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From landscape to individuals: forest dynamics under global change
- 1. From landscape to individuals: forest dynamics under global change Aitor Ameztegui CREAF - CTFC Lleida, 5 December 2016
- 4. Politicians Discussing Global Warming Isaac Cordal, Berlin
- 5. Politicians Discussing Global Warming Isaac Cordal, Berlin
- 18. Predictions in species distributions Hanewinkel et al. 2013, Nature Clim Cha
- 19. Predictions in species distributions Hanewinkel et al. 2013, Nature Clim Cha
- 20. Predictions in species distributions Hanewinkel et al. 2013, Nature Clim Cha
- 21. Predictions in species distributions Hanewinkel et al. 2013, Nature Clim Cha
- 22. Theurillat & Guisan, 2001, Clim Cha Predictions in species distributions
- 23. Theurillat & Guisan, 2001, Clim Cha Predictions in species distributions
- 24. Observed changes in species distributions Peñuelas & Boada, 2003, Glob. Cha. Biol
- 25. Observed changes in species distributions Peñuelas & Boada, 2003, Glob. Cha. Biol Palombo et al, 2013, Plant Bios.
- 26. Observed changes in species distributions Peñuelas & Boada, 2003, Glob. Cha. Biol Palombo et al, 2013, Plant Bios. Beckage et al, 2008, PNAS
- 27. Hättenschwiler & Körner, 1995 Observed changes in species distributions
- 28. Hättenschwiler & Körner, 1995 Observed changes in species distributions
- 29. Hättenschwiler & Körner, 1995 Observed changes in species distributions
- 30. Lenoir et al, 2010, Ecography Hättenschwiler & Körner, 1995 Observed changes in species distributions
- 31. Lenoir et al, 2010, Ecography Hättenschwiler & Körner, 1995 Observed changes in species distributions Why?
- 32. climate change is just part of the story
- 33. climate change is just part of the story GLOBAL
- 35. Climate change
- 39. Climate change Nitrogen deposition Land-use changes Atmospheric CO2 Biotic exchanges (inv. species)
- 41. Importance of components of global change Sala et al. (2000). Science
- 42. Importance of components of global change Sala et al. (2000). Science
- 49. Pinus uncinata = (P. mugo ssp. uncinata) 65.000 ha. Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Photo Credit: Lluís Coll
- 50. Pinus uncinata = (P. mugo ssp. uncinata) 65.000 ha. Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Photo Credit: Lluís Coll
- 51. Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog
- 52. Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog
- 53. Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog
- 54. Forest expansion in the Pyrenees P. uncinata in 1956 Encroached areas Ameztegui et al. 2010, Glob. Ecol. Biog
- 55. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Forest expansion in the Pyrenees P. uncinata in 1956 Encroached areas Ameztegui et al. 2010, Glob. Ecol. Biog
- 56. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Forest expansion in the Pyrenees P. uncinata in 1956 Encroached areas Ameztegui et al. 2010, Glob. Ecol. Biog
- 57. ALTITUDE vs COLONIZ ALTITUDE vs DENSIF ALTITUDE vs COLONIZ ALTITUDE vs DENSIF Shade index (º) 0 20 40 60 80 100 120 140 160 180 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Altitude (m) 1400 1600 1800 2000 2200 2400 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Grasslands (%) 0 20 40 60 80 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * Population change (%) 50 100 150 200 Probability 0,0 0,2 0,4 0,6 0,8 1,0 *
- 58. ALTITUDE vs COLONIZ ALTITUDE vs DENSIF ALTITUDE vs COLONIZ ALTITUDE vs DENSIF Shade index (º) 0 20 40 60 80 100 120 140 160 180 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Altitude (m) 1400 1600 1800 2000 2200 2400 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Grasslands (%) 0 20 40 60 80 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * Population change (%) 50 100 150 200 Probability 0,0 0,2 0,4 0,6 0,8 1,0 *
- 59. ALTITUDE vs COLONIZ ALTITUDE vs DENSIF ALTITUDE vs COLONIZ ALTITUDE vs DENSIF Shade index (º) 0 20 40 60 80 100 120 140 160 180 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Altitude (m) 1400 1600 1800 2000 2200 2400 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Grasslands (%) 0 20 40 60 80 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * Population change (%) 50 100 150 200 Probability 0,0 0,2 0,4 0,6 0,8 1,0 *
- 60. ALTITUDE vs COLONIZ ALTITUDE vs DENSIF ALTITUDE vs COLONIZ ALTITUDE vs DENSIF Shade index (º) 0 20 40 60 80 100 120 140 160 180 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Altitude (m) 1400 1600 1800 2000 2200 2400 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Grasslands (%) 0 20 40 60 80 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * Population change (%) 50 100 150 200 Probability 0,0 0,2 0,4 0,6 0,8 1,0 *
