Next Article in Journal
Acute Oak Decline and Agrilus biguttatus: The Co-Occurrence of Stem Bleeding and D-Shaped Emergence Holes in Great Britain
Next Article in Special Issue
Drought Stress Reaction of Growth and Δ13C in Tree Rings of European Beech and Norway Spruce in Monospecific Versus Mixed Stands Along a Precipitation Gradient
Previous Article in Journal
Genetic Diversity of Walnut (Juglans Regia L.) in the Eastern Italian Alps
Previous Article in Special Issue
Economic Feasibility of Managing Loblolly Pine Forests for Water Production under Climate Change in the Southeastern United States
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 8
Issue 3
10.3390/f8030082
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests

by
Ivo Machar
1,*,
Veronika Vlckova
2,
Antonin Bucek
3,
Vit Vozenilek
4,
Lubomir Salek
5 and
Lucie Jerabkova
6
1
Department of Development Studies, Faculty of Science, Palacky University, 17 listopadu 12, 771 46 Olomouc, Czech Republic
2
Department of Transport Telematics, Faculty of Transportation Sciences, Czech Technical University, Konviktska 20, 110 00 Prague, Czech Republic
3
Department of Forest Botany, Faculty of Forestry and Wood Technology, Mendel University, Geobiocoenology and Dendrobiology, Zemedelska 3, 613 00 Brno, Czech Republic
4
Department of Geoinformatics, Faculty of Science, Palacky University, 17 listopadu 12, 771 46 Olomouc, Czech Republic
5
Department of Forest Management, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Kamycka 129, 165 00 Prague, Czech Republic
6
Department of Geography, King’s College London, King’s Building, Strand London, London WC2R 2LS, UK
*
Author to whom correspondence should be addressed.
Forests 2017, 8(3), 82; https://doi.org/10.3390/f8030082
Submission received: 10 January 2017 / Revised: 13 March 2017 / Accepted: 14 March 2017 / Published: 16 March 2017
(This article belongs to the Special Issue Impacts of Climate Change—Selected Papers from FowiTa German Forest Sciences Conference (Sessions 1–5))
Browse Figures
Versions Notes

Abstract

:
The regional effects of climate change on forest ecosystems in the temperate climate zone of Europe can be modelled as shifts of forest vegetation zones in the landscape, northward and to higher elevations. This study applies a biogeographical model of climate conditions in the forest vegetation zones of the Central European landscape, in order to predict the impact of future climate change on the most widespread tree species in European deciduous forests—the European beech (Fagus sylvatica L.). The biogeographical model is supported by a suite of software applications in the GIS environment. The model outputs are defined as a set of conditions - climate scenario A1B by the Special Report on Emission Scenarios (SRES) for a forecast period, for a specified geographical area and with ecological conditions appropriate for the European beech, which provide regional scenarios for predicted future climatic conditions in the context of the European beech’s environmental requirements. These predicted changes can be graphically visualized. The results of the model scenarios for regional climate change show that in the Czech Republic from 2070 onwards, optimal growing conditions for the European beech will only exist in some parts of those areas where it currently occurs naturally. Based on these results, it is highly recommended that the national strategy for sustainable forest management in the Czech Republic be partly re-evaluated. Thus, the presented biogeographical model of climate conditions in forest vegetation zones can be applied, not only to generate regional scenarios of climate change in the landscape, but also as a support tool for the development of a sustainable forest management strategy.

1. Introduction

Increasingly, severe and more frequent drought events are expected to become a major risk for forest ecosystems under predicted climate change [1]. The changes in climate conditions are expected to result in changes in the forest structure [2]. We know that the current form of forest management in Central Europe, with its preference for conifer monocultures, will not be sustainable in the future [3,4]. A substantial increase in air temperature, along with a simultaneous reduction in precipitation during the growing season in Central and Southern Europe, will increase the likelihood of long and intensive summer droughts, which may have severe effects on vegetation in natural and managed ecosystems [5]. Timber production from these ecosystems also needs to be maintained because timber is a renewable material and, as such, it represents an environmentally viable material option. In the face of change and uncertainty [6], a forester needs to know the types of forests that will be most suitable under future climatic conditions. However, forests develop slowly, and during periods of rapid climate change they are likely to be in disequilibrium with the environment, leading to changed competition and possibly mortality [7]. Conversions to more drought-adapted forest types have been recommended in order to prevent climate change-induced forest dieback, and this should be the aim of any adaptive management, especially in areas where monocultures of drought-sensitive Norway spruce (Picea abies L. Karst) were promoted in the past. Although a complete forest conversion takes up to 120 years [8], a gradual process of introducing drought-tolerant species into drought-sensitive conifer monocultures provides immediate benefits, with the short-term enhancement of biodiversity, and the maintenance of timber production. This process includes planning for future long-term conditions.
The European beech (Fagus sylvatica L.) is the dominant tree species of the potential natural vegetation, from planar to montane vegetation zones in temperate Central Europe [9], and it has a key role in the European forest transition and adaptation strategies [10]. In the future, the European beech may occupy a larger area of the lower uplands and mountains, while its area in the lowlands and lower uplands may be restricted due to higher competitive pressure from the oak [11]. European beech distribution has been at equilibrium with the climate on its north-eastern leading edge, but not on its north-western leading edge [12]. The annual gross primary production of European beech is primarily affected by spring temperatures and, more irregularly, by summer water stress [13]. Based on climate change scenarios, by 2100, we can expect an expansion of climatically suitable habitats for the European beech towards northeastern Europe and higher elevations, especially in the Alps and the Pyrenees. At the same time, a sharp decline in suitable areas for the European beech in Western Europe can be expected [14]. The changing climate may also affect the European beech’s life history. In the next few decades, the European beech’s maximum lifespan could be shortened at higher elevations in Central Europe because of its faster growth, and in the Mediterranean mountains (e.g., Apennines) due to drought-induced mortality [15]. Several studies of European beech forests point to particular sensitivities to meteorological summer drought conditions [16,17,18,19,20], indicating that the growing season’s precipitation totals, which are often used to characterize the local growing conditions of stands of trees, are only subordinate determinants to above-ground productivity in European beech forests. Sensitivity to drought can also be reduced with an appropriate thinning strategy [21]. However, some studies show that European beech dominated forests are not severely prone to negative functional climate change effects and, therefore, their key functions, such as welfare and recreation, can be maintained [22].
In lowland areas, the European beech is often associated with the oak (Quercus sp.). Each of these species have different ecological requirements and the dominance of the European beech has begun to decline in locations where the mean annual temperature exceeds 11.2 °C and the annual precipitation drops below 510 mm [23]. It is predicted that in Serbia (the European beech’s most southeastern occurrence in Europe), by the end of the 21st century, approximately 90% of the current European beech forests will be outside their 20th century bioclimatic niche, and approximately 50% of European beech forests will be in a bioclimatic niche where mass European beech mortality has been recorded [24].
Although the European beech shows sensitivity to drought in forests where it is mixed with the Norway spruce, it can mitigate this limitation, as became evident during the extremely dry years of 1976 and 2003 in Central Europe [25,26]. The European beech trees near their distribution limit have already adapted to extreme conditions, while we have to expect changes in the growth patterns of the beech under mesic conditions [27]. In addition, according to [28], the sensitivity of the European beech to environmental constraints depends on neighborhood identity. Therefore, a systematic formation of mixed stands tends to be an appropriate sylvicultural measure in order to mitigate the effects of global warming and droughts on European beech growth patterns. However, management practices in the area of nature conservation strategies have not been substantially affected by scientific recommendations for forest management, and de [29] cites that ‘Pure’ science cannot solve the big uncertainties that surround climate change.
In forest ecosystems, the effects of climate change on a regional scale are most evident in the shift of forest vegetation zonation to higher elevations [30,31]. Nevertheless, disturbances, interspecific competition, different phenotype plasticity and various adaptations of dominant species to a particular ecosystem can all introduce considerable uncertainties into regional models of shifts in forest vegetation zones [32]. The growth response to climate change is manifest in long-term horizons [33], and the best recent records are probably in the shifts of the tree line in European mountains [34], although one of the most important drivers for upper tree line shift in the past was the management of alpine areas (e.g., grazing).
An understanding of the ongoing and potential shifts in vegetation zones is important for the development of strategies of sustainable forest management in the context of climate change [35]. The forest vegetation zones represent the regional fundamental frames of climatic conditions for the growth of forest tree species in commercial forests [36], which dominate in the European temperate zone. However, previously published studies of vegetation zone shifts are limited to a few countries dominated by Alpine regions [37,38,39]. Aside from the Alpine region, Svajda et al. [40] studied the altitudinal shift of the Dwarf mountain’s pine vegetation at the upper forest limit in the High Tatras (Slovakia)and Kutnar et al. [41] published predictions concerning the changes in the vegetation zones under climate changes in Slovenia. Predictions concerning the influence of the shift of the vegetation zones on tree species in Poland were elaborated on by [42], and the impact of terrain and vegetation structure on the tree line dynamic in the Sudeten region in central Europe was studied by [43].
Regional studies conducted in several countries, with the aim of predicting which forests would be more suitable for future conditions, have come up with similar recommendations concerning reductions in spruce monocultures, and giving preference to mixed forests with a higher proportion of deciduous tree species, particularly the European beech [44,45,46].
Our study aims to apply the forest vegetation zonation for modelling to future changes in climate conditions for the European beech, which is currently one of the most important deciduous tree species in European forests [47] (EUFORGEN 2011). The main aim of this article is to show how predicted changes in climate conditions in forest vegetation zones, as related to regional climate scenarios, can influence the European beech’s growth in the Central European landscape. Modelling climate condition changes in relation to the European beech can provide support for the development of strategies of adaptation measures in forest stands dominated by the species. They also provide a science-based rationale for forest management decisions [48] based on the adaptation approach to forest ecosystems [49]. Forest management adaptation strategies [50] aimed at sustainability must take into account a range of economic [51] and social aspects [52,53,54]. There are many uncertainties concerning the impact of climate change on European forests [6], so another goal of this study is to highlight the importance of the somewhat neglected biogeographical models, rooted in the concept of the forest vegetation zones. This article presents the results of the biogeographical model applications for the European beech in the cultural landscape of the Czech Republic for the forecast period 2030–2090.

