Environmental Studies
The need for a precise forecasting of the impacts of climate change on the future distribution of the Earth's principle biome is increasing. In this paper, forecasting methods covered include: the niche-theory models which categorize species by habitat (particularly environmental conditions where species may persist or perish). The general circulation models and the species-area curve models which consider large groups of species or all species.
The existing climate models based on approximations of increasing carbon dioxide and, to some extent, by lessening sulfate aerosols, forecast that temperatures will rise by 2.5-10.4oF (1.4-5.8oC) between the year1990 and 2100. Greater warming or climate change effect is expected within higher latitudes over the land, whereas sea surface temperature is expected to warm uniformly. Warming is also expected to be more within the winter than within summer, especially at high latitudes. It is expected that large areas are expected will be wetter, while other large regions are expected to be drier (Jarvis 2010). Additionally, storms are probably to be more intense. Between the year 1990 to 2100 is a wide range and it is challenging to forecast carbon dioxide release because many variables are involved. Studies on climate change have indicated that, even without carbon dioxide release variable, world climate will rise by 0.9o F (0.5o C) over the next 100 years as a result of warming caused by the ocean. Moreover, models forecast that sea level will increase by approximately 10 cm over the subsequent century (NRC 2011).
Evidence of climate change or global warming entails decreased snowfall, changes in weather trends, and rising sea levels. Precipitation patterns, precipitation levels, severe weather, and cloud cover are expected to be affected by the rise in GHG concentrations within the atmosphere. The multiple elements of climate modification are anticipated to impact all categories of biodiversity, from an organism to levels of biome (Hansen et al. 2011, p. 481). They mainly concern various forms and strengths of fitness decrease, expressed at different categories, and have an impact on individuals, species, populations, ecosystems, and ecological networks. At the most fundamental level of biodiversity, change in climate may decrease population’s genetic diversity resulting from directional selection as well as rapid migration, for instance, the case of flamingo migration in lake Nakuru in Kenya, that can in turn influence functioning and resilience of ecosystem (Botkin et al. 2007, p. 230).
Various impacts on populations are probably to change the, web of interaction, on the community level (Bengtsson & Hammer 2011). Basically, the response of certain species to change in climate can constitute an indirect effect on the species which depend on them. According to the findings of (Hansen et al. 2011, p. 508) on 9650 interspecific systems, approximately 6300 species may disappear due to the extinction of associated species.
Current Distribution of Biomes over the Surface of the Earth in Response to the Current Climatic Regime
The impacts of low temperature within the Polar areas, and domination of low moisture hinder the plant growth. Within the tropical areas, the occurrence of hot deserts within the subtropical convergence or meeting zone where sinking air currents frontal passage occurs, high precipitation is experienced. High precipitation result into more plant growth. The finer scale complications of the world biome distribution trends or patterns are as a result of regional and local variations in topography, soils, and land use (Hansen et al. 2011, p. 765).
Modeled World Vegetation Biomes
The comparison of modeled world vegetation and the current distribution of biome over the surface of the Earth in response to the current climatic regime, indicates that the model is consistent with the biome distribution trends with reference to low moisture dominance and low temperature within the polar, tropical and temperate regions, and finer-scale distribution patterns of biome resulting from regional and local variations in topography, soils, and land use.
Future World Vegetation Biomes
Because of climate change, great increase within land appropriate for agriculture is expected toward Polar Regions. All circulation models of the air forecast a greater rise in warming within the poles than within the equator. Moreover, a greater warming within the winter than within summer, and more warming during the night than during the daytime is anticipated. Consequently, the predicted climate within high latitudes is anticipated to rise greatly within days with temperatures always above freezing (Jarvis 2010). As measured via satellites, polar growing seasons, currently, have risen from twelve to eighteen days since 1980 (Prost et al. 2010, p. 4). It is also projected that, temperate regions dominated by dry land, particularly thorn shrub vegetation, will reduce as prospective agriculture increases towards low latitude regions. Besides, little space is expected towards higher latitudes as a result of climate change.
The Estimation of Species Loss
Studies indicate that local species loss cover a large range, with certain regions experiencing no losses while others experiencing complete extinction of existing species. High local extinctions may concern relatively large regions, for instance, (Townsend, Begon & Harper 2013) approximated that more than sixteen percent of European landmass may have species losses above 50 percent by 2050. This should be distinguished from predictions of species losses at the world level, which are lower than within the local level, this is because local losses do not necessarily result into global extinctions. Nonetheless, even the world estimates show major losses of biome resulting from climate changes which are higher than the present rates of extinction and much higher than the rates of species losses documented within the fossil record (Botkin et al. 2007, p. 236). For instance, the earliest global studies projected that by 2050, fifteen to thirty seven percent of species are under the threat of extinction or loss with the current climate warming (Prost et al. 2010, p. 4). Birds are estimated to be especially sensitive to changes in climate. Two studies have determined losses by 2050 resulting from climate modification: this range from below 0.3 percent of the globe’s 8750 lands birds are expected to go extinct (Hansen et al. 2011, p. 779) and up to thirty percent of the 8400 species of land bird within the Western Hemisphere may go extinct (Prost et al. 2010, p. 4). Concerning the vulnerability of twenty five main biodiversity hotspots, Jarvis (2010) suggest that the loss of endemic species may reach thirty nine to forty three percent within worst-case situations, representing the possible extinction of 56 000 common plant species and 3700 common vertebrate species (Bengtsson & Hammer 2011).
