###### Abstract  
The growth and geographical distribution of species are influenced by both abiotic and biotic factors. Abiotic factors for plants, also known as physical and chemical factors, are light, climate and geology [1; 2]. Biotic factors are the effects of living organisms on the environment, such as the competition for resources and space, or natural enemies [3]. It is clear that no single factor affects the survival, development and fitness of plants, but that there is an optimum for each factor where plants grow best [4]. An increased distance from the optimum leads to greater stress, until the limit of tolerance is reached and death occurs. As there is no single optimum, but rather a number of different optima for different factors such as temperature, light, moisture, nutrients, _etc._, and as they are all available to different extents, there is always at least one factor that limits the growth; the one that is least available. This is in essence \"the law of limiting factors\", first presented by [PERSON] in 1840 to explain the influence of chemical nutrients on plant growth. This approach can also be used to explain the existence of different ecosystems in different regions due to different climates [2]. The concept that the distribution of a species in any given region depends on the ecological niches available was introduced by [PERSON], 1986, who designed ecograms for the tree species of Europe according to environmental factors [5; 6]. The distribution of a species can be defined by abiotic factors, such as climate and substrate [7; 8; 9; 10], and these factors were also used in models for the potential distribution of species. These models can be designed by a mechanistic or empirical approach as envelope models, climate response surfaces, homoclines, ecological niche models or species distribution models. Mechanistic models use critical climatic values for the physiological tolerance of different species to explain the range of distribution of the species. This means that a model for the distribution of a species is based on the critical physiological values measured in laboratory tests. In empirical models, climatic conditions are measured in the field together with the probability of occurrence of different species. These models result in a distribution pattern of the species and make it possible to predict the distribution under diverse climate scenarios. In contrast to mechanistic models, empirical models also show the biotic influences on the species [11]. An example of a mechanistic model for Northern Europe was STASH, which simulated the biogeographical distribution of individual species on a regional scale for the specific case of lodgepole pine (_Pinus contorta_ Dougl.) in Scandinavia using scenarios from the Hamburg ECHAM3 climate model [12]. This bioclimatic model for the potential distributions of tree species in northern Europe was first published in 1996 [13]. Bioclimatic models on a global scale were used for modeling the carbon cycle. Models estimating the global net primary production (NPP, the difference between the CO\({}_{2}\) fixed in plant biomass and the CO\({}_{2}\) lost to the atmosphere) in units of bound carbon per unit area per annum are, for example, the Miami model [14], the Schuur model [15] and the National Center for Ecological Analysis and Synthesis (NCEAS) model [16]. The difference between these models is that the Schuur model was based on an extended data-set available for tropical regions, which allowed a better estimation undertropical climatic conditions than the Miami model [15]. For the NCEAS model, datasets were available from the Ecosystem Model Data Intercomparison (EMDI) project, for both grass-dominated and tree-dominated landscapes. Thus it was possible to calculate correlations for both grass- and tree-dominated sites. Furthermore, besides the NPP, the above-ground NPP (ANPP) was estimated [16,17].