1/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
2/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
3/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
4/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
5/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
6/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
7/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
8/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
9/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND...
10/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
11/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
12/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
13/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
14/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
15/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
16/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
17/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
18/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
19/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
20/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
21/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AN...
Upcoming SlideShare
Loading in …5
×

Modelling Vegetation Patterns in Semiarid Environments

852 views

Published on

Talk given during the meeting "Four decades of progress in monitoring and modeling of processes in the soil-plant-atmosphere system: applications and challenges" – 19-20 June 2013 Napoli

Published in: Environment, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
852
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
9
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Modelling Vegetation Patterns in Semiarid Environments

  1. 1. 1/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliSalvatore Manfreda1, Teresa Pizzolla1, Kelly K. Caylor21) University of Basilicata, Italy.2) Princeton University, USA.Modelling Vegetation Patterns in SemiaridEnvironmentse-mail: salvatore.manfreda@unibas.it
  2. 2. 2/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliSpatial Pattern of VegetationLandscape ecology emphasizes the interaction between spatialpattern and ecological process (movement of plants & animals;edge/interior effects, isolation) that is the causes and consequencesof spatial heterogeneity across a range of scales.“Two fundamental and interconnectedthemes in ecology are the developmentand maintenance of spatial and temporalpattern, and the consequences of thatpattern for the dynamics of populationsand ecosystems.”– Simon A. Levin, 1992(Photo by Yann Arthus-Bertrand)
  3. 3. 3/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliMotivationGlobal precipitation projections forDecember, January, and February (topmap) and June, July, and August (bottommap.) Blue and green areas are projectedto experience increases in precipitation bythe end of the century, while yellow andpink areas are projected to experiencedecreases.Source: Christensen et al. (2007)How climate change will impacton vegetation patterns?How this will modify waterresources?
  4. 4. 4/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliThe Study CaseSevilleta LTER(Caylor et al., AWR 2005)Upper Rio SaladoCatron County, NMCibola National ForestBasin Area: 681 km2Mean Annual Rainfall: 218±84 mm
  5. 5. 5/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 Napoli! Couple patterns of vegetation, soil, and climate to generate patterns ofsteady state water balance and soil moisture distribution within the basin! Use existing stochastic model of soil moisture:( ) ( )stsdtdsnZr χϕ −= ,Input is a poisson process ofrainfall events with a characteristicdistribution of storm depths(Rodriguez-Iturbe et al., 1999; Laioet al., 2001; Manfreda et al, 2010)Losses are determined according to a lossfunction that includesevaporation, transpiration, and leakage00.511.522.533.50 shsw s* sfc 1χ(s)cm/dEmaxEvapSoil Water Balance
  6. 6. 6/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliBasin Water Stress0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.900.20.40.60.81xθʹ′1.00.0⎪⎩⎪⎨⎧<⎟⎟⎠⎞⎜⎜⎝⎛=otherwisekTTifkTTseassnseasss1***/1ζζθts(t)Duration of the growing season, TseasξDuration of an excursionbelow ξ(Porporato et al., AWR – 2001)Dynamic water stress definedas a function of frequency ofcrossing, number of crossing,mean time of crossing, etc.
  7. 7. 7/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliPotentialevapotranspirationRn = Ra 1−α( )−εsσTs4+εaσTa4RdirRdif RemαRdirRrifRaatmospheretargetRa =GSCd2 cos θ( )dωω1ω2∫Net solar radiation
  8. 8. 8/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliDWS Treekmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.20.40.60.81DWS Shrubkmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.10.20.30.4DWS Grasskmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.20.40.60.81DWS Treekmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.20.40.60.81DWS Shrubkmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.10.20.30.40.5DWS Grasskmkm1 10 20 30 40 50 60 70 80 90 10011020304050607080 00.20.40.60.81T! s! = T!!s! −T! s +1ν s−1ν s!+γ1ν u!−T! u!!!duθ′ =T!"#! −T! s!T!"#!θDynamic Water StressDynamic water stress computedincluding initial conditionsThe mean first passage time (indays) of the stochastic processbetween s0 (initial condition) and<s>Basin morphology modifies dynamicwater stress allowing the existence ofsome species.
  9. 9. 9/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliDynamics of Organization within RiverNetworksInitialConditionNeighbor model:Interactions can occur between all 8 neighborsNetwork model:Interactions constrained by flow path – onlydownstream neighbors can be replaced21Cells replace neighbor pixels if it lowersthe local amount of water stress with aprobability pHow well do each of these interactionsrepresent the observed distribution of waterstress?(Caylor et al., GRL 2004)⎟⎟⎠⎞⎜⎜⎝⎛+−=2111θθθpCell becomes bare when θ is 1 for allvegetation types
