Climate2016, 4(2), 26; doi:10.3390/cli4020026 (registering DOI) - published 4 May 2016 Show/Hide Abstract
Abstract: Climate change adds an additional layer of complexity that needs to be considered in business strategy. For firms in the food industry, many of the important climate impacts are not directly related to food processing so a value chain approach to adaptation is recommended. However, there is a general lack of operational tools to support this. In this study, carbon and water footprints were conducted at a low-precision screening level in three case studies in Australia: Smith’s potato chips, OneHarvest Calypso™ mango and selected Treasury Wine Estates products. The approach was cost-effective when compared to high-definition studies intended to support environmental labels and declarations, yet provided useful identification of physical, financial, regulatory and reputational hotspots related to climate change. A combination of diagnostic footprinting, downscaled climate projection and semi-quantitative value chain analysis is proposed as a practical and relevant toolkit to inform climate adaptation strategies.
Climate2016, 4(2), 25; doi:10.3390/cli4020025 - published 28 April 2016 Show/Hide Abstract
Abstract: Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961–1990 and 2011–2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, and—if needed—to adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.
Climate2016, 4(2), 24; doi:10.3390/cli4020024 - published 19 April 2016 Show/Hide Abstract
Abstract: Climate influences geographic differences of vegetation phenology through both contemporary and historical variability. The latter effect is embodied in vegetation heterogeneity underlain by spatially varied genotype and species compositions tied to climatic adaptation. Such long-term climatic effects are difficult to map and therefore often neglected in evaluating spatially explicit phenological responses to climate change. In this study we demonstrate a way to indirectly infer the portion of land surface phenology variation that is potentially contributed by underlying genotypic differences across space. The method undertaken normalized remotely sensed vegetation start-of-season (or greenup onset) with a cloned plants-based phenological model. As the geography of phenological model prediction (first leaf) represents the instantaneous effect of contemporary climate, the normalized land surface phenology potentially reveals vegetation heterogeneity that is related to climatic adaptation. The study was done at the continental scale for the conterminous U.S., with a focus on the eastern humid temperate domain. Our findings suggest that, in an analogous scenario, if a uniform contemporary climate existed everywhere, spring vegetation greenup would occur earlier in the north than in the south. This is in accordance with known species-level clinal variations—for many temperate plant species, populations adapted to colder climates require less thermal forcing to initiate growth than those in warmer climates. This study, for the first time, shows that such geographic adaption relationships are supported at the ecosystem level. Mapping large-scale vegetation climate adaptation patterns contributes to our ability to better track geographically varied phenological responses to climate change.
Climate2016, 4(2), 23; doi:10.3390/cli4020023 - published 18 April 2016 Show/Hide Abstract
Abstract: Climate change and Land-Use Land-Cover change (LULC) has significantly displaced the local rainfall patterns and weather conditions in Pakistan. This has resulted in a different climate-related problem, particularly vector borne diseases. Dengue transmission has emerged as one of the most devastating and life threatening disease in Pakistan, causing hundreds of deaths since its first outbreak. This study is designed to understand and analyze the disease patterns across two distinct study regions, using Geographic Information System (GIS), Satellite Remote Sensing (RS) along with climate and socio-economic and demographics datasets. The datasets have been analyzed by using GIS statistical analysis techniques. As a result, maps, tables and graphs have been plotted to estimate the most significant parameters. These parameters have been assigned a contribution weight value to prepare a model and Threat Index Map (TIM) for the study areas. Finally, the model has been tested and verified against existing datasets for both study areas. This model can be used as a disease Early Warning System (EWS).
Climate2016, 4(2), 22; doi:10.3390/cli4020022 - published 12 April 2016 Show/Hide Abstract
Abstract: The study examined the spatiotemporal distribution of drought in the Maasai rangelands of Kenya. The implications of this distribution, in concert with the documented existing and/or projected social and biophysical factors, on critical rangeland resources in Maasai-pastoralism are discussed using an integrated approach. Participatory interviews with the Maasai, retrieval from archives, and acquisition from instrument measurements provided data for the study. Empirical evidence of the current study reveals that drought occurrences in this rangeland have been recurrent, widespread, cyclic, sometimes temporally clustered, and have manifested with varying intensities across spatial, temporal, and, occasionally, social scales; and they have more intensity in lower than higher agroecological areas. An estimated 86% of drought occurrences in this rangeland, over the last three decades alone, were of major drought category. The 2000s, with four major drought events including two extreme droughts, are an important drought period. A strong consensus exists among the Maasai regarding observed drought events. In Maasai-pastoralism, the phenomenon called drought, pastoralist drought, is simultaneously multivariate and multiscalar: its perception comprises the simultaneous manifestation of cross-scale meteorological, socioeconomic, and environmental factors and processes, and their various combinations. The inherent simultaneous multivariate and scalar nature of the pastoralist drought distinguishes it from the conventional drought types, particularly the meteorological drought that predominantly guides drought and resource management in the rangelands of Kenya. In Maasai-pastoralism, the scarcely used (33%) meteorological drought is construed as rainfall delay/failure across spatial and/or temporal scale, and never its reduced amount. Collectively, the current findings reveal that knowledge about drought affects the way the manifestation of this climatic hazard is perceived, communicated, and characterized; hence, ceteris paribus, alongside its spatiotemporal distribution, shapes the nature of the adaptive capacity of and resource management in Maasai-pastoralism. Studies that anticipate enhancing the drought-adaptive capacity of the Maasai should account for cross-scale social and biophysical factors, their processes, and interactions; they must engage the affected inhabitants, and utilize and integrate multiple data sources and approaches. These necessities become more crucial for informing adaptation under the present spatiotemporal distribution of drought as well as in relation to the projected increase in occurrence and intensity of this climatic hazard as the climate continues to change, and as pressures from socioeconomic globalization persistently proliferate into the Maasai’s social and biophysical landscapes.
Climate2016, 4(2), 21; doi:10.3390/cli4020021 - published 11 April 2016 Show/Hide Abstract
Abstract: Bangladesh has been experiencing increased temperature and change in precipitation regime, which might adversely affect the important ecosystems in the country differentially. The river flows and groundwater recharge over space and time are determined by changes in temperature, evaporation and crucially precipitation. These again have a spatio-temporal dimension. This geospatial modeling research aimed at investigating spatial patterns and changing trends of temperature and rainfall within the geographical boundary of Bangladesh. This would facilitate better understanding the change pattern and their probable impacts on the ecosystem. The southeastern region, which is one of the most important forest ecosystem zones in the country, is experiencing early onset and withdrawal of rain but increasing trends in total rainfall except in the Monsoon season. This means that the region is experiencing a lower number of rainy days. However, total rainfall has not changed significantly. The differential between maximum and minimum showed an increasing trend. This changing pattern in average max and min temperature along with precipitation might cause a situation in which the species that are growing now may shift to suitable habitats elsewhere in the future. Consequently, the biodiversity, watersheds and fisheries, productivity of land, agriculture and food security in the region will be affected by these observed changes in climate.