- 61. ALTITUDE vs COLONIZ ALTITUDE vs DENSIF ALTITUDE vs COLONIZ ALTITUDE vs DENSIF Shade index (º) 0 20 40 60 80 100 120 140 160 180 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Altitude (m) 1400 1600 1800 2000 2200 2400 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * * Forest expansion in the Pyrenees Ameztegui et al. 2010, Glob. Ecol. Biog Grasslands (%) 0 20 40 60 80 Probability 0,0 0,2 0,4 0,6 0,8 1,0 * Population change (%) 50 100 150 200 Probability 0,0 0,2 0,4 0,6 0,8 1,0 *
- 62. “Forests occupy the land on which the plow can not go”
- 63. “Forests occupy the land on which the plow can not go” Pliny the Elder (AD 23 – AD 79)
- 65. Traditional land-uses in European mountains “Forests occupy the land on which the plow can not go” Molina (2002)
- 66. Traditional land-uses in European mountains “Forests occupy the land on which the plow can not go” Molina (2002)
- 75. Photo Credit: Lluís Coll Does not mean there is no role of climate Does not mean there is no upward spread
- 76. Photo Credit: Lluís Coll Does not mean there is no role of climate Does not mean there is no upward spread
- 77. Ameztegui et al. 2016, Glob. Ecol. Biog
- 78. Ameztegui et al. 2016, Glob. Ecol. Biog
- 79. Ameztegui et al. 2016, Glob. Ecol. Biog
- 80. Ameztegui et al. In prep
- 81. Ameztegui et al. In prep PN Aigüestortes i Estany de Sant Maurici
- 82. Ameztegui et al. In prep
- 83. Ameztegui et al. In prep Total Forest Closed Forest FCC (%) 1956 9,000 ha 8,100 ha 54,3 2006 9,200 ha 8,950 ha 62,8 Change +2% +10%
- 91. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Consequences of forest expansion Photo: M. Beltran
- 92. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Consequences of forest expansion Photo: M. Beltran
- 93. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Consequences of forest expansion Photo: M. Beltran
- 94. Surface (ha) FCC (%) 1956 55.196 31,2 2006 64.074 (+15%) 55,6 Consequences of forest expansion Photo: M. Beltran
- 99. Climate change
- 100. Climate change
- 102. So how can we manage this? Experience on its own is an adequate basis for predicting the future if the future is exactly like, or very similar to, the past. This is generally not the case. This is bit like driving a car slowly down a freeway with the front windshield covered. One can navigate safely looking only in the rear-view mirror because the future direction of the road is changing slowly relative to the past direction and one’s speed. The knowledge gained from the rear view mirror (experience of the past) will show you when you start to go off the road in sufficient time for a course correction. But such a navigational procedure is not appropriate for driving on a winding mountain road where the future changes rapidly and unpredictably relative to the past. In such cases excessive reliance on experience will probably result in your vehicle going off the road Hamish Kimmins UBC
- 103. So how can we manage this? We need to anticipate future conditions Hamish Kimmins UBC
- 104. So how can we manage this? We need to anticipate future conditions Hamish Kimmins UBC MODELS
- 105. Statistical models that relate the current distribution of species and ecosystems to climate variables Types of models 1
- 106. Statistical models that relate the current distribution of species and ecosystems to climate variables Types of models 1
- 107. Statistical models that relate the current distribution of species and ecosystems to climate variables Types of models 1
- 108. Statistical models that relate the current distribution of species and ecosystems to climate variables Types of models 1
- 109. Process models based on ecophysiology2 Types of models
- 110. Population models that incorporate the effects of climate on the demography of species 3 Types of models
- 111. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Each species responds individually
- 112. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Each species responds individually • Competition, interactions
- 113. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Each species responds individually • Competition, interactions • Same scale as management
- 114. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Each species responds individually • Competition, interactions • Same scale as management • Easier to parameterize
- 115. Population models that incorporate the effects of climate on the demography of species 3 Types of models
- 116. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Parameterization time- consuming
- 117. Population models that incorporate the effects of climate on the demography of species 3 Types of models • Parameterization time- consuming • Computationally exigent
- 118. P. uncinata P. sylvestris A. alba OK, let’s model! What do we need?