2. Materials and Methods

This biogeographical model of climate conditions in the forest vegetation zones of the Czech Republic (hereinafter, model) is based on the relationship between the present climate and the distribution of vegetation zones in the landscape [55]. The model (Figure 1) is based on fundamental assumptions: (i) that the general ecological relationship between climate conditions and vegetation zonation will be maintained in the future [56,57]; (ii) that predicted climate change will be manifested into modified climate conditions in the present vegetation zones at the regional level; and (iii) that this process can be predicted [58]. It does not imply that the present vegetation zones within the cultural landscape will shift to higher elevations. The model outlines projections of changes in climate conditions to vegetation zonation, not changes in the vegetation zones as such. This fact is an important basic principle of the model. The model uses the forest vegetation zones as a reference framework for climate predictions of particular growing conditions for the European beech, for which the optimal climate conditions in the Czech Republic are unambiguously defined [59]. The current representation of the European beech in the forests of the Czech Republic is only 7.7%, which is considerably less than the expected representation (40.2%) in the potential natural vegetation [60].
The forest vegetation zones of the Czech Republic (Table 1) were defined using the method of bio-indication in the fundamental study by [61], and are widely applied in forest management practice. The detailed characteristics of the natural conditions of forest ecosystems in the forest vegetation zones of the Czech Republic [62] can easily be converted to the European forest, agricultural and protection typology systems related to habitats (e.g., in the NATURA 2000 European Network). Detailed climate characteristics of the vegetation zones are based on Macků [63].
A predictive climate database from the Czech Hydrometeorological Institute (CHMI), known as CLIMDATA, is the source of climate data for the model. It assigns the climate data to the set of 131 points regularly distributed throughout the Czech Republic in the form of the regular trapezia network. It contains a large validated database of climate parameters calculated by the model ALADIN-CLIMATE.CZ for the period 2010–2100 [64], for the scenario SRES A1B [65].
The Register of Biogeography [66] is an ecological database which includes geographical and site information, and it is the source of biogeographical data used in the model. It contains the detailed ecosystem characteristics of the Czech Republic’s landscape (i.e., vegetation zonation, soil types and soil conditions the so-called trophic and hydric series, the predominant type of topography) matched with individual cadaster areas. The Czech Republic consists of 13,000 cadasters (polygons with an average area of 6 km2). The register was created as a component of the Area Integral Information System (AIIS) [67]. The cadaster was selected as a basic spatial unit for the Register because it enables the evaluation of changes in the landscape, and utilizes periodically updated databases from the AIIS which characterize the current state of, and anthropogenic pressure on, the landscape. Census data and the utilization of soil resources are of particular interest, and they both use the cadaster as a basic unit. Cadasters are historic landscape units, originally established to document land tenure and estates, and as such they are not homogeneous in their natural conditions. Nevertheless, on the regional scale (all of the Czech Republic), the cadaster polygons capture the heterogeneity of the natural conditions in the whole country, because the original cadaster system, in existence without many changes since the 18th century, used natural boundaries such as streams, forest edges, and major geomorphological formations in the landscape to delineate its units [68].
The biogeographical model of changes to climatic conditions in the vegetation zones is a suite of specific software applications (FORTRAN programming language, IBM, New York, NY, USA) and a GIS application of Esri products (ArcGIS, Prague, Czech Republic). This is a static model that does not enable prediction of the rate of vegetation change. Climate characteristics were assigned to the points of the Register of Biogeography using an analytical-geometric method, which involved the construction of a network of points with a fine resolution of 250 m. The climatic data from these new points were calculated with a gradient method [69] and taken from the climatic variable of their four closest neighbors in the original climatic database CLIDATA. The predicted climate characteristics of defining points, their corresponding potential vegetation zone and the characteristics of natural climate conditions are expressed in the model algorithms. The algorithms were developed using the method of spatio-temporal analogies, with Lang’s Rainfall Factor used as the relationship coefficient (combining total annual precipitation and average annual temperature in one value) [70]. The climate growing conditions for the European beech in the Czech Republic were divided into four categories: “unsuitable climate conditions”, “moderately suitable climate conditions”, “suitable climate conditions”, and “optimal climate conditions” (related to climate conditions for different vegetation zones). These divisions in predicted climate conditions enable a clear visualization of the model outputs. The model outputs for the defined scenario combinations (time period, climate scenario, geographic area, ecological conditions for the European beech) provided a regional scenario of predicted future climate conditions for the European beech in the forecast period 2030–2090.

3. Results

3.1. Regional Scenario of Changes in Climate Conditions of Vegetation Zonation in the Czech Republic

The regional scenario of the changes in climate conditions for vegetation zonation in the Czech Republic for the forecast period 2030–2090 (regional scenario) clearly identifies three main predicted trends (Table 1): (i) a gradual increase in area for regions with climate conditions of the lower forest vegetation zones (1–3); (ii) a relatively stable area with climate conditions of the fourth forest vegetation zone, which remains the vegetation zone with the largest representation (55%) on the landscape in the Czech Republic, in both predicted periods; and (iii) a significant and very fast decrease in area for regions with climate conditions of the higher forest vegetation zones (5–8).

