Ecohydrology Fall 2015 Selforganized patterning http wwwatmosalbanyedu student gareth ammahtml Compics International Inc Arid lands Tiger Sahel Sub s urface flow wetlands ID: 309887 Download Presentation
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Presentation on theme: "Patterned Landscapes"— Presentation transcript
Slide1
Patterned Landscapes
EcohydrologyFall 2015Slide2
Self-organized patterning
http://
www.atmos.albany.edu
/student/
gareth
/amma.html
©
Compics International Inc.
Arid lands: Tiger Sahel
Sub-surface flow wetlands:
Surface flow wetlands:
Ocean: reefsSlide3
What are patterned landscapes?
The emergence of spatial pattern in ecosystems from the action of local ecological interactions (self-organization)Order emerges from disorder via the assembly of small scale interactions (emergent property)Can occur at multiple scales
We’re interested in ecosystem scale
Math applies to attributes individual organisms (spots, fingerprints, eye-patterns), ecosystems, chemical reactions, interstellar reactions
https://
www.youtube.com/watch?v=u-mEjfBaYks Slide4
Underlying Mechanisms
Activator-inhibitor principleA system component “generates” itself via some autocatalytic action (self-reinforcement)Acts at a local scaleAt the same time, this self-generation inhibits growth at a larger scale
Production of toxins, exhaustion of a critical resource, competitive effectsSlide5
Patterned Landscapes and Regime Shifts
Rietkerk et al. (2009)
ScienceSlide6
Engineering the Planet (Gaia)
Photosynthetic
Plants
Atmospheric
Oxygen
+
-
Heterotrophy
+
-Slide7
Activator-Inhibitor
Activators catalyze themselvesSlow diffusion prevents rapid expansion, but creates strong local positive feedbacks
Plants in the Gaia system
Inhibitors result from that action
Rapid diffusion allows the inhibitory effect to be felt at distance
Distal negative feedbacksOxygen in the Gaia systemRietkerk and van de Koppel (2008)TREESlide8
Scale Dependent Feedbacks
Local positive feedbacks catalyze dispersal over short distancesInhibition occurs over longer rangeAutocorrelation as an indicator
Rietkerk and van de Koppel (2008)
TREESlide9
Simulating Scale-Dependent Feedbacks
Random initial conditionsX-axis increases the strength of the local positive feedbackY-axis decreases the scale of the distal negative feedbackSlide10
Reaction – Diffusion Simulations
http
://mrob.com/pub/comp/xmorphia/index.html
Two diffusing reagents (U and V) react in a control space (U + 2V → 3V and
V → P (inert)Parameters control:Diffusion (Du and Dv) rate (with concentration gradient)Replenishment of U and utilization of V via “F” and “k”Slide11
Recent Example – Patterned Peatlands
Striking spatial surface patterning has been a subject of study for 30 years.10-100 m
2
patches of hummocks (thicker peat) and hollows (thinner peat)
Typically radial/maze on flat ground, ribbons orthogonal to flow on sloped ground
Eppinga et al. (2008)EcosystemsSlide12
Diagnostic Properties of Patterned Landscapes
Evidence of bi-stability
Evidence of scale dependent feedbacks
Rietkerk
and van de Koppel (2008)
TREE
Eppinga
et al. (2008)
EcosystemsSlide13
Evapotranspiration mechanism
Nutrients (TP)
Nutrients (TP)
Hollow
Hummock
g
round water flow:
ET pump
Precipitation
ET
PeatSlide14
Mechanism for Bog Patterning
Nutrient accumulation in higher ground driven by accelerated evapotranspiration and higher productivity
Water flows towards hummocks (either radially in flat landscapes or along slopes in sloped landscapes)
“Mines” nutrients from distal locations, making them less productive, and therefore less likely to maintain a positive carbon balance at high elevationSlide15
Tidal Mud Flats
Origins of ephemeral tidal mudflat patternsTop-down control of pattern lossSlide16
Regular Pattern on Mud Flats
Hummock and hollow morphologyRegular, Transient
Hummocks contain large biomass of diatoms
EPS cohesion of sediments
Hollows have low biomassWeak cohesion
Biogeomorphic patternSlide17
Models of Pattern
Bifurcation (alternative stable states) in response to erosion rates and photosynthesisSlide18
Measurements of Pattern
Significant negative spatial autocorrelation at pattern “wavelength”Orientation mattersSlide19
Impacts of Pattern
Pattern mudflats are more productive than homogenous mudflats
Trophic impacts
Patterned mudflats
hold the sediment more effectively than homogeneous mudflatsWater quality impactsSlide20
Trophic Interactions
Loss of pattern over the summerSlide21
Sediment Processes Impacted by Grazers
Increase in benthic invertebrate grazers over summer leads to loss of diatomsLoss of diatoms leads to loss of pattern
Observations over Time
Experimental ManipulationSlide22
Persistence and Loss of Pattern in the EvergladesSlide23
What Drives Local Variation in “States”?
