An assessment of the economic impact of climate change on the water sector in the Turks and Caicos Islands

The best description of water resources for Grand Turk was offered by Pérez Monteagudo (2000) who suggested that rain water was insufficient to ensure a regular water supply although water catchment was being practised and water catchment possibilities had been analysed. Limestone islands, mostly flat and low lying, have few possibilities for large scale surface storage, and groundwater lenses exist in very delicate equilibrium with saline seawater, and are highly likely to collapse due to sea level rise, improper extraction, drought, tidal waves or other extreme event. A study on the impact of climate change on water resources in the Turks and Caicos Islands is a challenging task, due to the fact that the territory of the Islands covers different environmental resources and conditions, and accurate data are lacking. The present report is based on collected data wherever possible, including grey data from several sources such as the Intergovernmental Panel on Climate Change (IPCC) and Cuban meteorological service data sets. Other data were also used, including the author’s own estimates and modelling results. Although challenging, this was perhaps the best approach towards analysing the situation. Furthermore, IPCC A2 and B2 scenarios were used in the present study in an effort to reduce uncertainty. The main conclusion from the scenario approach is that the trend observed in precipitation during the period 1961 - 1990 is decreasing. Similar behaviour was observed in the Caribbean region. This trend is associated with meteorological causes, particularly with the influence of the North Atlantic Anticyclone. The annual decrease in precipitation is estimated to be between 30-40% with uncertain impacts on marine resources. After an assessment of fresh water resources in Turks and Caicos Islands, the next step was to estimate residential water demand based on a high fertility rate scenario for the Islands (one selected from four scenarios and compared to countries having similar characteristics). The selected scenario presents higher projections on consumption growth, enabling better preparation for growing water demand. Water demand by tourists (stopover and excursionists, mainly cruise passengers) was also obtained, based on international daily consumption estimates. Tourism demand forecasts for Turks and Caicos Islands encompass the forty years between 2011 and 2050 and were obtained by means of an Artificial Neural Networks approach. for the A2 and B2 scenarios, resulting in the relation BAU>B2>A2 in terms of tourist arrivals and water demand levels from tourism. Adaptation options and policies were analysed. Resolving the issue of the best technology to be used for Turks and Caicos Islands is not directly related to climate change. Total estimated water storage capacity is about 1, 270, 800 m3/ year with 80% capacity load for three plants. However, almost 11 desalination plants have been detected on Turks and Caicos Islands. Without more data, it is not possible to estimate long term investment to match possible water demand and more complex adaptation options. One climate change adaptation option would be the construction of elevated (30 metres or higher) storm resistant water reservoirs. The unit cost of the storage capacity is the sum of capital costs and operational and maintenance costs. Electricity costs to pump water are optional as water should, and could, be stored for several months. The costs arising for water storage are in the range of US$ 0.22 cents/m3 without electricity costs. Pérez Monteagudo (2000) estimated water prices at around US$ 2.64/m3 in stand points, US$ 7.92 /m3 for government offices, and US$ 13.2 /m3for cistern truck vehicles. These data need to be updated. As Turks and Caicos Islands continues to depend on tourism and Reverse Osmosis (RO) for obtaining fresh water, an unavoidable condition to maintaining and increasing gross domestic product(GDP) and population welfare, dependence on fossil fuels and vulnerability to increasingly volatile prices will constitute an important restriction. In this sense, mitigation supposes a synergy with adaptation. Energy demand and emissions of carbon dioxide (CO2) were also estimated using an emissions factor of 2. 6 tCO2/ tonne of oil equivalent (toe). Assuming a population of 33,000 inhabitants, primary energy demand was estimated for Turks and Caicos Islands at 110,000 toe with electricity demand of around 110 GWh. The business as usual (BAU), as well as the mitigation scenarios were estimated. The BAU scenario suggests that energy use should be supported by imported fossil fuels with important improvements in energy efficiency. The mitigation scenario explores the use of photovoltaic and concentrating solar power, and wind energy. As this is a preliminary study, the local potential and locations need to be identified to provide more relevant estimates. Macroeconomic assumptions are the same for both scenarios. By 2050, Turks and Caicos Islands could demand 60 m toe less than for the BAU scenario.