3.2. Application of the Regional Scenario for Sustainable Management of Beech-Dominated Forests

Good and optimal growing conditions for the European beech currently prevail in two thirds of the Czech Republic (Table 2), and cover an area from the second to the sixth forest vegetation zones (Figure 2).
The visualization of the regional scenario for the year 2030 (Figure 3) shows a decrease in areas with optimal climate conditions for the European beech in the lower uplands and, instead, a slight enlargement of the area with mediocre climate conditions in this terrain. In the prediction period for 2050, the trend is reversed (Figure 4) and the area with the optimal climate conditions for the growth of European beech is 10% larger than today, according to the regional scenario (Table 2). However, the regional scenario predicts a relatively dramatic deterioration in the growing conditions for the European beech between the years 2070 and 2090. In 2070, in connection with an elevational shift of climate conditions in the forest vegetation zones to higher elevations (Figure S1), the optimal climate for the growth of the European beech will move to the highest mountain areas of the Czech Republic (higher than 1000 m above sea level) and a good climate for growing the European beech will remain in and above the area of the present fifth forest vegetation zone. The proportion of the good and excellent climate conditions will decrease to less than 10% of the whole area of the Czech Republic (Table 2). This trend will remain the same for the year 2090. The predicted trend in the changes in climatic growing conditions for the European beech in the Czech Republic forecasts a significant deterioration of its silviculture in the future. Following the regional scenarios, a strategy of sustainable forest management in the Czech Republic should take into consideration potential future threats likely to affect the European beech, which is now the major economic deciduous tree species in the forest sector in the Czech Republic. The predicted shift in the good and optimal climatic growing conditions for the European beech to the highest mountain areas in the Czech Republic will most likely affect the biodiversity associated with the present vegetation belts. In particular cadasters, according to the regional scenario, from 2070 onwards, the good and optimal climatic growing conditions for European beech dominated forests will only be found in parts of the areas currently occupied by natural European beech, from the fifth to the eighth forest vegetation zones (Figure 5 and Figure 6). Based on the regional scenario results, the national strategy of sustainable forest management in the Czech Republic (National Forest Program) should pay more attention to plans for alternative tree species composition in future planning, with regard to the predicted deterioration of climatic growing conditions for the European beech from the year 2070 (Table 2, Figure 5 and Figure 6).

4. Discussion

Global Climate Envelope Models [71], also referred to as Ecological Niche Models or Species Distribution Models, are statistical predictive tools applied in ecological research to estimate the distribution of species, biological communities and habitats [72], and may not always correspond to specific local conditions [73]. This applies to the European beech, which grows in central Europe under fairly specific climate conditions [74], with a natural elevational distribution from 350 m to 990 m.a.s.l. [75], tested the influence of climate and tree-specific traits on inter and intra-site variability in the drought responses of three common European temperate forest tree species in southern Germany and Alpine Austria: Norway spruce, Silver fir and European beech. General patterns of tolerance indicated the high vulnerability of the Norway spruce in comparison to the Silver fir and the European beech, and the strong influence of bioclimatic conditions on the drought responses of all three species. Consequently, drought events led to heterogeneous and variable response patterns in forests stands. These findings support the idea of deliberately using spontaneous selection and adaptation effects as a passive strategy in forest management under climate change conditions. This supports the importance of natural reserves; areas left to natural development without human intervention, where selection processes can take place. Such areas should be an integral part of a broad set of adaptation measures in temperate forests in Europe [76].
The results of the regional modelling of the impact of climate change on European Beech in the Czech Republic are consistent with the main phenomena related to vegetation changes induced by climate change in European beech-dominated forests. These include movement of montane forests dominated by deciduous trees towards a higher elevation, shift of montane beech-fir communities to beech communities and replacement of beech-dominated forests in highland areas by oak-hornbeam forests (especially in the northern Alps) [31]. The results of the biogeography model used in this article suggest that the strategy of sustainable forest management in the lower forest vegetation zones (1st–3rd) of the Czech Republic should focus on adjusting the tree species' composition in commercial forests (plantations) in favour of native broadleaved species, which may be less profitable but more ecologically suitable in these vegetation zones. The area of the fourth vegetation zone (with optimal climate conditions for the growth of the European beech) will continue to dominate the landscape of the Czech Republic in the context of the predicted climate changes. In forest management, the scenario indicates a stable area with optimal climate conditions for European beech (Fagus sylvatica L.). Sustainable forest management strategies in the fourth vegetation zone should thus favour such forest systems, which support beech as the dominant tree species. This can be done using the shelter wood system, and with the support of the European beech’s natural regeneration, etc. The commercial beech forests located in the fourth vegetation zone, in the northern area of the Bílé Karpaty Mountains in the eastern part of the Czech Republic, are where the European beech currently has its Central European ecological optimum [21]. The conditions suitable for the oak-coniferous variety of the fourth vegetation zone will disappear from the landscape, according to the scenario for 2050 (Figure 4). In comparison to the climate of the zonal variety in the fourth vegetation zone (beech zone), the climate of the oak-coniferous variety is characterized by higher continentality, frequent temperature inversions, late frosts and cooler soil profiles during the growing season which are caused by a higher water content in the soil. Ecosystems associated with these specific climate conditions, possessing the characteristics of the so-called central European taiga [77], will be adversely affected by future climate change, according to the model scenario for 2050 (Figure 3). The area with the conditions of the fifth vegetation zone (fir-beech) will decrease by 14% compared to its present state (Figure 2, Figure 3, Figure 4, Figure 5 and Figure 6). Overall, the shift in the climate conditions of vegetation zones toward higher altitudes will affect forest management strategies in the mountainous areas of the Czech Republic. The scenario for 2070 and 2090 indicate changes towards less favourable climate conditions for European beech, which can enhance a risk of biotic and abiotic disturbances and stressors. Strategies for sustainable forest management should aim to enhance the static stability of the present forest stands and, most importantly, convert the current spruce monoculture stands to mixed forests of European beech and Silver fir (Abies alba Mill), where a minor proportion of Norway spruce occur in moist and wet habitats (on pseudogleyed soils).
Projected changes in climate conditions for beech planting linked with forest vegetation zones, correspond to the expected trends in vegetation development in Europe concerning climate changes in the model of European vegetation EUROMOVE [78]. The main trends in the changes are also in line with observed trends in the distribution of wild animals, also explained by climate change, such as certain butterfly species [79] expanding their range to higher elevations. Reference [80] showed that the trend in ongoing changes in bird population sizes and the shifts in nesting areas in the Czech Republic, in the context of climate change, are caused by a decline in species adapted to colder climates in mountainous areas, and an increase in the ranges of lower-elevation species. This confirms the regional scenario of climate characteristics for the beech planting in our study.
Increasing average global temperatures and changes in precipitation over the last 100 years have induced movements in the vegetation zonation of ecosystems around the entire world [81]. The modelling of global vegetation changes using the General Circulation Model [82] clearly shows the effect of global changes on the distribution of vegetation formations. However, assessments of climate parameters vary among global climate models, mainly for the most recent decades [83]. Moreover, global vegetation models cannot take into consideration individual plant species, and the theoretical bases for those models neglect the migration characteristics of individual species and the succession processes occurring at the level of particular ecosystems [84]. The regional scale appears to be the most appropriate for addressing the influences of climate change, species distribution and the succession processes at the level of the ecosystem [85]. In addition, climate change in a particular geographical region often affects certain ecosystems in synergy with other regional influences, such as with landscape fragmentation [86]. Therefore, regional models may provide a fundamental understanding of the significance of climate change for specific target ecosystems [87].
The Fifth Assessment Report for the Intergovernmental Panel on Climate Change (IPCC) defined a set of four new scenarios, known as Representative Concentration Pathways (RCP). Predictive regional climate data for these scenarios are not yet available for the Czech Republic. Therefore, in our model, we had to apply the scenario SRES A1B, based on a validated regional climate database. One of the most important current research projects modelling regional climate change and its effect on organisms is the CORDEX project [88], with its Europe-specific section EURO-CORDEX [89]. The outputs of the regional modelling CORDEX, suitable for regional adaptation studies, should be available in the 500 × 500 m grid in the future.
The modelling of the spatial aspects of occurrence and its development, and the implications for vegetation zonation generate material for further research activities. Refs. [90,91] assessed the impact of elevation and terrain on various species of alpine herbaceous assemblages in the area of Picos de Europa in Spain by modelling on a 15 × 15 m grid. Elevation has the biggest effect on the overall floristic diversity of the community, supporting the close association between elevational climate and vegetation belts. However, the occurrence of individual species was influenced more strongly by slope aspect, topographic index, soil water content and the sun’s radiation. The existing models for the future distribution of flora and fauna mostly concentrate on individual target species or groups of species, whereas organisms interact in the ecosystem processes within their ecological niches, and thus the responses of biota to climate change are more likely to be identified at the level of ecosystem diversity [92]. The biogeographical regional models are particularly useful from this point of view [93].
The biogeographical model of changes in climatic conditions for the European beech, as caused by the predicted climate change, is one of a group of process-based biogeographical models used to predict the equilibrium reactions of vegetation to potential climate change on the regional scale [94]. This model type identifies the ecological limitations in the distribution of vegetation formations’ (vegetation zones) different equilibrium climate conditions [95]. The majority of proposed models are correlational models based on the mutual dependence among certain environmental bioclimatic variables (average temperature and total precipitation) and the present area of species distribution, or characteristics of species ecological niches [96]. When predictions based on climate scenarios show how the climate can change in the future, the corresponding biological species or their communities with zonal distribution are assigned to the new parameters, whereas, in our study, the vegetation zones were assigned as the new parameters. The biogeographical model used in our study utilizes the dependence of the vegetation belts on the long-term impacts of elevation and aspects characterized by average and extreme temperatures, and their dependence on the amount and distribution of precipitation [97]. The specifications for the present forest vegetation zones in the Czech Republic [98] were updated to a higher precision during the establishment of forest habitat typology [62], which laid the groundwork for silviculture based on ecological conditions [99].
The simulations of vegetation redistribution using biogeographical models are essentially static (equilibrium) views of the analyzed problem, as those models represent modelling based on a certain concentration of atmospheric carbon dioxide in the future. The static models provide a useful “picture” of the terrestrial ecosystems in equilibrium with particular climate conditions at a given time [100]. However, the application of these models is limited by the fact that the models do not simulate all known internal factors of vegetation dynamics, such as interspecies competition, natality and mortality of populations or physiological factors. Dynamic global vegetation models that integrate vegetation dynamics and ecosystem functions have been developed to overcome these limitations [101], but they cannot be used on a regional scale [102]. Some uncertainties in the prediction models arising from insufficient data on the autecology of a particular species can be partly eliminated by using species-specific models. However, these are few and far between and mostly applicable on a continental scale [103], only providing rough guidelines for regional applications. In addition, when interpreting mathematical models of the impact of climate change on biota, we must take into consideration that models do not provide a perfect prognosis of future development [104]. The models based on sophisticated analyses contribute significantly to the prognosis (by providing synthetic scenarios), but their sensitive application must be based on a good knowledge of the biology and ecology of the organisms being modelled [105].
The important benefit of biogeographical models is their potential application for strategies of adaptation and mitigation in the landscape in the context of ecosystem services [106]. The vegetation belts are also important with respect to ecological growing conditions for forest tree species (the European beech currently has optimal growing conditions in the Czech Republic, in the fourth vegetation belt). The first study, which analyzed the continual fluctuations in agro-climatic conditions over the last 200 years, as well as expected shifts in future decades [107], showed an expansion of warmer and drier agro-climatic conditions in the most fertile regions. The development of the climate in Europe can lead to the largest shift in agro-climatic conditions since the onset of agricultural activity long before our historical experience [108]. The same consideration is undoubtedly also valid in forestry [109,110]. Therefore, in forestry, the predictions concerning climate conditions and the analyses of their impact on the forest ecosystem must be considered as crucial initial inputs into the formation of strategies in sustainable forest management [111,112]. In relation to the strategies for the lower uplands and mountain forest vegetation zones in the European temperate zone [113], the European beech has been very intensively researched [114,115,116]. The high stability of old-growth European beech forests under natural conditions can contribute to the overall stability of managed forests in Central Europe [117].

5. Conclusions

In conclusion, based on the results of the regional models, we recommend that focus is placed on the sustainable forest management strategy of the Czech Republic, and on developing target tree species whose compositions take into consideration the climatic deterioration of growing conditions for the European beech from the year 2070 onwards.

Acknowledgments

The authors thank the anonymous reviewers for their comments and recommendations. The authors also thank the Czech Hydrometeorological Institute for climate input data to model. This study was supported by the grant “Cultural Landscape of Olomouc Archdiocese—Research, Presentation and Management” DG16P02B014 in the frame of the NAKI II research program funded by the Czech Republic.

Author Contributions

Ivo Machar and Antonin Bucek conceived and designed the model; Antonin Bucek contributed to the dendrobiology aspects; Veronika Vlckova, Vit Vozenilek and Lucie Jerabkova analyzed the data by GIS; Lubomir Salek contributed to forest management implications; and Ivo Machar wrote the paper.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kolström, M.; Lindner, M.; Vilén, T.; Maroschek, M.; Seidl, R.; Lexer, M.J.; Netherer, S.; Kremer, A.; Delzon, S.; Barbati, A.; et al. Reviewing the Science and Implementation of Climate Change Adaptation Measures in European Forestry. Forests 2011, 2, 961–982. [Google Scholar] [CrossRef] [Green Version]
  2. Nabuurs, G.J.; Pussinen, A.; van Bruselen, J.; Schelhaas, M.J. Future harvesting pressure on European forests. Eur. J. For. Res. 2007, 126, 391–400. [Google Scholar] [CrossRef]
  3. Strengbom, J.; Dahlberg, A.; Larsson, A.; Lindelöw, A.; Sandström, J.; Widenfalk, O.; Gustafsson, L. Introducing Intensively Managed Spruce Plantations in Swedish Forest Landscapes will Impair Biodiversity Decline. Forests 2011, 2, 610–630. [Google Scholar] [CrossRef]
  4. Seidl, R.; Rammer, W.; Lexer, M.J. Climate change vulnerability of sustainable forest management in the Eastern Alps. Clim. Chang. 2011, 106, 225–254. [Google Scholar] [CrossRef]
  5. European Environmental Agency (EEA). Impacts of Europe’s Changing Climate; EEA Report No. 2; European Environmental Agency: Copenhagen, Denmark, 2004. [Google Scholar]
  6. Lindner, M.; Fitzgerald, J.B.; Zimmermann, N.E.; Reyer, C.; Delzon, S.; van der Maaten, E.; Schelhaas, M.J.; Lasch, P.; Eggers, J.; van der Maaten-Theunissen, M.; et al. Climate change and European forests: What do we know, what are the uncertainties, and what are the implications for forest management? J. Environ. Manag. 2014, 146, 69–83. [Google Scholar] [CrossRef] [PubMed]
  7. Niinemets, Ü. Responses of forest trees to single and multiple environmental stresses from seedlings to mature plants: Past stress history, stress interactions, tolerance and acclimation. For. Ecol. Manag. 2010, 260, 1623–1639. [Google Scholar] [CrossRef]
  8. Temperli, C.; Bugman, H.; Elkin, C. Adaptive management for competing forest goods and services under climate change. Ecol. Appl. 2012, 22, 2065–2077. [Google Scholar] [CrossRef] [PubMed]
  9. Bohn, U.; Neuhäusl, R.; Gollub, G.; Hettwer, C.; Neuhäuslová, Z.; Schlüter, H.; Weber, H. Map of the Natural Vegetation of Europe. Scale 1:2500000; Landwirtschaftsverlag: Münster, Germany, 2002. [Google Scholar]
  10. Tarp, P.; Helles, F.; Holten-Andersen, P.; Larsen, J.B.; Strange, N. Modelling near-natural silvicultural regimes for beech—An economic sensitivity analysis. For. Ecol. Manag. 2000, 130, 187–198. [Google Scholar] [CrossRef]
  11. Silva, D.E.; Rezende Mazzella, P.; Legay, M.; Corcket, E.; Dupouey, J.L. Does natural regeneration determine the limit of European beech distribution under climatic stress? For. Ecol. Manag. 2012, 266, 263–272. [Google Scholar] [CrossRef]
  12. Saltré, F.; Duputié, A.; Gaucherel, C.; Chuine, I. How climate, migration ability and habitat fragmentation affect the projected future distribution of European beech. Glob. Chang. Biol. 2015, 21, 897–910. [Google Scholar] [CrossRef] [PubMed]
  13. Chiesi, M.; Chirici, G.; Marchetti, M.; Hasenauer, H.; Moreno, A.; Knohl, A.; Matteucci, G.; Pilegaard, K.; Granier, A.; Longdoz, B.; et al. Testing the applicability of BIOME-BGC to simulate beech gross primary production in Europe using a new continental weather dataset. Ann. For. Sci. 2016, 73, 713–727. [Google Scholar] [CrossRef]
  14. Saltré, F.; Saint-Amant, R.; Gritti, E.S.; Brewer, S.; Gaucherel, C.; Davis, B.A.S.; Chuine, I. Climate or migration: What limited European beech post-glacial colonization? Glob. Ecol. Biogeogr. 2013, 22, 1217–1227. [Google Scholar] [CrossRef]
  15. Di Filippo, A.; Biondi, F.; Maugeri, M.; Schirone, B.; Piovesan, G. Bioclimate and growth history affect beech lifespan in the Italian Alps and Apennines. Glob. Chang. Biol. 2012, 18, 960–972. [Google Scholar] [CrossRef]
  16. Seidling, W.; Ziche, D.; Beck, W. Climate responses and interrelations of stem increment and crown transparency in Norway spruce, Scots pine, and common beech. For. Ecol. Manag. 2012, 284, 196–204. [Google Scholar] [CrossRef]
  17. Van der Maaten, E. Climate sensitivity of radial growth in European beech (Fagus sylvatica L.) at different aspects in southwestern Germany. Trees 2012, 26, 777–788. [Google Scholar] [CrossRef] [Green Version]
  18. Gessler, A.; Keitel, C.; Kreuzwieser, J.; Matyssek, R.; Seiler, W.; Rennenberg, H. Potential risks for European beech (Fagus sylvatica L.) in a changing climate. Trees 2007, 21, 1–11. [Google Scholar] [CrossRef]
  19. Latte, N.; Lebourgeois, F.; Claessens, H. Increased tree-growth synchronization of beech (Fagus sylvatica L.) in response to climate change in northwestern Europe. Dendrochronologia 2015, 33, 69–77. [Google Scholar] [CrossRef]
  20. Müller-Haubold, H.; Hertel, D.; Seidel, D.; Knutzen, F.; Leuschner, C. Climate Responses of Aboveground Productivity and Allocation in Fagus sylvatica: A Transect Study in Mature Forests. Ecosystems 2013, 16, 1498–1516. [Google Scholar] [CrossRef]
  21. Bosela, M.; Štefančík, I.; Petráš, R.; Vacek, S. The effects of climate warming on the growth of European beech forests depend critically on thinning strategy and site productivity. Agric. For. Meteorol. 2016, 222, 21–31. [Google Scholar] [CrossRef]