- 119. Data requirements Allometry & resources Growth Mortality Dispersal & recruitment Climate change
- 120. Data requirements Allometry & resources Growth Mortality Dispersal & recruitment Climate change
- 121. Garbage In ————> Garbage Out
- 122. Garbage In ————> Garbage Out Your analysis is as good as your data
- 123. Modified from Loehle (2000) Fundamental niche differentiation Whittaker (1975)
- 124. Modified from Loehle (2000) Fundamental niche differentiation Whittaker (1975) Shifting competitive hierarchy Keddy (1989)
- 125. Modified from Loehle (2000) Fundamental niche differentiation Whittaker (1975) Shifting competitive hierarchy Keddy (1989) Continuum concept Austin and Smith (1990)
- 126. Modified from Loehle (2000) Fundamental niche differentiation Whittaker (1975) Shifting competitive hierarchy Keddy (1989) “Species are often limited by physical stresses at one margin, but by biotic interactions at the other, more favorable, margin of their distribution along environmental gradient” (Lenoir, 2010) Continuum concept Austin and Smith (1990)
- 127. Modified from Loehle (2000) Fundamental niche differentiation Whittaker (1975) Shifting competitive hierarchy Keddy (1989) “Species are often limited by physical stresses at one margin, but by biotic interactions at the other, more favorable, margin of their distribution along environmental gradient” (Lenoir, 2010) Continuum concept Austin and Smith (1990) Species-specific effects of climate
- 128. Allometry & resources Growth Mortality Dispersal & recruitment Climate change OK, let’s model! What do we need?
- 131. Canham & Murphy, 2016, Ecosphere
- 137. Effect of climate on growth & mortality Adapted from Gomez-Aparicio et al, 2011, Glob Ecol Biog
- 138. Adapted from Ruiz-Benito et al. 2013, PLoS One Effect of climate on growth & mortality Adapted from Gomez-Aparicio et al, 2011, Glob Ecol Biog
- 139. Adapted from Ruiz-Benito et al. 2013, PLoS One Effect of climate on growth & mortality Adapted from Gomez-Aparicio et al, 2011, Glob Ecol Biog Juvenile growth and mortality
- 140. P. sylvestris P. uncinataA. alba Effects of climate change: space for time approach x6
- 141. Subalpine belt (2000 m) ↓ Temperatures ↑ Precipitations ↑ Snow cover ↓ Growing season P. sylvestris P. uncinataA. alba Effects of climate change: space for time approach Montane belt (1500 m) ↑ Temperatures ↓ Precipitations ↓ Snow cover ↑ Growing season x6
- 142. Subalpine belt (2000 m) ↓ Temperatures ↑ Precipitations ↑ Snow cover ↓ Growing season P. sylvestris P. uncinataA. alba Effects of climate change: space for time approach Montane belt (1500 m) ↑ Temperatures ↓ Precipitations ↓ Snow cover ↑ Growing season x6
- 143. Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 144. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 145. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 146. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 147. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 148. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 149. Survival period (months) Accumulatedsurvival 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 Pinus sylvestris P < 0.001 (log-rank) Survival period (months) 0 9 15 21 27 33 39 Accumulatedsurvival 0.5 0.6 0.7 0.8 0.9 1.0 Abies alba P = 0.044 (log-rank) Survival period (months) Accumulatedsurvival Pinus uncinata 0 9 15 21 27 33 39 0.5 0.6 0.7 0.8 0.9 1.0 P = 0.214 (log-rank) Effect of climate on juvenile mortality Ameztegui & Coll, 2013 For. Ecol. Manag.
