A Theoretical Framework for Multi-Hazard Risk Mapping on Agricultural Areas Considering Artificial Intelligence, IoT, and Climate Change Scenarios

This work proposes a data-driven theoretical framework for addressing: (i) extreme climate events prediction through multi-hazard risk mapping using remote sensing, artificial intelligence, and hydrological models, considering multiple hazards; and (ii) environmental monitoring using on-site data collection and IoT technologies. The framework considers the possibility of evaluating multiple climate change scenarios for improving decision-making in terms of Government policies and farm planning. Its main requirements are gathered based on a literature review. Several essential metrics that can be evaluated, considering both supervised and unsupervised metrics and key performance indicators considering the triple bottom line aspects, are also proposed. The framework also adopts multi-hazard (considering several hazards) and multi-risk (considering several relevant stakeholders) aspects and can be used to simulate different scenarios, an essential task for improving decision-making.

The importance of plant diversity in the ecological management of insects in agroecosystems: a review

The objective of this study is to evaluate the importance of plant diversity in insect management in agroecosystems.The conventional management of agroecosystems is based on monoculture, with exploitation of plant genotypes susceptible to pests and diseases, with intense use of agrochemicals and soil mechanization. The impact on agroecosystem biodiversity by intensifying agronomic practices results in losses of important ecological functions: decomposition, nutrient cycling, predation and parasitism. The potential of plant diversity in the sustainability of agroecosystems is recommended through practices such as intercropping, agroforestry systems, management of cover crops, spontaneous herbs and the use of plants attractive to natural enemies and as pest traps. Farm planning should take into account some level of plant diversification to avoid pest insect outbreaks. Thus, it will be possible to reduce pesticides in conventional system, and reduce the number of interventions with alternative substances in farm in agroecological systems.

Residents’ Views on Landscape and Ecosystem Services during a Wind Farm Proposal in an Island Protected Area

Industrial wind farms are being developed within many protected areas, such as in EU Natura 2000 sites; this includes proposals on small Mediterranean islands, such as Samothraki in Greece. Scarce wild land areas on islands may be particularly vulnerable to landscape-scale degradation; this may have serious negative societal impacts. Samothraki’s resident perceptions were surveyed in the wake of such a proposal, in June 2018. Of 98 respondents, 48% reported they were against the wind farm plan, while 22% did not take sides. We compare for-and-against sub-group perceptions of the proposed wind farm with potential impacts on the landscape and explore residents’ opinions on ecosystem services and environmental pressures and threats. Conflict over the wind farm was prevalent; residents most frequently reported that the proposal threatens aesthetic and landscape qualities. Aesthetic qualities were also the second highest ranked ecosystem services, after freshwater provision. However, other threats, such as livestock overgrazing, top residents’ opinion of major environmental problems on the island. The questionnaire survey used provides a scoping assessment, which may assist in identifying "conflict hotspots" for wind farm development. A critical review of wind farm planning in protected areas is presented in light of insights gained from this survey and other relevant studies.

How to improve the state of the art in metocean measurement datasets

We present an analysis of three datasets of 10 min metocean measurement statistics and our resulting recommendations to both producers and users of such datasets. Many of our recommendations are more generally of interest to all numerical measurement data producers. The datasets analyzed originate from offshore meteorological masts installed to support offshore wind farm planning and design: the Dutch OWEZ and MMIJ and the German FINO1. Our analysis shows that such datasets contain issues that users should look out for and whose prevalence can be reduced by producers. We also present expressions to derive uncertainty and bias values for the statistics from information typically available about sample uncertainty. We also observe that the format in which the data are disseminated is sub-optimal from the users' perspective and discuss how producers can create more immediately useful dataset files. Effectively, we advocate using an established binary format (HDF5 or netCDF4) instead of the typical text-based one (comma-separated values), as this allows for the inclusion of relevant metadata and the creation of significantly smaller directly accessible dataset files. Next to informing producers of the advantages of these formats, we also provide concrete pointers to their effective use. Our conclusion is that datasets such as the ones we analyzed can be improved substantially in usefulness and convenience with limited effort.

Opportunities and challenges for seasonal climate forecasts to more effectively assist smallholder farming decisions

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers.