3,834 research outputs found

    Resilience and food security in a food systems context

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    This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners

    Vulnerability of the Nigerian coast and communities to climate change induced coastal erosion

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    Improving coastal resilience to climate change hazards requires understanding past shoreline changes. As the coastal population grows, evaluation and monitoring of shoreline changes are essential for planning and development. Population growth increases exposure to sea level rise and coastal hazards. Nigeria, where the study is situated, is among the top fifteen countries in the world for coastal population exposure to sea level rise. This study provided a novel lens in establishing a link between social factors and the intensifying coastal erosion along the Akwa Ibom State study coast. The mixed-method approach used in the study to assess the vulnerability of the Nigerian coast and communities to climate change-induced coastal erosion proved to be essential in gathering a wide range of data (physical, socio economic, participatory GIS maps and social learning) that contributed to a more robust and holistic assessment of coastal erosion, which is a complex issue due to the interplay between the human and natural environments. Remotely sensed data was used to examine the susceptibility and coastal evolution of Akwa Ibom State over 36 years (1984 -2020). Longer-term (1984- 2020) and short-term (2015-2020) shoreline change analyses were used to understand coastal erosion and accretion. From 1984-2020, the total average linear regression rate (LRR) was - 2.7+0.18m/yr and from 2015-2020, it was -3.94 +1.28m/yr, demonstrating an erosional trend along the study coast. Although the rate of erosion varies along the study coast, the linear regression rates (LRR) results show a predominant trend of erosion in both the short and longer term. According to the 2022 Intergovernmental Panel on Climate Change report, loss of land, loss of assets, community disruption and livelihood, loss of environmental resources, ecosystem, loss of life, or adverse health impact are all potential risks along the African coast due to climate change – this study shows that these risks are already occurring today. To quantify the anticipated future coastal erosion risk by 2040 along the study coast, the findings in this study show an overall average LRR of -2.73+ 0.99 m/yr which anticipates that coastal erosion will still be prevalent along the coast by 2040. And, given the current global climate change situation, should be expected to be much higher than the current forecasting. This study re-conceptualised the European Environmental Agency Driver-Pressure StateImpact-Response (DPSIR) model to show Hazard-Driver-Pressure-State-Impact ResponseObservation causal linkages to coastal erosion hazards. The results showed how human activities and environmental interactions have evolved through time, causing coastal erosion. Removal of vegetation cover/backstop for residential and agricultural purposes, indicate that human activities significantly contribute to the study area's susceptibility, rapid shoreline changes, and vulnerability to coastal erosion, in addition to oceanic and climate change drivers such as sea level rise and storminess. Risk perception of coastal erosion in the study area was analysed using the rhizoanalytic method proposed by Deleueze. The method demonstrates how connections and movements can be related and how data can be used to show multiplicity, mark and unmark ideas, rupture pre-conceptions and make new connections. This study shows that coastal erosion awareness is insufficient to build a long-term management plan and sustain coastal resilience. The Hino's conceptual model which provides in-depth understanding on planned retreat was used to illustrate migratory and planned retreat for the study coast where relocation has already occurred due to coastal erosion. The result fell within the Self-Reliance quadrant, indicating that people left the risk zone without government backing or retreat plans. Other coastal residents who have not relocated fell within the Hunkered Down quadrant, showing that they are willing to stay in the risk zone and cope with the threat unless the government/environmental agencies relocate them. This study shows that coastal resilience requires adaptive capacity and government support. However, multilevel governance has inhibited government-community dialogue and involvement, increasing coastal erosion vulnerability. The coastal vulnerability index to coastal erosion was calculated using the Analytical Hierarchy Process weightings. It revealed that 67.55% of the study coast falls within the high-very high vulnerability class while 32.45% is within the very low-low vulnerability class. This study developed and combined a risk perception index to coastal erosion (RPIerosion) and participatory GIS (PGIS) mapping into a novel coastal vulnerability index called the integrated coastal erosion vulnerability index (ICEVI). The case study evaluation in Akata, showed an improvement in the overall vulnerability assessment to reflect the real-world scenario, which was consistent with field data. This study demonstrated not only the presence and challenges of coastal erosion in the research area but also the relevance of involvement between the local stakeholders, government and environmental agencies. Thus, showing the potential for the perspectives of the inhabitants of these regions to inform the understanding of the resilience capacity of the people impacted, and importantly to inform future co-design and/or selection of effective adaptation methods, to better support coastal climate change resilience in these communities. Overall, the study provides a useful contribution to coastal erosion vulnerability assessments in data-scarce regions more broadly, where the mixed-methods approach used here can be applied elsewhere

    A Bayesian hierarchical assessment of night shift working for offshore wind farms

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    This article presents a Bayesian data‐modelling approach to assessing operational efficiency at offshore wind farms. Input data are provided by an operational database provided by a large offshore wind farm which employs an advanced data management system. We explore the combination of datasets making up the database, using them to train a Bayesian hierarchical model which predicts weekly lost production from corrective maintenance and time‐based availability. The approach is used to investigate the effect of technician work shift patterns, specifically addressing a strategy involving night shifts for corrective maintenance which was employed at the site throughout the winter. It was found that, for this particular site, there is an approximate annual increase in time‐based technical availability of 0.64%. We explore the effect of modelling assumptions on cost savings; specifically, we explore variations in failure rate, price of electricity, number of technicians working night shift, extra staff wages, months of the year employing 24/7 working and extra vessel provision. Results vary quite significantly among the scenarios investigated, exemplifying the need to consider the question on a farm‐by‐farm basis

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    Investigating drivers of cyanobacterial blooms in Aotearoa – New Zealand lakes using sedimentary ancient DNA

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    Healthy lake ecosystems support biodiversity and human populations. They provide many ecosystem services such as water, food and energy. Lakes can be impacted by natural disturbances, but they are increasingly threatened by human-induced disturbances. Studies have shown that eutrophication and climate change often enhance cyanobacteria over other photosynthetic taxa. As cyanobacterial blooms are becoming more frequent and intense throughout the world, more lake systems are being investigated. In some cases there is not a clear link between eutrophication and cyanobacterial blooms. One such example is Lake Pounui (Wairarapa, New Zealand), which has little intensive agriculture in its catchment but water quality has degraded markedly in the last decade. The lake now experiences heavy cyanobacterial blooms every summer. This could be due to the presence of a non-native fish population, the European perch (Perca fluviatilis). This thesis examined the relationship between cyanobacterial blooms and perch introduction in New Zealand lakes, including a multi-trophic study in Lake Pounui. Perch were introduced c. 1870 in New Zealand but introduction records are patchy and sometimes non-existent. Moreover, most lake systems are not studied until they are already degraded. This thesis used a combination of traditional proxies (pollen, charcoal, pigments) and modern proxies (sedimentary ancient DNA, XRF scanning) from lake sediment cores to reconstruct lake ecology in pre-human times, after MÂŻaori settlement between the 13th to 15th century, and after European settlement from 1840 AD. Timelines and intensity of human impact were reconstructed with pollen, charcoal analysis, and sediment dating when possible. Cyanobacterial communities in six lakes were reconstructed through their sedimentary ancient DNA (sedaDNA) using metabarcoding and droplet digital PCR (ddPCR) in Chapter 2. Bloom-forming species were present in all lakes prior to human arrival; however their overall abundance was low. Total cyanobacteria abundance and richness increased in all lakes after European settlement but was very pronounced in four lakes, where bloom-forming taxa became dominant. The trends in cyanobacterial abundance from ddPCR were then compared to cyanobacterial pigments (canthaxanthin, echinenone, myxoxanthophyll and zeaxanthin) using