  22. Pötzelsberger, E.; Wolfslehner, B.; Hasenauer, H. Climate change impacts on key forest functions of the Vienna Woods. Eur. J. For. Res. 2015, 134, 481–496. [Google Scholar] [CrossRef]
  23. Mette, T.; Dolos, K.; Meinardus, C.; Braüning, A.; Reineking, B.; Blaschke, M.; Pretzsch, H.; Beierkuhnlein, C.; Gohlke, A.; Wellstein, C. Climatic turning point for beech and oak under climate change in Central Europe. Ecosphere 2013, 4, 1–19. [Google Scholar] [CrossRef]
  24. Stojanovič, D.B.; Kržič, A.; Matovič, B.; Orlovič, S.; Duputie, A.; Djurdjevič, V.; Galič, Z.; Stojnič, S. Prediction of the European beech (Fagus sylvatica L.) xeric limit using a regional climate model: An example from southeast Europe. Agric. For. Meteorol. 2013, 176, 94–103. [Google Scholar] [CrossRef]
  25. Pretzsch, H.; Dieler, J.; Seifert, T.; Rötzer, T. Climate effects on productivity and resource use efficiency of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica (L.)) in stands with different spatial mixing patterns. Trees 2012, 26, 1343–1360. [Google Scholar] [CrossRef]
  26. Pretzsch, H.; Schütze, G.; Uhl, E. Resistance of European tree species to drought stress in mixed versus pure forests: Evidence of stress release by inter-specific facilitation. Plant Biol. 2013, 15, 483–495. [Google Scholar] [CrossRef] [PubMed]
  27. Weber, P.; Bugmann, H.; Pluess, A.R.; Walthert, L.; Rigling, A. Drought response and changing mean sensitivity of European beech close to the dry distribution limit. Trees 2013, 27, 171–181. [Google Scholar] [CrossRef]
  28. Metz, J.; Annighöfer, P.; Schall, P.; Zimmermann, J.; Kahl, T.; Schultze, E.-D.; Ammer, C. Site-adapted admixed tree species reduce drought susceptibility of mature European beech. Glob. Chang. Biol. 2016, 22, 903–920. [Google Scholar] [CrossRef] [PubMed]
  29. De Koning, J.; Turnhout, E.; Winkel, G.; Blondet, M.; Borras, L.; Ferranti, F.; Geitzenauer, M.; Sotirov, M.; Jump, A. Managing climate change in conservation practice: An exploration of the science–management interface in beech forest management. Biodivers. Conserv. 2014, 23, 3657–3671. [Google Scholar] [CrossRef] [PubMed]
  30. Bertrand, R.; Lenoir, J.; Piedallu, C.; Riofrío-Dillon, G.; de Ruffray, P.; Vidal, C.; Pierrat, J.C.; Gegout, J.C. Changes in plant community composition lag behind climate warming in lowland forests. Nature 2011, 479, 517–520. [Google Scholar] [CrossRef] [PubMed]
  31. Garamvoelgyi, A.; Hufnagel, L. Impacts of climate change on vegetation distribution No. 1. Climate change induced vegetation shifts in the Palearctic region. Appl. Ecol. Environ. Res. 2013, 11, 79–122. [Google Scholar] [CrossRef]
  32. Iverson, L.R.; Mckenzie, D. Tree-species range shifts in a changing climate: Detecting, modelling, assisting. Landsc. Ecol. 2013, 28, 879–889. [Google Scholar] [CrossRef]
  33. Büntgen, U.; Frank, D.C.; Kaczka, R.J.; Verstege, A.; Zwijacz-Kozica, T.; Esper, J. Growth responses to climate in a multi-species tree-ring network in the Western Carpathian Tatra Mountains. Tree Physiol. 2007, 27, 689–702. [Google Scholar] [CrossRef] [PubMed]
  34. Vanoni, M.; Bugmann, H.; Nötzli, M.; Bigler, C. Quantifying the effects of drought on abrupt growth decreases of major tree species in Switzerland. Ecol. Evol. 2016, 6, 3555–3570. [Google Scholar] [CrossRef]
  35. Kulhavý, J. A new concept in sustainable forest management—The need for forest ecosystem and landscape research. J. For. Sci. 2004, 50, 520–525. [Google Scholar]
  36. Svobodová, J.; Voženílek, V. Relief for Models of Natural Phenomena. In Landscape Modelling: Geographical Space, Transformation and Future Scenarios (Urban and Landscape Perspectives); Anděl, J., Bičík, I., Dostál, P., Shasneshin, S., Eds.; Springer: Dordrecht, The Netherlands, 2009; Volume 8, pp. 183–196. [Google Scholar]
  37. Elkin, C.; Gutiérrez, A.G.; Leuzinger, S.; Manusch, C.; Temperli, C.; Rasche, L.; Bugmann, H. A 2 °C warmer world is not safe for ecosystem services in the European Alps. Glob. Chang. Biol. 2013, 19, 1827–1840. [Google Scholar] [CrossRef] [PubMed]
  38. Egli, H.R. Landscape change in the Bavarian Alpine Region and political approaches to management. Erde 2010, 141, 383–384. [Google Scholar]
  39. Rosbakh, S.; Bernhardt-Römermann, M.; Poschlod, P. Elevation matters: Contrasting effects of climate change on the vegetation development at different elevations in the Bavarian Alps. Alp Bot. 2014, 124, 143–154. [Google Scholar] [CrossRef]
  40. Švajda, J.; Solar, J.; Janiga, M.; Buliak, M. Dwarf Pine (Pinus mugo) and selected abiotic habitat conditions in the Western Tatra Mountains. Mt. Res. Dev. 2011, 31, 220–228. [Google Scholar] [CrossRef]
  41. Kutnar, L.; Kobler, A. Prediction of forest vegetation shift due to different climate-change scenarios in Slovenia. Sumar. List 2011, 135, 113–126. [Google Scholar]
  42. Zajaczkowski, J.; Brzeziecki, B.; Perzanowski, K.; Kozak, I. Impact of potential climate changes on competitive ability of main forest species in Poland. Sylwan 2013, 157, 253–261. (In Polish) [Google Scholar]
  43. Treml, V.; Chuman, T. Ecotonal Dynamics of the Altitudinal Forest Limit are Affected by Terrain and Vegetation Structure Variables: An Example from the Sudetes Mountains in Central Europe. Arct. Antarct. Alp. Res. 2015, 47, 133–146. [Google Scholar] [CrossRef]
  44. Griess, V.C.; Acevedo, R.; Härtl, F.; Staupendahl, K.; Knoke, T. Does mixing tree species enhance stand resistance against natural hazards? A case study for spruce. For. Ecol. Manag. 2012, 267, 284–296. [Google Scholar] [CrossRef]
  45. Lasch-Born, P.; Suckow, F.; Gutsch, M.; Reyer, C.; Hauf, Y.; Murawski, A.; Pilz, T. Forests under climate change: Potential risks and Opportunities. Meteorol. Z. 2015, 24, 157–172. [Google Scholar]
  46. Matthies, B.D.; Valsta, L.T. Optimal forest species mixture with carbon storage and albedo effect for climate change mitigation. Ecol. Econ. 2016, 123, 95–105. [Google Scholar] [CrossRef]
  47. EUFORGEN 2011. European Forest Genetic Resources Programme. Distribution Maps. Available online: http://www.euforgen.org/distribution-maps (accessed on 6 August 2016).
  48. Parviainen, J.; Frank, G. Protected forests in Europe approaches-harmonizing the definitions for international comparison and forest policy making. J. Environ. Manag. 2003, 67, 27–36. [Google Scholar] [CrossRef]
