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Forest ecosystems: forecasting, modeling and vulnerability

Forest ecosystems: forecasting, modeling and vulnerability. Roman COROBOV Republic of Moldova. Historical aspect and current state. Construction of ecology-phytocoenotic rows. Assessment of stability and sensitivity. Development of future bioclimate scenarios.

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Forest ecosystems: forecasting, modeling and vulnerability

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  1. Forest ecosystems:forecasting, modeling and vulnerability Roman COROBOV Republic of Moldova

  2. Historical aspect and current state Construction of ecology-phytocoenotic rows Assessment of stability and sensitivity Development of future bioclimatescenarios Ecosystem transformation in new climate Principal steps in the assessment of ecosystem sensitivity to climate change

  3. Mid-European wide-leaf zone Mid-European wide-leave forests West-European sea climate Balti steppe East-European continental climate European-Asia Steppe Zone Budjac steppe Mediterranean forest zone Subtropical steppe Xerophilic oak forest Mediterranean climate Forming the Moldova’s Natural Ecosystems

  4. Step 1. Natural forests - historical aspect Forest areas: Northern forest Beech forests Codru Oak-hornbeam Southern forests Oaks occupy about half of all forest territory

  5. Dynamic of forest fund 1848 1861 1875 1893 1914 1918 1925 1965 1985 1997 Most forests were cut before the 1850s, with the lowest forest cover in 1918-1925. At present, forests occupy only about 9-10% of Moldova territory

  6. Changes in forest composition (1925-2000) 1925 1962 1985 1997 In the 20th century some increase of oak forests and maximal decrease of beech ones took place, along with significant increase of introducents share.

  7. Step 2: Development of ecological rows as the model of natural ecosystems change in new climatic conditions Essence of the method: Today’s temporal and spatial transition from ones plant types to the others is used as an objective criterion for assessment of the directions and parameters of natural ecosystem qualitative changes in new climate

  8. Percentage of Moldova wetlands with different levels of ground water (m) Ecological row of meadow ecosystems Fresh and dry meadow When runoff decreases Bottomland meadow When runoff increases Grass marsh

  9. Forest type Ash-willow stand (Saliceta cinereae) White-willow stand (Saliceta albae) White poplar stand (Populeta albae) English oak forest (Querceta roboris) Salicetum phragmitosum (australis) Salicetum phragmitosum (australis) Populetum rubosum (caesi) Quercetum aegopodiosum (podagrariae) S. typhosum (latifoliae) P. aegopodiosum (podagrariae) Q. sambucosum (nigrae) S. typhosum (angustifoliae) Associations S. thelipteridosum (palustris) S. caricosum (ripariae) P. rubosum (caesii) Q, corylosum (avelanae) S. caricosum (acutiformis) S. rubosum (caesii) P. convollariosum (majalis) Q. urticosum (dioicae) S. elytrigosum (repentis) Increase of aridity Ecological row of flood plain forest community depending on humidity conditions

  10. Step 3:Assessment of forest stability & sensitivityby ecological demands of dominant species to temperature and precipitation In baseline climate outside of optimum conditions are : Quercus pubescens - by temperature,Fagus sylvatica - by humidity. Quercus roburhas most wide ecological amplitude by humidity factor.

  11. East boundary Ecological optimum South-East boundary North boundary Disposition of key forest species in their area Кодры North South Fagussylvatica Carpinus betulus Quercus petraea Quercus robur Quercus pubescens Tilia tomentosa Tilia platyphyllos Malus sylvestris Pyrus pyrester Ulmus carpinifolia Fraxinus excelsior Acer campestris Acer tatarica Viburnum lantana Cerasus avium Tilia cordata Sorbus domestica Carpinus orientalis Cotinus coggygria Ligustrum vulgare Rhamnus tinctoria Crataegus pentagyna Pyrus elaeagnifolia Acer pseudoplatanus Sorbus torminalis Hedera helix Acer pseudoplatanus

  12. To precipitation decrease To temperature increase Vulnerable Sustainable Sustainable Fagus sylvatica Quercus petreae Carpinus betulus Acer pseudoplatanus Betula pendula Tilia tomentosa Sorbus aucuparia Padus racemosa Quercus robur Quercus pubescens Tilia cordata Fraxinus excelsior Acer tatarica Carpinus orientalis Sorbus domestica Quercus pubescens Tilia cordata Sorbus domestica Sorbus torminalis Carpinus orientalis Fraxinus excelsior Sensitivity of forest species to climatic changes

  13. Statistical comparison of temperature & precipitation effects on streamflow 10 % annual temperature change 10 % precipitation change 5.0/6.6 % streamflow change 6.5/7.7 % streamflow change

  14. 49,6 49,4 1 49,2 Water level 0,6 49 49,7 0,2 Crosscorrelations 48,8 -0,2 49,5 48,6 -0,6 0 40 80 120 160 Water level 49,3 -1 Precipitation -13 -8 -3 2 7 12 17 1 lag 49,1 0,6 0,2 Crosscorrelations 48,9 27 37 47 57 67 -0,2 Precipitation -0,6 -1 -10 -6 -2 2 6 10 lag Simple and cross-correlation between monthly (left) and annual (right) underground water level and precipitation r = 0.075 r = 0.165

  15. Step 4-5: Projections of change under different climate change scenarios

  16. Water supply (W) Heat supply (T, Ñ) Temperate warm (104-124) Warm (125-144) Very warm (145-164) Hot (165-184) Fresh(2.0  0.6) 2e 2f - - Dry(0.6  -0.8) 1e 1f 1g 1h Very dry (-0.8 -2.2) 0e 0f 0g 0h T = T = Ti, where Ti - mean monthly air temperatures in a month with positive temperatures W = P/T – 0.0286 T, where P – precipitation sum for months with positive air temperatures 1969-1990 2010-2039 2040-2069 2070-2099 SRES A2 based climate of forest habitats

  17. Remaining uncertainties (IPCC, 2007): • although not completely quantified, many species can achieve rapid large-scale migrations, under a considerable range of lagged responses; • future landscapes will differ substantially from past climate change situations and landscape fragmentation creates major obstacles to migration; • migration is moderated by such processes as competition, soil formation, land use, herbivores, pathogens; • tree species do not only respond to a changing climate by migration, but also by local adaptation, including genetic one.

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