highperformance liquid chromatography in Chapter 3, to assess the likelihood of the historical increase observed. Pigments / sedaDNA relationships were more consistent when all pigments were summed, which is likely due to differences in species composition across lakes. The positive correlations confirmed an increase in cyanobacterial biomass since European arrival. Due to patchy records for fish introduction, fish sedimentary DNA was compared to environmental DNA (eDNA) from water samples as a methodological check (Chapter 4) before applying this method to the sediment cores. This study was undertaken in three small and shallow lowland lakes by targeting perch and rudd (Scardinius erythrophthalmus). Fish DNA was evenly distributed across the whole lake except when the fish population was low. Samples collected from the sediment contained fish DNA more often than water samples in two out of the three small shallow lakes (including Lake Pounui). Sediment geochemistry probably impeded detection in the third lake. Perch sedaDNA was therefore used as an indication of fish presence in Lake Pounui for Chapter 5, which explored multitrophic changes in Lake Pounui over the last c. 1,000 years. In addition to pollen, charcoal, and 14C dating, XRF scanning was used to reconstruct mineralogic shifts from the catchment (Ti/inc, K/inc) and within the lake (inc/coh). Biological trends were reconstructed by targeting the sedaDNA of bacteria (16S rRNA), microeukaryotes (18S rRNA), metazoans (CO1), and macrophytes (rbcL, trnL). Complemented by historical records and studies, the data produced in this thesis indicated that the biggest changes in Lake Pounui happened after European settlement (c. 1845), with land clearance, perch introduction, climate change, and probable fertiliser application driving the degradation of the water quality in c. 180 years. This study revealed shifts in native communities (macrophytes, bacteria, oligochaete worms) and the appearance of new species (perch, macrophytes, freshwater nematodes) previously undocumented using sedaDNA. The results highlight just how complex yet fragile lake ecosystems can be and how little we still know about them. Sedimentary ancient DNA is a useful tool to study the insidious and long-lasting impact of nonnative species on freshwater ecosystems because it widens the range of species that can be studied. However, it needs to be complemented with other proxies. This thesis provides a framework to study fish DNA in small shallow lakes (Chapter 4). It can also inform future management and restoration strategies in lakes, especially in Lake Pounui, by retracing historical water quality (Chapter 2) and identifying taxa present prior to, during, and after lake degradation (Chapter 5)

    Mainstreaming of Nature-Based Solutions for the mitigation of hydro-meteorological hazard: governance analysis of a socio- technical change

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    The Nature-Based Solutions (NBS) concept and approach were developed to simultaneously face challenges such as risk mitigation and biodiversity conservation and restoration. NBSs have been endorsed by major International Organizations such as the EU, the FAO and World Bank that are pushing to enable a mainstreaming process. However, a shift from traditional engineering “grey” solutions to wider and standard adoption of NBS encounters technical, social, cultural, and normative barriers that have been identified with a qualitative content analysis of policy documents, reports and expert interviews. The case of the region Emilia-Romagna was studied by developing an analytical framework that brought together the social-ecological context, the governance system and the characteristics of specific NBSs

    Assessing crop water requirements and irrigation scheduling at different spatial scales in Mediterranean orchards using models, proximal and remotely sensed data