An assessment of the economic impact of climate change on the coastal and human settlements Sector in Barbados

This study assesses the potential economic impact of climate change on coastal human settlements in the Caribbean, with specific reference to Barbados, and evaluates the costs and benefits of undertaking various adaptation strategies. The aim is to assist Caribbean territories in developing the strategies and capacity needed to deal with the potential impact of severe weather events that are anticipated to occur with increased frequency and intensity as a result of climate change. Some of the key anticipated manifestations of climate change for the Caribbean include elevated air and sea-surface temperatures, sea-level rise, possible changes in extreme events and a reduction in freshwater resources.This research focuses on how human settlements distributed along the coast of Guyana, especially those in low elevation coastal zones (LECZ)are affected by these impacts. Focusing on three potential transmission sources - sea-level rise, stronger storm hazards and increased precipitation – the study considers the vulnerability of populations in the LECZ areas and estimates the overall threat posed by climate change to coastal populations and infrastructure. Vulnerability to climate change (measured as exposed assets) was estimated for four emission scenarios as outlined by the Special Report on Emissions Scenarios (SRES), namely the A1, A2, B1 and B2 scenarios for the period 2010 to 2100 and as detailed by the Intergovernmental Panel on Climate Change (IPCC), using global circulation models (GCM) and storm surge hazard maps.

A study of climate change in the Caribbean: impacts of climate change in small communitites

ECLAC, Subregional Headquarters for the Caribbean

Climate change in Central América: Potential impacts and public policy options

Since 2008 we have supported the collaborative initiative "Economics of Climate Change in Central America" aimed at demonstrating the impacts of climate variability and change and fostering a discussion on public policies in key sectors. The initiative has been led by the Ministries of Environment and Treasury or Finance of Central America, with the support of their ministerial councils, CCAD, COSEFIN, and Economic Integration Secretariat, SIECA. The Ministries of Agriculture and of Health, with their councils, CAC and COMISCA, have also joined the effort; and the Dominican Republic came on board in 2015.

Wolf presence in the ranch of origin: Impacts on temperament and physiological responses of beef cattle following a simulated wolf encounter

This experiment evaluated temperament, vaginal temperature, and plasma cortisol in beef cows from wolf-naive and wolf-experienced origins that were subjected to a simulated wolf encounter. Multiparous, pregnant, nonlactating Angus-crossbreed cows from the Eastern Oregon Agricultural Research Center located near Burns, OR (CON; n = 50), and from a commercial operation near Council, ID (WLF; n = 50), were used. To date, grey wolves are not present around Burns, OR, and thus CON were naive to wolves. Conversely, wolves are present around Council, ID, and WLF cows were selected from a herd that had experienced multiple confirmed wolf-predation episodes from 2008 to 2012. Following a 50-d commingling and adaptation period, CON and WLF cows were ranked by temperament, BW, and BCS and allocated to 5 groups (d 0; 10 CON and 10 WLF cows/group). Groups were individually subjected to the experimental procedures on d 2 (n = 3) and d 3 (n = 2). Before the simulated wolf encounter, cow temperament was assessed and blood samples and vaginal temperatures (using intravaginal data loggers) were collected (presimulation assessments). Cows were then sorted by origin, moved to 2 adjacent drylot pens (10 WLF and 10 CON cows/pen), and subjected to a simulated wolf encounter event for 20 min, which consisted of 1) cotton plugs saturated with wolf urine attached to the drylot fence, 2) continuous reproduction of wolf howls, and 3) 3 leashed dogs that were walked along the fence perimeter. Thereafter, WLF and CON cows were commingled and returned to the handling facility for postsimulation assessments, which were conducted immediately after exposure to wolf-urine-saturated cotton plugs, wolf howl reproduction, and 20-s exposure to the 3 dogs while being restrained in a squeeze chute. Chute score, temperament score, and plasma cortisol concentration increased (P <= 0.01) from pre- to postsimulation assessment in WLF but did not change in CON cows (P >= 0.19). Exit velocity decreased (P = 0.01) from pre-to postsimulation assessment in CON but did not change (P = 0.79) in WLF cows. In addition, WLF cows had a greater (P = 0.03) increase in temperature from pre-to postsimulation assessments compared with CON cows. In conclusion, the simulated wolf encounter increased excitability and fear-related physiological stress responses in cows that originated from a wolf-experienced herd but not in cows that originated from a wolf-naive herd.