citizen scientists and 2) farmers’ mobile telephone usage. Building on motivational factors identified from previous citizen science studies, a questionnaire based methodology was developed which allowed the analysis of motivational factors and their relation to farmers’ characteristics. The questionnaire was applied in three communities of farmers, in countries from different continents, participating as citizen scientists. We used statistical tests to compare motivational factors within and among the three countries. In addition, the relations between motivational factors and farmers characteristics were assessed. Lastly, Principal Component Analysis (PCA) was used to group farmers based on their motivations. Although there was an overlap between the types of motivations, for Indian farmers a collectivistic type of motivation (i.e., contribute to scientific research) was more important than egoistic and altruistic motivations. For Ethiopian and Honduran farmers an egoistic intrinsic type of motivation (i.e., interest in sharing information) was most important. While fun has appeared to be an important egoistic intrinsic factor to participate in other citizen science projects, the smallholder farmers involved in this research valued ‘passing free time’ the lowest. Two major groups of farmers were distinguished: one motivated by sharing information (egoistic intrinsic), helping (altruism) and contribute to scientific research (collectivistic) and one motivated by egoistic extrinsic factors (expectation, expert interaction and community interaction). Country and education level were the two most important farmers’ characteristics that explain around 20% of the variation in farmers motivations. For educated farmers, contributing to scientific research was a more important motivation to participate as citizen scientists compared to less educated farmers. We conclude that motivations to participate in citizen science are different for smallholders in agriculture compared to other sectors. Citizen science does have high potential, but easy to use mechanisms are needed. Moreover, gamification may increase the egoistic intrinsic motivation of farmers.

Integrated Assessment Approach

Integrated Assessment (IA) projects are designed to produce practical and interdisciplinary results, thus the final report will differ from that of a traditional research project. The goal of IA is to summarize scientific knowledge in order to build consensus and guide decision making around a particular environmental issue. The emphasis is on collaborative work with stakeholders and analysis of existing data to help clarify the issue, rather than new experiments and data collection. The final report of an IA should: 1) describe the data and methods used, 2) explain the status, trends, causes and impacts of the issue, 3) evaluate practical strategies for addressing the issue, and 4) provide guidance for implementing new strategies.

Scaling Point and Plot Measurements of Greenhouse Gas Fluxes, Balances, and Intensities to Whole Farms and Landscapes

Measurements of nutrient stocks and greenhouse gas (GHG) fluxes are typically collected at very local scales (<1 to 30 m2) and then extrapolated to estimate impacts at larger spatial extents (farms, landscapes, or even countries). Translating point measurements to higher levels of aggregation is called scaling. Scaling fundamentally involves conversion of data through integration or interpolation and/or simplifying or nesting models. Model and data manipulation techniques to scale estimates are referred to as scaling methods.

Impacts of climate change adaptation options on soil functions: A review of European case-studies

Abstract Soils are vital for supporting food security and other ecosystem services. Climate change can affect soil functions both directly and indirectly. Direct effects include temperature, precipitation, and moisture regime changes. Indirect effects include those that are induced by adaptations such as irrigation, crop rotation changes, and tillage practices. Although extensive knowledge is available on the direct effects, an understanding of the indirect effects of agricultural adaptation options is less complete. A review of 20 agricultural adaptation case‐studies across Europe was conducted to assess implications to soil threats and soil functions and the link to the Sustainable Development Goals (SDGs). The major findings are as follows: (a) adaptation options reflect local conditions; (b) reduced soil erosion threats and increased soil organic carbon are expected, although compaction may increase in some areas; (c) most adaptation options are anticipated to improve the soil functions of food and biomass production, soil organic carbon storage, and storing, filtering, transforming, and recycling capacities, whereas possible implications for soil biodiversity are largely unknown; and (d) the linkage between soil functions and the SDGs implies improvements to SDG 2 (achieving food security and promoting sustainable agriculture) and SDG 13 (taking action on climate change), whereas the relationship to SDG 15 (using terrestrial ecosystems sustainably) is largely unknown. The conclusion is drawn that agricultural adaptation options, even when focused on increasing yields, have the potential to outweigh the negative direct effects of climate change on soil degradation in many European regions.

Sustainable development goal 2: improved targets and indicators for agriculture and food security

AbstractThe pursuit of global food security and agricultural sustainability, the dual aim of the second sustainable development goal (SDG-2), requires urgent and concerted action from developing and developed countries. This, in turn, depends on clear and universally applicable targets and indicators which are partially lacking. The novel and complex nature of the SDGs poses further challenges to their implementation on the ground, especially in the face of interlinkages across SDG objectives and scales. Here we review the existing SDG-2 indicators, propose improvements to facilitate their operationalization, and illustrate their practical implementation in Nigeria, Brazil and the Netherlands. This exercise provides insights into the concrete actions needed to achieve SDG-2 across contrasting development contexts and highlights the challenges of addressing the links between targets and indicators within and beyond SDG-2. Ultimately, it underscores the need for integrated policies and reveals opportunities to leverage the fulfillment of SDG-2 worldwide.