Studies on changes within species abundance project biodiversity erosion in a similar order of the extent as species extinction model project, that is, extinction of eleven to seventeen percent of mean species abundance at the end of this century (Jarvis 2010). Utilizing data from 799 coral reefs, 6222 amphibians and 9856 birds, the IUCN projected that 35 percent of the globe’s birds, 71 percent of water reef making corals and 52 percent of amphibians are especially vulnerable to climate modification (Townsend, Begon & Harper 2013). Variability within regional extinctions is considerably higher than within global extinction estimations. In some areas, the composition of species will never change at all while in others nearly all species will go extinct due to climate change (Le Houerou 2010).
Theoretical Models for Evaluating the Future World Biodiversity
Many techniques exist to make inferences, beginning with available palaeoclimatic or current data, observations, experiments, and meta-analyses (Adams 2008). Ecological modeling is commonly used method for predictive studies. Progress within this field is coupled with high pace as well as the plurality of techniques or approaches. In specific, three main approaches exist to estimate species loss, focusing on future modifications within species range or changes within species abundance or species extinction.
Biodiversity Range Models
Studies modeling species array or range shifts are mostly based on the hypothesis that species niches is described by climate niche and the species, (environmental variables). This defines the appropriate climatic environment for those specific species. The models relate present species ranges with many climatic variables, hence define the envelope for every species (Townsend, Begon & Harper 2013). Thereafter, it is possible to estimate this envelope for diverse future climate situations to determine the possible redistribution of the appropriate climate space of species. The threat to extinction may then be determined through different ways utilizing species-area relationships (Le Houerou 2010).
Shifts within distinct vegetation groups, often known as biome are frequently simulated with DVM (Dynamic Vegetation Models). Dynamic Vegetation Models apply time series in climate data (for instance precipitation, temperature, sunshine days, humidity) taking into consideration constraints of soil characteristics and topography to simulate daily or monthly dynamics of flora and fauna processes. Species of plants are represented as groups having similar structural and physiological properties, known as Plant Functional Types, which are structured to represent major groups of plants (Townsend, Begon & Harper 2013). Plant Functional Types distribution may then be applied to estimate shifts in biome.
Species Loss Models
The simplest way of determining extinction threat is to presume that species go extinct in situations where no suitable habitat exists (Prost et al. 2010, p. 4). This can underestimate extinction since species always enter the vortex of extinction before the entire habitat is lost. On the other hand, it can significantly overestimate extinction since most species have fragile or weak habitat specificity (Prost et al. 2010, p. 4).
The SAR (species-area relationship), an empirical correlation between the land area and the number of species, is always applied to estimate extinction threat (Bengtsson & Hammer 2011). Extinction of species are worked out like a direct function of climate-induced contraction range or habitat loss based on the examination that extinction risk rises with declining range and size of the population. Species-area relationship can under or over-estimate species extinction threat based on the species capacity to persist within small population or acclimatize to new environments. Moreover, it fails to offer time frame within which extinctions are probably to happen (Jarvis 2010).
Within (DRR) dose-response relationship models, experiments and observation data may be applied to produce empirical relationships between significance of world drivers (dose) and changes within species loss (response).
Most models concentrate on species loss, which is the last stage of decrease within abundance and is less immediate effect of climate change. Effects on biodiversity are projected by use of biodiversity indicators such as mean species abundance (MSA) (Botkin et al. 2007, p. 227) as well as Biodiversity Intactness Index (BII) (Jarvis 2010). For instance, the GLOBIO model applies a matrix of alterations within mean regional species abundances due to conversion between two land cover categories or land use, resulting from empirical studies (Adams 2008). These categories of models apply species abundances within pristine ecosystems like a baseline, thus offer a measure of the distance derived from animal communities and naturalness of plants following man disturbances. Moreover, species abundance models on the basis of plant characteristics and abiotic traits may offer evidence of changes within ecosystem services (Jarvis 2010).
There are many drawbacks to these models, particularly regarding the indicators of biodiversity developed from the dose-response relationship applied to species numbers or abundance. They depend extensively on the quality or value of the entered data, uncertainty cannot be considered, and they are challenging to link to commonly applied biodiversity indices (Bengtsson & Hammer 2011).
Model Combinations
Current modeling methods normally incorporate a series of one or many future socio-economic situations, one or many extinction drivers, species loss models or one biodiversity range. Projections are then expressed in terms of many extinction metrics. This produces a range of model combinations resulting to a broad range of estimations which are difficult to compare, this is because the underlying presumptions vary greatly. Despite significant differences and biases, these models normally show that various species are expected to decline fast at an international scale (Townsend, Begon & Harper 2013).
Reference List
NRC 2011, “Climate Stabilization Targets: Emissions, Concentrations, and Impacts over Decades to Millennia”, National Research Council, The National Academies Press, Washington, DC, USA.
Adams, J 2008, “Vegetation-climate interaction: How vegetation makes the global environment” Berlin: Springer.
Bengtsson, L, & Hammer, C 2011, “Geosphere-biosphere interactions and climate”, Cambridge: Cambridge University Press.
Jarvis, P 2010, “Ecological principles and environmental issues”, Harlow, England: Prentice Hall.
Prost, S, Smirnov, N, Fedorov, B, Sommer, S, Stiller, M., Nagel, D, G et al. 2010, Influence of Climate Warming on Arctic Mammals? New Insights from Ancient DNA Studies of the Collared Lemming Dicrostonyx torquatus. PLOS One, vol. 3, no. 1, pp. 4.
Townsend, C, Begon, M, & Harper, J 2013, “Essentials of ecology”, Malden, MA: Blackwell Pub.
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