- 150. Effect of climate on juvenile growth Relative height growth Montane Subalpine Difference 0.381 0.305 -19.9% *** 0.289 0.232 -19.7%*** 0.207 0.160 -22.7%*** 0.283 0.276 -2.4% n.s. Betula pendula Pinus sylvestris Abies alba Pinus uncinata Ameztegui & Coll, 2013 For. Ecol. Manag.
- 151. Effect of climate on juvenile growth Differences in growth match differences in growing period between sites (20%) Relative height growth Montane Subalpine Difference 0.381 0.305 -19.9% *** 0.289 0.232 -19.7%*** 0.207 0.160 -22.7%*** 0.283 0.276 -2.4% n.s. Betula pendula Pinus sylvestris Abies alba Pinus uncinata Ameztegui & Coll, 2013 For. Ecol. Manag.
- 152. Effect of climate on juvenile growth Differences in growth match differences in growing period between sites (20%) Relative height growth Montane Subalpine Difference 0.381 0.305 -19.9% *** 0.289 0.232 -19.7%*** 0.207 0.160 -22.7%*** 0.283 0.276 -2.4% n.s. Betula pendula Pinus sylvestris Abies alba Pinus uncinata P. uncinata is unresponsive to elevation Ameztegui & Coll, 2013 For. Ecol. Manag.
- 153. Effect of climate on juvenile growth Differences in growth match differences in growing period between sites (20%) Relative height growth Montane Subalpine Difference 0.381 0.305 -19.9% *** 0.289 0.232 -19.7%*** 0.207 0.160 -22.7%*** 0.283 0.276 -2.4% n.s. Betula pendula Pinus sylvestris Abies alba Pinus uncinata P. uncinata is unresponsive to elevation Ameztegui & Coll, 2013 For. Ecol. Manag. Hättenschwiler & Körner, 1995
- 154. Effect of climate on juvenile growth & mortality Modified from Loehle, 2000, Can J For Res
- 155. Effect of climate on juvenile growth & mortality Modified from Loehle, 2000, Can J For Res
- 156. Effect of climate on juvenile growth & mortality Modified from Loehle, 2000, Can J For Res
- 157. Effect of climate on juvenile growth & mortality Modified from Loehle, 2000, Can J For Res
- 159. So: what can we expect? Not the same factor for upper and lower limits (temperatures vs. competition, drought) Subalpine species unlikely to decline (restrict upward migration, species interactions) P. uncinata P. sylvestris A. alba
- 160. So: what can we expect? Not the same factor for upper and lower limits (temperatures vs. competition, drought) Subalpine species unlikely to decline (restrict upward migration, species interactions) P. uncinata P. sylvestris A. alba
- 161. ? ? Vegetation may not migrate as an entity, but changes in community composition and species interactions should be expected So: what can we expect? Not the same factor for upper and lower limits (temperatures vs. competition, drought) Subalpine species unlikely to decline (restrict upward migration, species interactions) P. uncinata P. sylvestris A. alba
- 162. ? ? Vegetation may not migrate as an entity, but changes in community composition and species interactions should be expected So: what can we expect? Not the same factor for upper and lower limits (temperatures vs. competition, drought) Subalpine species unlikely to decline (restrict upward migration, species interactions) P. uncinata P. sylvestris A. alba Model of forest dynamics
- 164. SORTIE-ND: individual-based model of forest dynamics JABOWA (Botkin et al. 1972) SORTIE (Pacala et al, 1993, 1996) FORET (Shugar and West, 1977) SORTIE-ND: spatially-explicit, individually-based model Lines, 2012
- 165. Ini$al condi$ons: juvenile growth P. uncinata – P. sylvestris (ecologically similar) P. uncinata – A. alba (more shade-tolerant fir) +10% +25% +50% +10% +25% +50% -10% -25% -50%
- 166. Results: juvenile growth Increases in growth can lead to higher presence of P. sylvestris and species substitution
- 167. Results: juvenile growth Ameztegui, Coll & Messier, 2015 Increases in growth can lead to higher presence of P. sylvestris and species substitution
- 168. Results: juvenile growth and initial composition In the case of an ecotone with ecologically different species, increases in growth do not represent a change in final composition
- 169. Results: juvenile growth and initial composition In the case of an ecotone with ecologically different species, increases in growth do not represent a change in final composition
- 178. Humid Mesic Xeric 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0 1000 2000 3000 4000 0010203040506070 CD0−5 D5−10 D10−15 D15−20 D20−25 D25−30 D30−35 D35−40 D40−45 D45−50 D50−55 D55−60 CD0−5 D5−10 D10−15 D15−20 D20−25 D25−30 D30−35 D35−40 D40−45 D45−50 D50−55 D55−60 CD0−5 D5−10 D10−15 D15−20 D20−25 D25−30 D30−35 D35−40 D40−45 D45−50 D50−55 D55−60 Stems·ha NoCC CCB2 CCA2 20 40 60 20 40 60 20 40 60 PlotAPlotBPlotC 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 Year BasalArea(m2·ha−1) Intensity 00 10 20 30 40 50 60 70 Type Low