  10. 10. 10/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliNeighbor Model0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.900.20.40.60.81xθʹ′Network modelActualSteady-State ConditionModel calibration
  11. 11. 11/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliVegetation Pattern obtained including theEffects of Morphology on Solar RadiationThe hypothesis of feasible optimality is explored using four cellular automataapproaches.The initial random vegetation mosaic is modified through the iteration of localinteractions that occur between adjacent locations.These interactions are defined such that the replacement probabilities (P )adopted combine both the dynamic water stress (𝜃′ ) and the planttranspiration (T ). The schemes proposed are the following:
  12. 12. 12/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 Napoli(Manfreda et al., Procedia Environ. Sci. 2013)Vegetation Pattern obtained including theEffects of Morphology on Solar RadiationAmong all considered cases,the second and thirdschemes (see Fig. 5 B and C)provide spatial patterns thatreplicate more closely theactual distribution ofvegetation in the Rio Saladobasin.
  13. 13. 13/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliVegetation Pattern obtained including theEffects of Morphology on Solar RadiationInitialConditionCells replace neighbor pixels if itlowers the local amount of waterstress with a probability p⎟⎟⎠⎞⎜⎜⎝⎛+⎟⎟⎠⎞⎜⎜⎝⎛+−=2112111TTTpθθθVegetation strategy is:•  to minimize of stress•  and maximize transpiration
  14. 14. 14/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliEcohydrological Model: Simulation Results(Hurvitz, 2002)The proposed model has been used to predict 256 scenariodefined changing both the mean rainfall rate (λ) and the meanrainfall depth (α).Increasing mean annual rainfall200 400 600 800 1000 12001002003004005006007008009001000(A) (B) (C)Bare soilGrassShrubTreeMaps are obtained using the measured rainfall rate (λ = 0.284 day−1) and changing theparameter α that assumes the following values: 0.474cm (A), 0.517cm (B), 0.631cm (C).
  15. 15. 15/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliShannon’s Entropy – Diversity Index0.40.50.60.70.20.250.30.350.40.450.500.511.5λαShannonsentropySHDI = − pi*ln pi( )i=1m∑SHDI increases as the number ofdifferent patch types increasesand/or the proportional distributionof area among patch typesbecomes more comparablepi = proportion of landscapeoccupied by the class i.The Shannon’s evenness index (SHDI) represents a well-known landscapemetric that accounts for both abundance and evenness of species in thelandscape. This index has the same expression of the informational entropyand is defined by(Manfreda and Caylor, Water 2013)
  16. 16. 16/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliSame Rainfall with Different Rate or MeanDepth…changes in α provides sharper modifications of landscape.
  17. 17. 17/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliSame Rainfall with Different Rate or MeanDepthLandscapeDiversityAnnual rainfallChanging α Changing λ
  18. 18. 18/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliResults on a Mediterranean AreaAridity Index (De Martonne)Basin Subasins(Manfreda, Ann Arid Zone 2013)
  19. 19. 19/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliConclusionsThe main outcomes of the present work can be summarized in following points:i)  The algorithm that seems to explain the actual structure of vegetationobserved in the Upper Rio Salado basin is the one that tend to minimizedynamic water stress and maximize vegetation water use;ii)  The landscape analyses, based on the modeling applications, show thatreduction of landscape diversity (described by the Shannon’s Index) mayoccur rapidly for small changes in the rainfall characteristics;iii)  These changes are exacerbated when rainfall modifications are due toreduction in the mean rainfall depth;iv)  The impact of climate change on the vegetation pattern depends on thevulnerability of a system with respect to the expected changes.
  20. 20. 20/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliReferences! Manfreda, S., K.K. Caylor, On The Vulnerability of Water Limited Ecosystems toClimate Change, Water, 5, 819-833; doi:10.3390/w5020819, 2013.! Manfreda, S., T. Pizzolla, K.K. Caylor, Modeling Vegetation Patterns in SemiaridEnvironment, Procedia Environmental Science, 2013.! Pizzolla, T., S. Manfreda, K.K. Caylor, M. Fiorentino, Il ruolo dell’esposizione e dellapendenza dei versanti sullo stress idrico della vegetazione, Atti del Convegno diidraulica e Costruzioni Idrauliche - IDRA2012, 9-14 settembre 2012, Brescia, 2012.! Acampora, A., T. Pizzolla, S. Manfreda, Effects of Morphology on Solar Radiation andEvapotranspiration, 3rd International Meeting on Meteorology and Climatology of theMediterranean - IMCM 2011.! Acampora, A., A. Sole, M. T. Carone, T. Simoniello, S. Manfreda, Le Metriche delPaesaggio come Strumento di Analisi del Territorio, in Informatica e PianificazioneUrbana e Territoriale a cura di Las Casas G., Pontrandolfi P., Murgante B., Atti dellaSesta Conferenza Nazionale INPUT 2010, Libria, pp 221-231, vol.1, 2010.! Manfreda, S., Ecohydrology: a New Interdisciplinary Approach to Investigate onClimate-Soil-Vegetation Interactions, Annals of Arid Zones, 48 (3 & 4), 219-228,2009.
  21. 21. 21/21FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES – 19-20 June 2013 NapoliThanks for your attention…

×