of the vegetation. To consider supplementary parameters, hydrological processbased models support understanding of the behaviour of hydrologic systems as a
response to climate change. Such models include evapotranspiration, surface runoff, subsurface and interflow, and river channel flow. For HABIT-CHANGE the
hydro-ecological model SWIM (Krysanova et al. 2000; Hattermann et al. 2008) was
applied. SWIM is a hydrological model at the scale of a catchment area (for details
refer to Chap. 3). It integrates relevant hydrological processes to investigate the
impacts of climate changes, such as water percolation, groundwater recharge, plant
water uptake, soil evaporation, and river routing. SWIM allows the development of
scenarios, for example, with a focus on the habitat type, and it provides information
relevant to vegetation dynamics, i.e. the available soil water (Holsten et al. 2009).
However, model results rely strongly on the quality and the resolution of the input
data (like observed runoff, soil and land use data) for the specific investigation area.
5.2.3 Modelling Distribution and Occurrence
of Plants and Animals
While the projection of potential impacts of climate change on water resources is
very helpful and can be linked to specific management options, many protected
areas aim to conserve specific plants or animals. Most modelling work to assess the
potential impact of climate change on biodiversity relies on habitat modelling of
plants and animals, and provides risk assessments for specific species or habitats
(Normand et al. 2007; Hickler et al. 2012). Most of these approaches use statistical
approaches, such as Bioclimatic Envelopes (BEM), and do not consider functional
relationships, as, for example, with dynamic vegetation models (DVMs). Although
DVMs are able to analyse changing patterns of competition their disadvantage is
that they are resolved either at the basis of plant functional types or selected (tree)
species (Ku ¨hn et al. 2009; Bellard et al. 2012). An additional uncertainty arises
from other model shortcomings, e.g. the adaptive capacity of single species or
species associations possibly being underestimated (Thuiller et al. 2008; Fordham
et al. 2012).
When focusing on nature conservation issues the impact of climate change alone
would not be so extensive if habitat destruction and fragmentation were not so
widely advanced permitting species to adapt their distribution area (Opdam and
Wascher 2004). The inclusion of land use parameters improves model results
significantly.
So far, the major outputs of modelling the impacts on plants and animals (fungi
are not yet a focus) are limited to projected changes in probabilities of occurrence.
Furthermore, plants, animals, and fungi represent only a specific hierarchy or scale
of biodiversity and nature conservation goals. Climate change affects biodiversity
on different scales from changing mutation rates of genes and phenology to energy
fluxes and ecosystem services (Vohland 2008; Bellard et al. 2012).
5 Climate Change Impact Modelling Cascade – Benefits and Limitations. . .
69
response to climate change. Such models include evapotranspiration, surface runoff, subsurface and interflow, and river channel flow. For HABIT-CHANGE the
hydro-ecological model SWIM (Krysanova et al. 2000; Hattermann et al. 2008) was
applied. SWIM is a hydrological model at the scale of a catchment area (for details
refer to Chap. 3). It integrates relevant hydrological processes to investigate the
impacts of climate changes, such as water percolation, groundwater recharge, plant
water uptake, soil evaporation, and river routing. SWIM allows the development of
scenarios, for example, with a focus on the habitat type, and it provides information
relevant to vegetation dynamics, i.e. the available soil water (Holsten et al. 2009).
However, model results rely strongly on the quality and the resolution of the input
data (like observed runoff, soil and land use data) for the specific investigation area.
5.2.3 Modelling Distribution and Occurrence
of Plants and Animals
While the projection of potential impacts of climate change on water resources is
very helpful and can be linked to specific management options, many protected
areas aim to conserve specific plants or animals. Most modelling work to assess the
potential impact of climate change on biodiversity relies on habitat modelling of
plants and animals, and provides risk assessments for specific species or habitats
(Normand et al. 2007; Hickler et al. 2012). Most of these approaches use statistical
approaches, such as Bioclimatic Envelopes (BEM), and do not consider functional
relationships, as, for example, with dynamic vegetation models (DVMs). Although
DVMs are able to analyse changing patterns of competition their disadvantage is
that they are resolved either at the basis of plant functional types or selected (tree)
species (Ku ¨hn et al. 2009; Bellard et al. 2012). An additional uncertainty arises
from other model shortcomings, e.g. the adaptive capacity of single species or
species associations possibly being underestimated (Thuiller et al. 2008; Fordham
et al. 2012).
When focusing on nature conservation issues the impact of climate change alone
would not be so extensive if habitat destruction and fragmentation were not so
widely advanced permitting species to adapt their distribution area (Opdam and
Wascher 2004). The inclusion of land use parameters improves model results
significantly.
So far, the major outputs of modelling the impacts on plants and animals (fungi
are not yet a focus) are limited to projected changes in probabilities of occurrence.
Furthermore, plants, animals, and fungi represent only a specific hierarchy or scale
of biodiversity and nature conservation goals. Climate change affects biodiversity
on different scales from changing mutation rates of genes and phenology to energy
fluxes and ecosystem services (Vohland 2008; Bellard et al. 2012).
5 Climate Change Impact Modelling Cascade – Benefits and Limitations. . .
69