- 181. Take-home messages In Mediterranean mountains, land-use changes cannot be forgotten when assessing the effects of global change on forest dynamics Before modelling, we need to know our species, which factors are affecting them and in which direction The effects of climate change will be defined by species-specific responses and by interspecific competitive relationships Species combinations and current structure are important, since responses are not the same if competitors are ecologically similar (Pines) or if they have different requirements
- 182. Take-home messages In Mediterranean mountains, land-use changes cannot be forgotten when assessing the effects of global change on forest dynamics Before modelling, we need to know our species, which factors are affecting them and in which direction The effects of climate change will be defined by species-specific responses and by interspecific competitive relationships Species combinations and current structure are important, since responses are not the same if competitors are ecologically similar (Pines) or if they have different requirements Importance of explicitly considering land-use changes and biotic interactions when modelling climate change
Editor's Notes
- how many of you have seen this image before?. It went viral in the social media a couple of weeks ago. How many? No one? It represents the temperature departure in the Northern Hemisphere for the 17th november, as compared to the average temperature between 1979 and 2000. And the striking thing is, as you see, that the arctic was like 20 degrees above the average temperature in the area. This is just an example, one of the fastest shocking evidences, that shows that climate change is no longer am uncertain threat that will affect us in the future, but a current reality that is affecting us today. But as I said, it is just an example, there are many more
- Look, for example, at this chart. It is showing the extent of arctic see ice during winter, and comparing the average between 19811 and 2000 with 2016. And you see 2016 is a pretty bad year, second worse only after 2012.
- But of course there are climate skeptics, people that say that these phenomena are not proof of anything. I particularly like this installation, it’s from a Spanish artist and can be seen in Berline, and it’s called. And it reflects the attitude of some people about climate change: it doesn’t matter the evidences, they could literally have the water at the neck level and would still doubt about it. And it could get even worse, with the new political context, in which we have the president-elect of the US, who just said that climate change is an hoax created by Chinese…
- But despite these voices, the truth is there is a trend, a clear trend, no matter if you consider the last 25 years, 50 or 100 years. Temperatures are rising, and the rise is matching the increase in CO2 in the atmosphere, which by the way it’s in its maximum in recent (and no so recent) history.
- It is even more clear in this figure, created by Ed Hawkins. Here we can see the evolution of monthly temperatures from 1850 to 2016. D’you know this one? let’s have it a look, it is nice to see. So you see 2016 is really an extraordinary year. Actually, this stops in February, but since then, every single month has been the hottest on average since there are records. But it is clear here that there is a trend
- And the predictions are even worse, because even the most optimistic scenarios forecast a 2 degree increase in temperatures, and some models predict even 6 to 7 degrees, which would be catastrophic
- And we all know about the consequences for iconic species like polar bears. But what about forests? Are the impacts of climate change already visible in the forest?
- So this is an example. Does anyone know what is this picture showing? Why are these trees leaning? This is a phenomenon called ‘drunken trees’ or ‘drunken forests’ because the trees do really seem to have drunken a bit too much. It happens mostly on boreal forests in Canada and Siberia, and is a consequence of climate change. The soils in these area are usually frozen during most of the year, this is what is called: permafrost. Consequently, roots cannot penetrate the hard frozen layer, and trees are adapted to shallow soils by making very shallow root systems. With the increase in temperatures, soils that used to be frozen begin to thaw, and the soil then becomes soft and can no longer hold the trees weight. Since the roots are shallow, the trees lean or even fall.