  49. Idle, E.T.; Bines, T.J.H. Management Planning for Protected Areas. A Guide for Practitioners and Their Bosses; Eurosite, England Nature: Peterborough, UK, 2005; pp. 86–144. [Google Scholar]
  50. Reyer, C.; Bugmann, H.; Nabuurs, G.J.; Hanewinkel, M. Models for adaptive forest management. Reg. Environ. Chang. 2015, 15, 1483–1487. [Google Scholar] [CrossRef]
  51. Hanewinkel, M.; Hummel, S.; Cullmann, D. Modelling and economic evaluation of forest biome shifts under climate change in southwest Germany. For. Ecol. Manag. 2010, 259, 710–719. [Google Scholar] [CrossRef]
  52. Keskitalo, E.C.H. How can forest management adapt to climate change? Possibilities in different forestry systems. Forests 2011, 2, 415–430. [Google Scholar] [CrossRef]
  53. Klenk, N.L.; Adams, B.W.; Bull, G.Q.; Innes, J.L.; Cohen, S.J.; Larson, B.C. Climate change adaptation and sustainable forest management: A proposed reflexive research agenda. For. Chron. 2011, 87, 351–357. [Google Scholar] [CrossRef]
  54. Mermet, L.; Farcy, C. Contexts and concepts of forest planning in a diverse and contradictory world. For. Policy Econ. 2011, 13, 361–365. [Google Scholar] [CrossRef]
  55. Vlčková, V.; Buček, A.; Machar, I.; Daněk, T.; Pechanec, V.; Brus, J.; Kilianová, H. The application of geobiocoenological landscape typology in the modelling of climate change implications. J. Landsc. Ecol. 2015, 8, 69–81. [Google Scholar]
  56. Kirilenko, A.P.; Solomon, A.M. Modelling dynamic vegetation response to rapid climate change using bioclimatic classification. Clim. Chang. 1998, 38, 15–49. [Google Scholar] [CrossRef]
  57. Yee, T.W.; Mitchell, N.D. Generalized additive models in plant ecology. J. Veg. Sci. 1991, 2, 587–602. [Google Scholar] [CrossRef]
  58. Woodward, F.I.; Lomas, M.R.; Betts, R.A. Vegetation-climate feedback in a greenhouse world. Philos. Trans. R. Soc. Lond. B Biol. Sci. 1998, 353, 38–39. [Google Scholar] [CrossRef]
  59. Úradníček, L.; Maděra, P.; Kolibáčová, S.; Koblížek, J. Woody Plant Species in Czech Republic; Matice Lesnická: Písek, Czech Republic, 2001; p. 333. (In Czech) [Google Scholar]
  60. Moravec, J.; Husová, M.; Chytrý, M.; Neuhäuslová, Z. Vegetation Survey of the Czech Republic. Volume 2. Hygrophilous, Mesophilous and Xerophilous Deciduous Forests; Academia: Praha, Czech Republic, 2000; p. 319. (In Czech) [Google Scholar]
  61. Zlatník, A. Overview of geobiocoene groups originally forest and shrub type in ČSR. Zprávy Geografického ČSAV 1976, 13, 55–64. (In Czech) [Google Scholar]
  62. Viewegh, J.; Kusbach, A.; Mikeska, M. Czech forest ecosystem classification. J. For. Sci. 2003, 49, 85–93. [Google Scholar]
  63. Macků, J. Climatic characteristics of forest vegetation zones of the Czech Republic. J. Landsc. Ecol. 2015, 7, 39–48. [Google Scholar] [CrossRef]
  64. Pretel, J. Current Climate Development and its Outlook. Ochr. Prir. 2009, 46, 2–7. (In Czech) [Google Scholar]
  65. Nakićenović, N.; Swart, R. Special Report on Emissions Scenarios; A Special Report of Working Group III of the IPCC; IPCC: New York, NY, USA, 2000; p. 612. [Google Scholar]
  66. Machar, I. Applying of the Biogeography Register to Predicting the Consequences of Global Climate Changes on the Landscape in the Czech Republic. In Proceedings of the 11th International Conference on Environment, Ecosystems and Development, Brasov, Romania, 1–3 June 2013; pp. 15–18.
  67. Buček, A.; Vlčková, V. Collection of Maps with Prognosis of Global Climate Changes Consequences for Nature in the Czech Republic. Acta Pruhon. 2011, 98, 83–87. [Google Scholar]
  68. Skaloš, J.; Engstová, B. Methodology for mapping non-forest wood elements using historic cadastral maps and aerial photographs as a basis for management. J. Environ. Manag. 2010, 91, 831–843. [Google Scholar] [CrossRef] [PubMed]
  69. Vlčková, V. System Nature of Modelling of Possible Trends in the Effects of Climate Change through the Technology of Geographic Information Systems Tools. Acta Inform. Prag. 2014, 3, 70–88. (In Czech) [Google Scholar] [CrossRef]
  70. Kupka, I. Is the Lang’s rain factor usable for assessing the microclimate influence on growth height of forest culture? Rep. For. Res. 2006, 51, 153–156. [Google Scholar]
  71. Botkin, D.B.; Saxe, H.; Araújo, M.B.; Betts, R.; Bradshaw, R.H.W.; Cedhagen, T.; Chesson, P.; Dawson, T.P.; Etterson, J.R.; Faith, D.P.; et al. Forecasting the effects of global warming on biodiversity. BioScience 2007, 57, 227–236. [Google Scholar] [CrossRef]
  72. Elith, J.; Leathwick, J.R. Species distribution models: Ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009, 40, 677–697. [Google Scholar] [CrossRef]
  73. Bedia, J.; Herrera, S.; Gutiérrez, J.M. Dangers of using global bioclimatic datasets for ecological niche modeling. Limitations for future climate projections. Glob. Planet. Chang. 2013, 107, 1–12. [Google Scholar] [CrossRef]
  74. Bublinec, E.; Luptáková, A.; Kúdelová, D.; Macko, J. Selected characteristics of climate in beech ecosystems. Ecology 2011, 30, 282–287. [Google Scholar] [CrossRef]
  75. Zang, C.; Hartl-Meier, C.; Dittmar, C.; Rothe, A.; Menzel, A. Patterns of drought tolerance in major European temperate forest trees: Climatic drivers and levels of variability. Glob. Chang. Biol. 2014, 20, 3767–3779. [Google Scholar] [CrossRef] [PubMed]
  76. Plesník, J.; Pelc, F. Nature and landscape in the Czech Republic and their adaptation to climate change. Ochr. Prír. 2009, 64, 30–34. (In Czech) [Google Scholar]
  77. Divisek, J.; Chytry, M.; Grulich, V.; Polakova, L. Landscape classification of the Czech Republic based on the distribution of natural habitats. Preslia 2014, 86, 209–231. [Google Scholar]
  78. Bakkenes, M.; Alkemade, J.R.M.; Ihle, F.; Leemans, R.; Latour, J.B. Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050. Glob. Chang. Biol. 2002, 8, 390–407. [Google Scholar] [CrossRef]
  79. Konvička, M.; Maradová, M.; Beneš, J.; Fric, Z.; Kepka, P. Uphill shifts in distribution of butterflies in the Czech Republic: Effects of changing climate detected on a regional scale. Glob. Ecol. Biogeogr. 2003, 12, 403–410. [Google Scholar] [CrossRef]