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    Accurate estimations of crop water requirements are necessary to improve water use in agriculture and to optimize the use of available freshwater resource. To this aim, the Agro-Hydrological models represent useful tools to quantify the crop actual evapotranspiration. To define the upper boundary condition of the Agro-Hydrological models it is essential to assess the atmospheric water demand, expressed as crop reference evapotranspiration, ETo. In literature several methods, different in terms of input data requirement and climate variables combinations, have been developed to estimate ETo. Among these methods it is commonly used the well-known FAO56 Penman-Monteith (FAO56-PM) thermodynamic approach. Implementing this method requires access to climate data usually measured by ground weather stations. Unfortunately, these instruments are not always available, in this case recent climate reanalysis databases are useful solution to overcome this limitation. Direct measurements of actual evapotranspiration, ETa, are important to validate the results of the model’s application. These measurements, especially for large scale use, can be time consuming and economically expensive. Moreover, improper installation of the sensors or incorrect calibrations could cause outliers in time series or compromise the continuity of the data time series. Recently Machine Learning (ML) algorithm have been developed to predict and fill the gaps in time series of ETa. The joint use of Agro-Hydrological models with proximity and remotely sensed data is one of the possible ways to accurately estimate crop water requirements. The remote observations of the land surface represent a reliable strategy to identify the spatial distribution of vegetation biophysical parameters, such as, crop coefficient Kc under actual field conditions. The general objective of the research was to assess the crop water requirements in two typical crops (citrus and olive) of the Mediterranean region, using FAO56 Agro-Hydrological model based on functional relationships Kc(VIs) between crop coefficient, Kc, and Vegetation Indices (VIs) calibrate using in situ measurements and VIs obtained by multispectral remotely sensed data. Moreover, it was evaluated the reliability of the reanalysis climate variables provided by ERA5-Land database to assess ETo in Sicily (Italy). The performance of the ERA5-Land reanalysis weather data to estimate ETo, was assessed considering 39 ground weather station distributed in Sicily region. The ETo values estimated on the basis of climate variables from ERA5-L database encourage the use of reanalysis database to assess ETo. In general, the results were in agreement with those obtained from ground measurement, with average Root Mean Square Error (RMSE) equal to 0.73 mm d-1 and corresponding Mean Bias Error (MBE) equal to -0.36 mm d-1. The research activities were carried out in two experimental fields. The first experimental field is a citrus orchard located near the Villabate town whereas the second one was the irrigation district 1/A, managed by “Consorzio di Bonifica della Sicilia” ex “Consorzio di Bonifica Agrigento 3”, Castelvetrano, Sicily (Italy), characterized mainly by olives orchards. The time series of ETa, acquired by the Eddy Covariance (EC) tower installed in the citrus experimental field was processed using the Gaussian Process Regression (GPR) algorithm in order to fill the gaps. The performances were evaluated in terms of Nash Sutcliffe Efficiency (NSE) coefficient and RMSE. The values of NSE ranging between 0.74 and 0.88, whereas the RMSE values lower or equal to 0.55 mm d-1 confirm the suitability of the GPR model, to predict time ETa series. FAO56 Agro-Hydrological model was applied for the irrigation seasons 2018, 2019 and 2020 (Villabate) and for the irrigation seasons 2018 and 2019 (Castelvetrano). For each study areas, using VIs obtained from Sentinel-2 Multi Spectral Images (MSI) level 2A, a Kc(VIs) relationship was developed and then implemented in the model. The model was used to estimates spatial and temporal variability of the actual evapotranspiration, soil water content (SWC), in the root zone, crop coefficient and stress coefficient, as well as, to irrigation scheduling. For the citrus orchard a non-linear Kc(VIs) relationship was identified after assuming that the sum of two VIs, such as Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI), is suitable to represent the spatio-temporal dynamics of the investigated environment. The application of the FAO56 Agro-Hydrological model indicated that the estimated ETa was characterized by RMSE, and MBE, of 0.48 and -0.13 mm d−1 respectively, while the estimated SWC, were characterized by RMSE = 0.01 cm3 cm−3 and the absence of bias, then confirming that the suggested procedure can produce highly accurate results in terms of dynamics of SWC and ETa under the investigated field conditions. In the Castelvetrano irrigation district 1/A, a linear Kc(VI) relationship was identified following the Allen and Pereira (A&P) procedure which was based on the height of the canopy and the fraction of vegetation cover, the last was estimated by the NDVI. The differences between simulated and measured seasonal values was encouraging for the 2018, with value equal to 3%, while for the 2019 it was equal to 17%. These results highlight that the proposed model, with further improvements, and more accurate information such as the effective depth of root zone and the real volumes delivered by the hydrants, can be a useful tool for supporting the decision in the management of the irrigation demands in the irrigation district
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