- But again, this is only an example, let-s try to systematize a bit more which can be the effects of climate change on forests. This diagram has some years, but I think it is still mostly valid. Here it classifies the effects of climate change on forests as effects on physiology, on phonology, on species distributions and in situ adaptations. All these effects can actually act together, creating changes in species interactions, and we can have a feedback in which these changes further causes shifts in distribution. But the final result is that we will have changes in structure and composition of the forests.
- There are many examples of these changes, like an increase in the duration of the growing season caused by advances in leaf unfolding, physiological changes like drought-related decay episodes, or changes on biotic interactions, such as this study in which the authors observed an increase in the activity of the pine processionary moth at higher elevations, because milder winters allow moths to survive at higher elevations.
- But I think someone has already talked you about the effects of climate change, or someone will be, so I want to focus in the changes in species distribution. Since vegetation is largely distributed along latitudinal belts that are mainly controlled by climate, it is not surprising that most models have predicted large changes in species distribution, mainly a northward displacement of forest ecosystems. Depending on the rate of change in temperatures and the ability of species to track these changes, this could also lead to a decline in the surface devoted to some species and even to some extinctions. Here, for example, you can see the predicted changes in species distribution across Europe based on the current distribution of species according to the forest inventory. And you can see that for most groups of species the predictions are a large northward displacement, but some groups, as pines or birch would significantly reduce their surface, whereas others, such as oaks, would increase their surface.
- In mountain areas, vegetation distributes along elevational belts, and therefore the predictions are of an upward displacement of these belts, and consequently, a reduction in the surface of alpine and nival belts, so that some species that are exclusive of these elevational ranges may even become extint. These are, for example, predictions for the Swiss Alps, and you see how the belts would be displaced in elevation.
- But all these studies are predictions about what will happen in mountain forests in the future. Then, one could wonder, if, according to IPCC, the effects of climate change are already noticeable, can we observe changes in species distribution over the last decades? Is there a signal that indicates mountain forests are migrating northwards? And, well, the response, as in many cases in science – at least the most interesting cases in science – would be “it depends”. There are of course some studies that have detected changes in species distribution. For example, this is a study in the Catalan mountains that reported an elevational displacement of Mediterranean species (mainly holm oak) into forests previously dominated by temperate species such as European beech. Another example comes from the Italian Appenines, where you can even visually appreciate that Pinus mugo is expanding upwards and has reached the top of the mountain. Or, in North American forests, Beckage observed an increase in the relative importance of hardwood forests as compared to boreal forests in the mountains of Vermont.
- These are only a few examples, there are of course more, but more interestingly, there are also examples of a total lack of displacement in species distribution, and even of significant downward displacements. In a meta-analyses of the responses of treeline worldwide, Harsch and others found that only half of the studied treelines actually showed a significant upward displacement. And Lenoir, in 2010, observed that 65% of the species in french mountain forests showed upward shifts, 10% remained stable, but up to 25% moved downwards. Why? Which do you think can be the reasons of these downward displacements? how can they be explained?
- There is a variety of reasons, but one of them is that climate change, despite being of course a very real and worrying phenomenon, is just part of the story. And instead of climate change, we should better talk about global change, which includes CC but is broader and include also other processes.
- In the literature there are usually 5 processes that are considered to be part of global change: can you name a few?
- And which one do you think is more important? Why? Globally, it is estimated that land-use changes are the most important process, followed by climate-change, but the relative weight or importance of each of these components on ecosystems is not the same, and varies across biomes, so that we can find the main component to be different depending on which biome we are. For example if we consider tropical or southern temperate forests, land-use changes are the most important.
- But what about Europe? Which are the main changes we can see in European forests? this is a reconstruction of forest cover in Europe in the last 100 years. What do you expect to see? Ok, Let’s see What have you seen?
- And if we focus in Spain, the trend is the same, even more pronounced.
- And which one do you think is more important? Globally, it is estimated that land-use changes are The relative weight or importance of each of these components on ecosystems is not the same, and more importantly, it also varies across biomes, so that we can find the main component to be different depending on which biome we are. In the case of the European mountains, at least southern European mountains such as the Pyrenees, the Alps the Appenines, as they are located in a transition area between alpine and mediterranean regions, land-use changes and climate change emerge as the main drivers of change.