  80. Reif, J.; Storch, D.; Voříšek, P.; Šťastný, K.; Bejček, V. Bird-habitat associations predict population trends in central European forest and farmland birds. Biodivers. Conserv. 2008, 17, 3307–3319. [Google Scholar] [CrossRef]
  81. Gonzales, P.; Neilson, R.P.; Lenihan, J.M.; Drapek, R.J. Global patterns in the vulnerability of ecosystems to vegetation shift due to climate change. Glob. Ecol. Biogeogr. 2010, 19, 755–768. [Google Scholar] [CrossRef]
  82. Grassl, H. Status and improvements of coupled general circulation models. Science 2000, 288, 1991–1997. [Google Scholar] [CrossRef] [PubMed]
  83. Dubrovský, M.; Hayes, M.; Pierpaolo, D.; Trnka, M.; Svoboda, M.; Pierpaolo, Z. Multi-GCM projections of future drought and climate variability indicators for the Mediterranean region. Reg. Environ. Chang. 2014, 14, 1907–1919. [Google Scholar] [CrossRef]
  84. Neilson, R.P.; Pitelka, L.F.; Solomon, A.M.; Nathan, R.; Midgley, G.F.; Fragoso, J.M.V.; Lishke, H.; Thompson, K. Forecasting Regional to Global Plant Migration in Response to Climate Change. Bioscience 2005, 55, 749–759. [Google Scholar] [CrossRef]
  85. Drégelyi-Kiss, Á.; Drégelyi-Kiss, G.; Hufnagel, L. Ecosystems as climate controllers-biotic feedbacks. Appl. Ecol. Environ. Res. 2008, 6, 111–134. [Google Scholar] [CrossRef]
  86. Opdam, P.; Wascher, D. Climate change meets habitat fragmentation: Linking landscape and biogeographical scale levels in research and conservation. Biol. Conserv. 2004, 117, 285–297. [Google Scholar] [CrossRef]
  87. Walther, G.R. Community and ecosystem responses to recent climate change. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2010, 365, 2019–2024. [Google Scholar] [CrossRef] [PubMed]
  88. World Climate Research Programme. Available online: http://wcrp.ipsl.jussieu.fr/SF_RCD_CORDEX.html (accessed on 15 March 2017).
  89. EURO-CORDEX. Available online: http://www.euro-cordex.net/060378/index.php.en (accessed on 15 March 2017).
  90. Tuček, P.; Caha, J.; Janoška, Z.; Vondráková, A.; Samec, P.; Voženílek, V.; Bojko, J. Forest vulnerability zones in the Czech Republic. J. Maps 2014, 10, 179–182. [Google Scholar] [CrossRef]
  91. Jiménez-Alfaro, B.; Marcenó, C.; Bueno, A.; Gavilán, R.; Obeso, J.R. Biogeographic deconstruction of alpine plant communities along altitudinal and topographic gradients. J. Veg. Sci. 2014, 25, 160–171. [Google Scholar] [CrossRef]
  92. Parmesan, C. Biotic Response: Range and Abundance Changes. In Climate Change and Biodiversity, 1st ed.; Lovejoy, T.E., Hannah, L., Eds.; Yale University Press: New Haven, CT, USA; London, UK, 2005; pp. 41–55. [Google Scholar]
  93. Lomolino, M.V.; Riddle, B.R.; Brown, J.H. Biogeography, 3rd ed.; Sinauer Associates Inc.: Sunderland, UK, 2009; p. 752. [Google Scholar]
  94. Peterson, A.T.; Tian, H.; Martínez-Meyer, E.; Soberón, J.; Sánchez-Cordero, V.; Huntley, B. Modelling Distributional Shifts of Individual Species and Biomes. In Climate Change and Biodiversity, 1st ed.; Lovejoy, T.E., Hannah, L., Eds.; Yale University Press: New Haven, CT, USA; London, UK, 2005; pp. 211–228. [Google Scholar]
  95. Giorgi, F.; Hewitson, B.; Christensen, J.; Hulme, M.; von Storch, H.; Whetton, P.; Jones, R.; Merns, I.; Fu, C. Regional climate information—Evaluation and projection. In Climate Change 2001: The Scientific Basis; Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P., Dai, X., Maskell, K., Johnson, C.I., Eds.; Cambridge University Press: New York, NY, USA, 2002; pp. 583–638. [Google Scholar]
  96. Peterson, A.T.; Soberon, T.J.; Sanchez-Cordero, V. Conservatism of ecological niches in evolutionary time. Science 1999, 285, 1265–1267. [Google Scholar] [CrossRef] [PubMed]
  97. Vahalík, P.; Mikita, T. Possibilities of forest altitudinal vegetation zones modelling by geoinformatic analysis. J. Landsc. Ecol. 2012, 4, 49–61. [Google Scholar] [CrossRef]
  98. Mackovčin, P. A multi-level ecological network in the Czech Republic: Implementing the territorial system of ecological stability. GeoJournal 2000, 51, 211–220. [Google Scholar] [CrossRef]
  99. Průša, E. Silviculture on Typological Foundations, 1st ed.; Lesnická Práce: Kostelec nad Cernymi lesy, Czech Republic, 2001; p. 593. (In Czech) [Google Scholar]
  100. Neilson, R.P.; Prentice, I.C.; Smith, B.; Kittel, T.; Viner, D. Simulated changes in vegetation distribution under global warning. In The Regional Impacts of Climate Change: An assessment of Vulnerability; Special Report of IPCC Working Group II; Watson, R.T., Zinyowera, M.C., Moss, R.H., Dokken, D.J., Eds.; Cambridge University Press: Cambridge, UK, 1998; pp. 439–456. [Google Scholar]
  101. Prentice, I.C.; Webb, R.S.; Ter-Mikhaelian, M.T.; Solomon, A.M.; Smith, T.M.; Pitovranov, S.E.; Nikolov, N.T.; Minin, A.A.; Leemans, R.; Lavorel, S.; et al. Developing a Global Vegetation Dynamics Model: Results of an IIASA Summer Workshop; IIASA Research Report, RR-89-007; Institute for Applied Systems Analysis: Laxenburg, Austria, 1989; p. 48. [Google Scholar]
  102. Bachelet, D.R.; Neilson, R.P.; Lenihan, J.M.; Drapek, R.J. Climate Change Effects on Vegetation Distribution and Carbon Budget in the U.S. Ecosystems 2001, 4, 164–185. [Google Scholar] [CrossRef]
  103. Morin, X.; Thuiler, W. Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change. Ecology 2009, 90, 1301–1313. [Google Scholar] [CrossRef] [PubMed]
  104. Ackerman, F.; DeCanio, S.J.; Howarth, R.B.; Sheeran, K. Limitations of integrated assessment models of climate change. Clim. Chang. 2009, 95, 297–315. [Google Scholar] [CrossRef]
  105. Walther, G.R.; Post, E.; Convey, P.; Menzel, A.; Parmesan, C.; Beebee, T.J.C.; Fromentin, J.M.; Hoegh-Guldberg, O.; Fairlein, F. Ecological responses to recent climate change. Nature 2002, 416, 389–395. [Google Scholar] [CrossRef] [PubMed]
  106. Schröter, D.; Cramer, W.; Leemans, R.; Prentice, I.C.; Araújo, M.B. Ecosystem service supply and vulnerability to global change in Europe. Science 2005, 310, 1333–1337. [Google Scholar] [CrossRef] [PubMed]
  107. Trnka, M.; Brázdil, R.; Dubrovský, M.; Semerádová, D.; Štěpánek, P.; Dobrovolný, P.; Možný, M.; Eitzinger, J.; Málek, J.; Formayer, H.; et al. A 200-year climate record in Central Europe: Implications for agriculture. Agron. Sustain. Dev. 2011, 31, 631–641. [Google Scholar] [CrossRef]
