Post-Disaster Housing Reconstruction in Sri Lanka: What Methodology?

Research methodology is the procedural framework within which the research is conducted. This includes the overall approach to a problem that could be put into practice in a research process, from the theoretical underpinning to the collection and analysis of data. Choice of methodology depends on the primary drivers: topic to be researched and the specific research questions. Hence, methodological perspectives of managing stakeholder expectations of PDHR context are composed of research philosophies, research strategy, research design, and research techniques. This research belonged to social constructivism or interpretivism within a philosophical continuum. The nature of the study was more toward subjectivism where human behavior favored voluntary stance. Ontological, methodological, epistemological, and axiological positioning carried the characteristics of idealism, ideographic, anti-positivism, and value laden, respectively. Data collection comprises two phases, preliminary and secondary. Exploratory interviews with construction experts in the United Kingdom and Sri Lanka were carried out to refine the interview questions and identify the case studies. Case study interviews during the secondary phase took place in Sri Lanka. Data collected at the preliminary stage were used to assess the attributes of power, legitimacy/proximity, and urgency of stakeholders to the project using Stakeholder Circle™ software. Moreover, the data collected at secondary phase via case studies will be analyzed with NVivo 8. This article aims to discuss these methodological underpinnings in detail applied in a post-disaster housing reconstruction context in Sri Lanka

Impact of culture towards disaster risk reduction

Number of natural disasters has risen sharply worldwide making the risk of disasters a global concern. These disasters have created significant losses and damages to humans, economy and society. Despite the losses and damages created by disasters, some individuals and communities do not attached much significance to natural disasters. Risk perception towards a disaster not only depends on the danger it could create but also the behaviour of the communities and individuals that is governed by their culture. Within this context, this study examines the relationship between culture and disaster risk reduction (DRR). A comprehensive literature review is used for the study to evaluate culture, its components and to analyse a series of case studies related to disaster risk. It was evident from the study that in some situations, culture has become a factor for the survival of the communities from disasters where as in some situations culture has acted as a barrier for effective DRR activities. The study suggests community based DRR activities as a mechanism to integrate with culture to effectively manage disaster risk

Climate Change Impacts on Rice Farming Systems in Northwestern Sri Lanka

Sri Lanka has achieved tremendous progress since 1950 in crop production and food availability. Yields grew at an impressive rate until leveling off in the mid-eighties. Sri Lanka's population is anticipated to grow in the coming decades, creating an ever-greater demand for food security on the household, sub-district, regional, and national scales.The agricultural sector in Sri Lanka is vulnerable to climate shocks. An unusual succession of droughts and floods from 2008 to 2014 has led to both booms and busts in agricultural production, which were reflected in food prices. In both instances, the majority of farmers and consumers were adversely affected.At present the rice-farming systems are under stress due to inadequate returns for the farmers and difficulty in coping with shocks due to climate, pests, and diseases, and prices for produce. There are government price-support mechanisms, fertilizer-subsidy schemes, and crop insurance schemes, but the levels of the supports are modest and often do not effectively reach the farmers

Tallo: A global tree allometry and crown architecture database.

This is the final version. Available from Wiley via the DOI in this record. Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.Natural Environment Research Council (NERC)Natural Environment Research Council (NERC); Ministry of Education, Youth and Sports of the Czech RepublicFAPEMIGUniversidad Nacional Autónoma de MéxicoUniversidad Nacional Autónoma de MéxicoConsejo Nacional de Ciencia y TecnologíaSwedish Energy AgencyUKRIFederal Ministry of Education and ResearchNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Science FoundationNational Science FoundationInternational Foundation for ScienceP3FACDynAfForNanjing Forestry UniversityJiangsu Science and Technology Special ProjectHebei UniversityAgence Nationale de la RechercheAgence Nationale de la RechercheAgua Salud ProjectU.S. Department of EnergyCAPE

Tallo: A global tree allometry and crown architecture database

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd

Dynamic Coupling of Near-Field and Far-Field Models

Deepwater spills pose a unique challenge for reliable predictions of oil transport and fate, since live oil spewing under very high hydrostatic pressure has characteristics remarkably distinct from oil spilling in shallow water. It is thus important to describe in detail the complex thermodynamic processes occurring in the near-field, meters above the wellhead, and the hydrodynamic processes in the far-field, up to kilometers away. However, these processes are typically modeled separately since they occur at different scales. Here we directly couple two oil prediction applications developed during the Deepwater Horizon blowout operating at different scales: the near-field Texas A&M Oilspill Calculator (TAMOC) and the far-field oil application of the Connectivity Modeling System (oil-CMS). To achieve this coupling, new oil-CMS modules were developed to read TAMOC output, which consists of the description of distinct oil droplet “types,” each of specific size and pseudo-component mixture that enters at a given mass flow rate, time, and position into the far field. These variables are transformed for use in the individual-based framework of CMS, where each droplet type fits into a droplet size distribution (DSD). Here we used 19 pseudo-components representing a large range of hydrocarbon compounds and their respective thermodynamic properties. Simulation results show that the dispersion pathway of the different droplet types varies significantly. Indeed, some droplet types remain suspended in the subsea over months, while others accumulate in the surface layers. In addition, the decay rate of oil pseudo-components significantly alters the dispersion, denoting the importance of more biodegradation and dissolution studies of chemically and naturally dispersed live oil at high pressure. This new modeling tool shows the potential for improved accuracy in predictions of oil partition in the water column and of advancing impact assessment and response during a deepwater spill