- So this was our main objectove in this study, to better understand which is the role of climate and land-use changes in forest expansion? We wanted to quantify the processes of forest expansion, assess the spatial patterns of these processes and infer, from them, the main driving factors We used Pinus uncinata as study case, and we compared more than 200 pairs of aerial photographs, half taken in the 50’s, in the so-called american flight (it was partially funded by the US Army), and some taken in 2006, 50 years later. We used more than 200 pairs of aerial photographs, so we covered the whole distributional range of the species in Catalonia (more than 65,000 ha, a 75% of the total in the Pyrenees)
- The procedure we used was the following: we established a 150 x 150 m grid and reclassied the black and white images into a binary map (forest/no forest), and determined the forest cover, for each cell, in 1956 and 2006. With this, we could define the two major processes. We observed that indeed, Pinus uncinata had increased its surface by more than 15% in the last 50 years. Furthermore, we also observed that mean canopy cover had almost doubled in the same period. We then overlapped these patterns with some topographic variables such as elevation, slope or aspect, but also with some socio-economic variables that captured the potential changes in land-use at the municipality level: population change, population density, importance of primary dector, ect.
- The procedure we used was the following: we established a 150 x 150 m grid and reclassied the black and white images into a binary map (forest/no forest), and determined the forest cover, for each cell, in 1956 and 2006. With this, we could define the two major processes. We observed that indeed, Pinus uncinata had increased its surface by more than 15% in the last 50 years. Furthermore, we also observed that mean canopy cover had almost doubled in the same period. We then overlapped these patterns with some topographic variables such as elevation, slope or aspect, but also with some socio-economic variables that captured the potential changes in land-use at the municipality level: population change, population density, importance of primary dector, ect.
- Once the expansion and densification were quantified, it was the time to assess the spatial patterns. We related the probability of expansion to: And more interestingly, we also observed that patterns of expansion matched data on the municipality level. So we observed, as an example, that colonization was higher in those muncipilaties that had greater population looses, whereas in those municipalities where grasslands were still important, colonization was lower. With this information, we checked if patterns of land-abandonment could explain these patterns of expansion
- This is a typical landscape one can fin in these areas, and there is a known quote by a famous naturalist that described Spanish woodlands by saying that forests occupy the land in which the plow cannot go. And this is actually true, you see that forests are really limited to the slopes and the river banks, while the rest of the surface is agricultural crops. But the funny thing is, to give you an idea of the long history of land uses and habitat modification in Europe, that this sentence was written by Pliny the Elder, a Roman naturalist and geographer that lived in the first century of our Era.
- And indeed, in mountain areas such as the Pyrenees, traditional use of the landscape has been determined by the need to be as autonomous as possible, since these areas have been quite isolated from the main valleys and cities until some decades ago. Thus, the economy was based on small, familiar exploitation, with all the arable land devoted to agriculture – mainly cereals – a high grazing pressure of sheeps and goats, a high pressure into forest, that were a source of both timber and fuelwood, and extensive use of fire as a tool to control vegetation and promote pastures. The consequence is a landscape similar to this one, in which the forest, as related by the Roman geographer, was only in the hillslopes.
- You see the forest is restricted to the upper part and every available piece of land is exploitied, mainly for agriculture but also fr other uses. From the 40’s and 50’s, there were important socioeconomic changes that led to a sharp depopulation of the Pyrenees, and mainly three processes occured in the landscape (1, 2, 3) Wiith this new context, the landscape changed into something more similar to this, or to make it more visual, to this.
- Wiith this new context, the lanscape changed into something more similar to this, or to make it more visual, to this.