  108. Spulerova, J.; Dobrovodska, M.; Izakovicova, Z.; Kenderessy, P.; Petrovic, F.; Stefunkova, D. Developing a stratégy for the protection of traditional agricultural landscapes based on a complex landscape-ecological evaluation (the case study of a mountain landscape in Slovakia). Morav. Geogr. Rep. 2013, 21, 15–26. [Google Scholar]
  109. Kongsager, R.; Locatelli, B.; Chazarin, F. Addressing Climate Change Mitigation and Adptation Together: A Global Assessment of Agriculture and Forestry Projects. Environ. Manag. 2016, 57, 271–282. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Pretel, J. Specification of Existing Estimates of the Climate Change Impacts in the Sectors of Water Management, Agriculture and Forestry Sectors, and Proposals for Adaptation; Final Report 2007–2011, Project VaV—SP/1a6/108/07; ČHMÚ: Praha, Czech Republic, 2011; p. 126. (In Czech) [Google Scholar]
  111. Campioli, M.; Vincke, C.; Jonard, M.; Kint, V.; Demarée, G.; Ponette, G. Current status and predicted impact of climate change on forest production and biogeochemistry in the temperate oceanic European zone: Review and prospects for Belgium as a case study. J. For. Res. 2012, 17, 1–18. [Google Scholar] [CrossRef]
  112. Jönsson, A.M.; Lagergren, F.; Smith, B. Forest management facing climate change—An ecosystem model analysis of adaptation strategies. Mitig. Adapt. Strateg. Glob. Chang. 2015, 20, 201–220. [Google Scholar] [CrossRef]
  113. Torres-Rojo, J.M.; Vilcko, F.; von Gadow, K. Evaluating management regimes for European beech forests using dynamic programming. For. Syst. 2014, 23, 470–482. [Google Scholar]
  114. Bilek, L.; Remes, J.; Zahradnik, D. Managed vs. unmanaged. Structure of beech forest stands (Fagus sylvatica L.) after 50 years of development, Central Bohemia. For. Syst. 2011, 20, 122–138. [Google Scholar] [CrossRef]
  115. Pretzsch, H.; Biber, P.; Uhl, E.; Dauber, E. Long-term stand dynamics of managed spruce-fir-beech mountain forests in Central Europe: Structure, productivity and regeneration success. Forestry 2015, 88, 407–428. [Google Scholar] [CrossRef]
  116. Vacek, Z.; Vacek, S.; Bilek, L.; Kral, J.; Remes, J.; Bulusek, D.; Kralicek, I. Ungulate Impact on Natural Regeneration in Spruce-Beech-Fir Stands in Cerny Dul Nature Reserve in the Orlicke Hory Mountains, Case Study from Central Sudetes. Forests 2014, 5, 2929–2946. [Google Scholar] [CrossRef]
  117. Kucbel, S.; Saniga, M.; Jaloviar, P.; Vencurik, J. Stand structure and temporal variability in old-growth beech-dominated forests of the northwestern Carpathians: A 40-years perspective. For. Ecol. Manag. 2012, 264, 125–133. [Google Scholar] [CrossRef]
Forests 08 00082 g001 550
Figure 1. Flowchart of biogeographic envelope for a regional model of climate conditions in vegetation zones of the Czech Republic
Figure 1. Flowchart of biogeographic envelope for a regional model of climate conditions in vegetation zones of the Czech Republic
Forests 08 00082 g001
Forests 08 00082 g002 550
Figure 2. Present status (2010) of climate conditions for European beech in the Czech Republic.
Figure 2. Present status (2010) of climate conditions for European beech in the Czech Republic.
Forests 08 00082 g002
Forests 08 00082 g003 550
Figure 3. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2030.
Figure 3. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2030.
Forests 08 00082 g003
Forests 08 00082 g004 550
Figure 4. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2050.
Figure 4. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2050.
Forests 08 00082 g004
Forests 08 00082 g005 550
Figure 5. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2070.
Figure 5. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2070.
Forests 08 00082 g005
Forests 08 00082 g006 550
Figure 6. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2090.
Figure 6. Visualization of predicted distribution of climate conditions for the European beech in the Czech Republic in 2090.
Forests 08 00082 g006
Table
Table 1. Current extent and future areas with projected climatic characteristics corresponding to the respective forest vegetation zones of the Czech Republic.
Table 1. Current extent and future areas with projected climatic characteristics corresponding to the respective forest vegetation zones of the Czech Republic.
Forest Vegetation ZoneExtent of Climate Conditions for Vegetation Zones in
20102030205020702090
% from the Area of the Czech Republic
1.Oak3.463.9812.7838.4140.82
2.Beech-oak12.0614.295.4938.5138.51
3.Oak-beech18.2120.1420.1416.4116.41
4.aBeech39.6246.2254.915.603.98
4.bOak-coniferous variety of the fourth vegetation belt3.628.690.000.000.00
5.Fir-beech19.405.605.601.070.28
6.Spruce-fir-beech2.530.800.800.000.00
7.Spruce1.000.280.280.000.00
8.Dwarf pine subalpine0.100.000.000.000.00
Table
Table 2. Current state and prediction of the climate conditions for European beech in the Czech Republic (forecast period 2030, 2050, 2070, and 2090 year).
Table 2. Current state and prediction of the climate conditions for European beech in the Czech Republic (forecast period 2030, 2050, 2070, and 2090 year).
Climate Conditions20102030205020702090
km2
Unsuitable climate2144.862728.522144.8630,281.8630,281.86
Moderately suitable climate10,624.1018,522.5712,258.3723,510.9224,781.26
Suitable climate30,883.5823,772.2523,027.4822,092.2321,281.24
Optimum climate35,182.7133,811.9141,404.542950.252490.89

Share and Cite

MDPI and ACS Style

Machar, I.; Vlckova, V.; Bucek, A.; Vozenilek, V.; Salek, L.; Jerabkova, L. Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests. Forests 2017, 8, 82. https://doi.org/10.3390/f8030082

AMA Style

Machar I, Vlckova V, Bucek A, Vozenilek V, Salek L, Jerabkova L. Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests. Forests. 2017; 8(3):82. https://doi.org/10.3390/f8030082

Chicago/Turabian Style

Machar, Ivo, Veronika Vlckova, Antonin Bucek, Vit Vozenilek, Lubomir Salek, and Lucie Jerabkova. 2017. "Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests" Forests 8, no. 3: 82. https://doi.org/10.3390/f8030082

APA Style

Machar, I., Vlckova, V., Bucek, A., Vozenilek, V., Salek, L., & Jerabkova, L. (2017). Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests. Forests, 8(3), 82. https://doi.org/10.3390/f8030082

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop