Topp, K., Eory, V., Bannink, A., Bartley, D. J., Blanco-Penedo, I., Cortignani, R., et al. (2017). Modelling climate change adaptation in European agriculture: Definitions and Current Modelling (Vol. 10).
Abstract: Confidential content, in preparation for a peer-reviewed publication.
|
Topp, K. (2016). Case 4: Adaptation of European dairy farms to climate change: a case study approach.. Rotterdam (Netherlands).
Abstract: Presentation SC 2.10 Farming systems. Case 4: Adaptation of European dairy farms to climate change: a case study approach, Kairsty Topp, Scotland's Rural College, United Kingdom (2016). Presented at the international conference Adaptation Futures 2016, Rotterdam, the Netherlands. No Label
|
Topp, K. (2015). Synergies and trade-offs of adaptation and mitigation on dairy farms (Vol. 5).
Abstract: Livestock farms with ruminants have large and diverse fluxes of greenhouse gases, but are also affected in diverse ways by climate change. This calls for assessments of possible options to mitigate GHG and to adapt to changing climate, primarily at the farm-scale. This study focuses on the effects of adaptation and mitigation options, and their synergies and trade-offs on GHG emissions and production on European dairy farms. The impact of climate change on livestock production systems will vary with livestock type, system design and local conditions. These effects are direct through impacts on animal performance and indirect through effects on crop yield and quality. These impacts demand adaptations of farming systems to cope with the changed climate. Adaptation can be categorized in three main categories: feed, livestock and water management. Several of these adaptation options have impact on greenhouse gas emissions and thus on the mitigation potential. There is therefore need to align measures for reducing greenhouse gas emissions with the likely adaptations to be adopted. Based on expert opinion, assessments have been performed on which adaptation and mitigation measures would likely be adopted for real on maritime dairy farms located in Ireland and the Netherlands. No Label
|
Kipling, R. P., Don, A., & Topp, K. (2014). Assessing the availability of data on grassland Carbon sequestration in Europe. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The role of grasslands in the sequestration of atmospheric Carbon represents an important benefit of extensive livestock systems based on permanent grasslands. The accurate modelling of such systems is key to understanding their potential in mitigating GHG emissions, and this in turn relies on access to high quality data. Here, the availability of Carbon sequestration data for EU grasslands is investigated, using information gathered from reviews of journal papers and EU project outputs. The challenges involved in providing information on datasets to modellers are discussed, and the next steps in the gathering and sharing of meta-data are defined.
|
Kipling, R., Topp, K., & Don, A. (2014). Appropriate meta-data for modellers (Vol. 3).
Abstract: Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label
|