- Of course, our findings doesN’T mean at all that there is no advance of the treeline in the Pyrenees. Actually, there is, and in a study we are currently performing we have observed that the treeline has advanced on average 40 m. But the advance can also be related to changes in land-use, and we have seen that those areas that had a more intense use in the past are those in which the treeline displacement has been greater. So, as I said, there has been an upward displacement of the limit, but there has been a more intense downward displacement into abandoned farmlands and croplands
- This findings have also been observed in several mountain areas in Europe. For example, Gehrig-Fasel found in a study in the Swiss Alps that most of the advance in treeline was due to an infilling of a potential distribution that was previously lowered due to land-uses, and not to actual climatic signal. This has also been observed for the Italian appenines,
- Obviously, this has consequences. If you remember, we had observed that mean canopy cover had increased from to, In other Mediterranean mountains other athors have also seen that the main change in ladn cover during the last decades is a substitution of open forest for closed forests. and this is favoring in many areas a secondary succession in which more shade tolerant species such as silver fir are colonizing the understory of the pine forest that are currently dominant
- But one could argue that this is, let’s say, a fixed picture, a description of the situation right now. But stll, and despite the importance of land-use changes, climate will exert an influence on the growth and mortality of tree species. Traditionally, it was assumed that the behavior of species along a gradient of temperatures was this one, and one species was substituted by others when its growth and survival started to decline due to warmer conditions. However, Loehle argued that for many species the response is like this one, and species substitution occurs when a species from a southern or lower origin outcompetes the species coming from subalpine areas. This has very important consequences, cause most envelope or species distribution models just assume the first case, and thus lead to predictions of sharp decline in the distribution of some species, and even to extinctions that can be exaggerated as compared
- But one could argue that this is, let’s say, a fixed picture, a description of the situation right now. But stll, and despite the importance of land-use changes, climate will exert an influence on the growth and mortality of tree species. Traditionally, it was assumed that the behavior of species along a gradient of temperatures was this one, and one species was substituted by others when its growth and survival started to decline due to warmer conditions. However, Loehle argued that for many species the response is like this one, and species substitution occurs when a species from a southern or lower origin outcompetes the species coming from subalpine areas. This has very important consequences, cause most envelope or species distribution models just assume the first case, and thus lead to predictions of sharp decline in the distribution of some species, and even to extinctions that can be exaggerated as compared
- Ademas Lorena ha visto que esto es asi Y paloma tambien En este contexto lo que habra es competicion
- Ademas Lorena ha visto que esto es asi Y paloma tambien En este contexto lo que habra es competicion
- With the predictions of increase in temperatures associated to global warming, many models and studies forecast upward displacement of species, so that species from the montane belt would spread into the subalpine belt. However, there are factors other than climate that canalso have a significant effect, and that complicate the whole process a little For instance, we know now that the upper and lower limits of a species distribution are commonly not controlled by the same factor, and while temperature usually restricts the upper limit, drought or competition can drive the lower one, depending on the species and the area In this context, we should not expect subalpine species to decline, and thus the position of the ecptone would be ultimately driven by the interacions between montane species and subalpien species under the new scenario Also, it is important to take into account that factors acting at different spatial scales can be important for the future of these forests So, what we got with these considerations is a high level of uncertainty
- But instead of just doing the simulations, we used the model to assess the importance of two processes that were probably not well understood yet: individual.-based (the fate of every single tree in the plot is simulated independently) spatially-explict (so the spatial interactions between neighboring trees are taken into account). That made SORTIE and ideal option for our objectives
- But we were also interested in assessing the sensitivity to differences in juvenile growth, so we also tested different scenarios. For the first stand, as P. sylvestris is expected to be favored by the expected increase in temperatures (based on literature and our known results), we tested the effects of an increase in growth of 10, 25 and 50% In the case of silver fir, there is much more uncertainty on how will this species behave with future climate. On one hand, it could be favored by the increase in temreatures, but, on the other hand, it could suffer from drought due to its sensitivity to this parameter. Consequently, we tested three scenarios in which growth was enhanced by and three more in which it was reduced by… We did not vary gorwth of Pinus uncinata because our results fdrom previous studies suggest a scarca sensitivity of this species to changes in temperatures
- When we made juvenile growth vary we observed different effects dpending on the stand. In the case of the pine stand, we observed that an increase in juvenile growth of Pinus sylvestris resulted in differences in the final stand composition, wheras not in the total basal area. However, in the case of pine-fir stands, even an increase of 50% in abies growth did not result in significant differences in final stand composition.
- When we made juvenile growth vary we observed different effects dpending on the stand. In the case of the pine stand, we observed that an increase in juvenile growth of Pinus sylvestris resulted in differences in the final stand composition, wheras not in the total basal area. However, in the case of pine-fir stands, even an increase of 50% in abies growth did not result in significant differences in final stand composition.