Seeking justice in Green Revolutions: Synergies and trade-offs between large-scale and smallholder agricultural intensification in Rwanda

AbstractThe adaptive potential of pathogens in novel or heterogeneous environments underpins the risk of disease epidemics. Antagonistic pleiotropy or differential resource allocation among life-history traits can constrain pathogen adaptation. However, we lack understanding of how the genetic architecture of individual traits can generate trade-offs. Here, we report a large-scale study based on 145 global strains of the fungal wheat pathogen Zymoseptoria tritici from four continents. We measured 50 life-history traits, including virulence and reproduction on 12 different wheat hosts and growth responses to several abiotic stressors. To elucidate the genetic basis of adaptation, we used genome-wide association mapping coupled with genetic correlation analyses. We show that most traits are governed by polygenic architectures and are highly heritable suggesting that adaptation proceeds mainly through allele frequency shifts at many loci. We identified negative genetic correlations among traits related to host colonization and survival in stressful environments. Such genetic constraints indicate that pleiotropic effects could limit the pathogen’s ability to cause host damage. In contrast, adaptation to abiotic stress factors was likely facilitated by synergistic pleiotropy. Our study illustrates how comprehensive mapping of life-history trait architectures across diverse environments allows to predict evolutionary trajectories of pathogens confronted with environmental perturbations.

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A stochastic approach to analyze trade-offs and risks associated with large-scale water resources systems

Water Resources Research ◽

10.1029/2006wr005094 ◽

2007 ◽

Vol 43 (6) ◽

Cited By ~ 68

Author(s):

A. Tilmant ◽

R. Kelman

Keyword(s):

Water Resources ◽

Large Scale ◽

Stochastic Approach ◽

Water Resources Systems ◽

Trade Offs

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An integrated life cycle and water footprint assessment of nonfood crops based bioenergy production

Scientific Reports ◽

10.1038/s41598-021-83061-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jun Li ◽

Fengyin Xiong ◽

Zhuo Chen

Keyword(s):

Life Cycle ◽

Environmental Sustainability ◽

Large Scale ◽

Water Footprint ◽

Arable Land ◽

Integrated Analysis ◽

Actual Performance ◽

Bioenergy Production ◽

Trade Offs ◽

Hybrid Pennisetum

AbstractBiomass gasification, especially distribution to power generation, is considered as a promising way to tackle global energy and environmental challenges. However, previous researches on integrated analysis of the greenhouse gases (GHG) abatement potentials associated with biomass electrification are sparse and few have taken the freshwater utilization into account within a coherent framework, though both energy and water scarcity are lying in the central concerns in China’s environmental policy. This study employs a Life cycle assessment (LCA) model to analyse the actual performance combined with water footprint (WF) assessment methods. The inextricable trade-offs between three representative energy-producing technologies are explored based on three categories of non-food crops (maize, sorghum and hybrid pennisetum) cultivated in marginal arable land. WF results demonstrate that the Hybrid pennisetum system has the largest impact on the water resources whereas the other two technology options exhibit the characteristics of environmental sustainability. The large variances in contribution ratio between the four sub-processes in terms of total impacts are reflected by the LCA results. The Anaerobic Digestion process is found to be the main contributor whereas the Digestate management process is shown to be able to effectively mitigate the negative environmental impacts with an absolute share. Sensitivity analysis is implemented to detect the impacts of loss ratios variation, as silage mass and methane, on final results. The methane loss has the largest influence on the Hybrid pennisetum system, followed by the Maize system. Above all, the Sorghum system demonstrates the best performance amongst the considered assessment categories. Our study builds a pilot reference for further driving large-scale project of bioenergy production and conversion. The synergy of combined WF-LCA method allows us to conduct a comprehensive assessment and to provide insights into environmental and resource management.

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System design for inferring colony-level pollination activity through miniature bee-mounted sensors

Scientific Reports ◽

10.1038/s41598-021-82537-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Haron M. Abdel-Raziq ◽

Daniel M. Palmer ◽

Phoebe A. Koenig ◽

Alyosha C. Molnar ◽

Kirstin H. Petersen

Keyword(s):

Data Acquisition ◽

Honey Bees ◽

Large Scale ◽

Physical World ◽

Cluttered Environments ◽

Robotic Mapping ◽

Large Scale Data ◽

Trade Offs ◽

Large Numbers ◽

Engineered Systems

AbstractIn digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.

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Exploring trade-offs in frequency allocation in a transit network using bus route patterns: Methodology and application to large-scale urban systems

Transportation Research Part B Methodological ◽

10.1016/j.trb.2015.06.018 ◽

2015 ◽

Vol 81 ◽

pp. 577-595 ◽

Cited By ~ 16

Author(s):

İ. Ömer Verbas ◽

Hani S. Mahmassani

Keyword(s):

Large Scale ◽

Urban Systems ◽

Frequency Allocation ◽

Transit Network ◽

Trade Offs

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The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation

Journal of Artificial Intelligence Research ◽

10.1613/jair.1.12181 ◽

2020 ◽

Vol 69 ◽

pp. 471-500

Author(s):

Shih-Yun Lo ◽

Shiqi Zhang ◽

Peter Stone

Keyword(s):

Mobile Robot ◽

Motion Planning ◽

Mobile Robots ◽

Large Scale ◽

Accurate Estimate ◽

Indoor Environments ◽

Task Planning ◽

Trade Offs ◽

High Level ◽

Task Level

Intelligent mobile robots have recently become able to operate autonomously in large-scale indoor environments for extended periods of time. In this process, mobile robots need the capabilities of both task and motion planning. Task planning in such environments involves sequencing the robot’s high-level goals and subgoals, and typically requires reasoning about the locations of people, rooms, and objects in the environment, and their interactions to achieve a goal. One of the prerequisites for optimal task planning that is often overlooked is having an accurate estimate of the actual distance (or time) a robot needs to navigate from one location to another. State-of-the-art motion planning algorithms, though often computationally complex, are designed exactly for this purpose of finding routes through constrained spaces. In this article, we focus on integrating task and motion planning (TMP) to achieve task-level-optimal planning for robot navigation while maintaining manageable computational efficiency. To this end, we introduce TMP algorithm PETLON (Planning Efficiently for Task-Level-Optimal Navigation), including two configurations with different trade-offs over computational expenses between task and motion planning, for everyday service tasks using a mobile robot. Experiments have been conducted both in simulation and on a mobile robot using object delivery tasks in an indoor office environment. The key observation from the results is that PETLON is more efficient than a baseline approach that pre-computes motion costs of all possible navigation actions, while still producing plans that are optimal at the task level. We provide results with two different task planning paradigms in the implementation of PETLON, and offer TMP practitioners guidelines for the selection of task planners from an engineering perspective.

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Quantifying synergies and trade-offs in the water-land-energy-food-climate nexus using a multi-model scenario approach

10.5194/egusphere-egu2020-15192 ◽

2020 ◽

Author(s):

Jonathan Doelman ◽

Tom Kram ◽

Benjamin Bodirsky ◽

Isabelle Weindle ◽

Elke Stehfest

Keyword(s):

Climate Change ◽

Sustainable Development ◽

Food Security ◽

Food Production ◽

Large Scale ◽

Sustainable Development Goals ◽

Integrated Assessment Model ◽

Assessment Model ◽

Trade Offs ◽

Development Goals

The human population has substantially grown and become wealthier over the last decades. These developments have led to major increases in the use of key natural resources such as food, energy and water causing increased pressure on the environment throughout the world. As these trends are projected to continue into the foreseeable future, a crucial question is how the provision of resources as well as the quality of the environment can be managed sustainably.Environmental quality and resource provision are intricately linked. For example, food production depends on availability of water, land suitable for agriculture, and favourable climatic circumstances. In turn, food production causes climate change due to greenhouse gas emissions, and affects biodiversity through conversion of natural vegetation to agriculture and through the effects of excessive fertilizer and use of pesticides. There are many examples of the complex interlinkages between different production systems and environmental issues. To handle this complexity the nexus concept has been introduced which recognizes that different sectors are inherently interconnected and must be investigated in an integrated, holistic manner.Until now, the nexus literature predominantly exists of local studies or qualitative descriptions. This study present the first qualitative, multi-model nexus study at the global scale, based on scenarios simultaneously developed with the MAgPIE land use model and the IMAGE integrated assessment model. The goal is to quantify synergies and trade-offs between different sectors of the water-land-energy-food-climate nexus in the context of sustainable development goals (SDGs). Each scenario is designed to substantially improve one of the nexus sectors water, land, energy, food or climate. A number of indicators that capture important aspects of both the nexus sectors and related SDGs is selected to assess whether these scenarios provide synergies or trade-offs with other nexus sectors, and to quantify the effects. Additionally a scenario is developed that aims to optimize policy action across nexus sectors providing an example of a holistic approach that achieves multiple sustainable development goals.The results of this study highlight many synergies and trade-offs. For example, an important trade-off exists between climate change policy and food security targets: large-scale implementation of bio-energy and afforestation to achieve stringent climate targets negatively impacts food security. An interesting synergy exists between the food, water and climate sectors: promoting healthy diets reduces water use, improves water quality and increases the uptake of carbon by forests.

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MULTI-CLASS RESOURCE SHARING WITH BATCH ARRIVALS

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964818000323 ◽

2018 ◽

Vol 33 (3) ◽

pp. 348-366

Author(s):

Paul Ezhilchelvan ◽

Isi Mitrani

Keyword(s):

Resource Sharing ◽

Large Scale ◽

Virtual Machines ◽

Cloud Provider ◽

Batch Arrivals ◽

Large Scale Systems ◽

Trade Offs ◽

Resource Requirements ◽

Partial Blocking ◽

Fixed Point Iterations

A cloud provider hosts virtual machines (VMs) of different types, with different resource requirements. There are bounds on the total amounts of each kind of resource that are available. Requests arrive in batches of different sizes. Under the ‘complete blocking’ policy, a request is accepted only if all the VMs in its batch can be accommodated. The ‘partial blocking’ policy would accept a request if there is room for at least one of the VMs in the batch. Blocked requests are lost, with an associated loss of revenue. The trade-offs between costs and benefits are evaluated by means of appropriate models, for which novel solutions based on fixed-point iterations are proposed. The applicability of those solutions is extended, by means of simplifications, to very large-scale systems. Numerical examples and comparisons with simulations are presented.

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Entangled Systems at the Energy-Water-Food Nexus

Reconsidering the Impact of Climate Change on Global Water Supply, Use, and Management - Advances in Environmental Engineering and Green Technologies ◽

10.4018/978-1-5225-1046-8.ch009 ◽

2017 ◽

pp. 144-165

Author(s):

Joseph Nyangon ◽

Nabeel Alabbas ◽

Lawrence Agbemabiese

Keyword(s):

Large Scale ◽

Food Resource ◽

Institutional Processes ◽

Trade Offs ◽

Institutional Structures ◽

Private And Public ◽

Energy Economy ◽

Political Economic ◽

Resource Systems

This chapter assesses energy, water, and food resource systems based on their inter- and intra-sectoral imperatives of large scale development investments at the institutional level (including private and public activities) and how to achieve security of resource supplies. It identifies key interrelated processes, practices, and factors that underpin integrated resource management (IRM) and their attendant benefits. Applying the E4 framework concerned with energy, economy, environment, and equity to identify the main threats to these systems, the chapter evaluates their institutional, political, economic, cultural and behavioral components, and characterizes the forces that drive each of them at different governance scales. The chapter is guided by political economy, economic, and sociological theories that suggest that institutional structures affect economic factors and processes (i.e. production, distribution, and consumption processes). A case study of energy, water, and food (EWF) conflicting sectoral imperatives in Delaware is discussed in detail to better understand how these policy and institutional processes occur, which forms they take, and in which ways they define the quality and quantity of EWF resource systems in the State. In order to verify these parameters, the analysis considered the advantages of a sectorally balanced, E4 framework, in particular to evaluate the valency and magnitude of cross-sectoral connections, balance competing needs, and identify policy options that address various trade-offs.

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