Watts et al. (2010)Slide24
Predictions
Bi-modal distribution of soil elevationScale-dependent auto-correlationAnisotropic because the landscape is patterned in the direction of flow
Changes with hydrologic modificationSlide25
Bi-Modality is a Keystone Feature of the Best Conserved Parts of the Landscape
(and the loss of this feature PRECEDES changes in vegetation!)
Bimodal (cm)
A-priori
(cm)
Stabilized Flow06.7Drained0
4.2Conserved 117.4
14.1Conserved 220.219.1
Transition 1
24.724.1
Transition 226.1
12.2Impounded
013.9
ENP
16.9
14.2Slide26
Scale-Dependent Feedbacks are Present, Anisotropic, and can DegradeSlide27
What Are the Mechanisms?
Discriminating amongst causes and consequences is hard (correlation ≠ causation)So how to proceed?Slide28
Model Experiments – Turn On and Turn Off MechanismsSlide29
Rich Pattern VarietySlide30
Everglades Ridge-Slough Landscape
Important features
Shallow regional slope (3 cm km
-1
)
Elevated ridges, lower sloughs (Δh ~ 25 cm)Autogenic (i.e., not driven by limestone)Patches elongated with historical flow, sloughs are interconnectedRidges cover ca. 50% of area in conservedHydroperiod – R ~ 90%, S ~ 100%Regular patterning?Slide31
Patterning/Pattern
Loss in the Everglades
Parallel ridges and sloughs existed in an organized pattern, oriented parallel to the flow direction, on a slightly sloping peatland
Compartmentalization and water management have led to degraded landscape patterns
detrimental ecological effects (SCT, 2003)Historic FlowContemporary FlowSlide32
Mechanisms Matter
“Getting the water right” = understanding mechanisms of pattern genesisCompeting mechanisms all make predictions that “look” similar (elongated patches)
Alternative discriminant indicators?
Cheng et al., 2011
Lago
et al., 2010Larsen et al., 2011
Acharya et al., in prep
Velocity & Sediment
Soil TP
HydroperiodSlide33
Hypotheses for Landscape Formation
Sediment redistribution
(
Larsen et al., 2007; Larsen and Harvey, 2010,
2011
)Requires unobserved (and unlikely) velocitiesWavelength governed by local velocity dynamicsNutrient redistribution (Ross et al., 2006; Cheng et al., 2011)Requires unobserved hydraulic gradients in groundwaterWavelength controlled by lateral transport distances“Self-Organizing Canal” Hypothesis (Cohen et al., 2011)Feedback between pattern (as it relates to landscape flow routing), hydroperiod
and C accretionCritically, predicts the distal feedback is diffuse, acting weakly at any location…no characteristic wavelength
Potentially Useful IndicatorsPresence and magnitude of landscape characteristic wavelength
Distribution of patch sizes (power vs. exponential) Slide34
Spectral Analysis Reveals Scale Dependent Feedbacks in Regular Patterns
2D Fourier transform used to extract spectral information
Peaks in R-spectrum correspond to dominant wavelengthsSlide35
Evidence of Scale-Dependent Feedbacks in Regular
Patterns
DeBlauw
et al. 2007Slide36
Theory:
Fractal PatterningLocal facilitation, growth impeded by
global
constraints (e.g., finite water)
Patch sizes are power functions
with no characteristic wavelengthScanlon et al., 2007 (isotropic local contagion)Slide37
No periodicity (i.e.,
no characteristic wavelength)Patterning is scale-free (global not distal feedback)
Ridge-Slough Pattern
WCA3AN
Northern
WCA3AS
Central
WCA3ASCasey et al. in prepSlide38
Fractal Patch Size Distributions
Regular patterns yields exponential functions
Patch size truncated by distal feedbacks
Fractal patterns produce power functions
Local facilitation with diffuse constraints
IMPOUNDEDCONSERVEDDRAINEDYuan et al. in prepSlide39
Based on cellular automata model
(Scanlon et al. 2007)Scale-free (global) constraint on ridge expansionRidge prevalence controls landscape
discharge competence
Anisotropic local feedback
Invoked in ALL ridge-slough models
Mechanism? Simple Aperiodic ModelCasey et al. in prepSlide40
Scale Dependent Pattern Features: Elongation and Orientation
Length:Width
Eccentricity
Orientation
Solidity
Casey et al.
in prepSlide41
Summary:
Discriminating Mechanisms of Pattern GenesisThe ridge-slough landscape exhibits fractal
not
regular
patterningNo characteristic wavelength; power function distribution of lengths, widths and areasI
mplies weak distal feedbacks inconsistent with most proposed mechanismsOur scale-free model misses scale-dependenciesOrientation & elongation increase with patch sizeGetting the water right for the ridge-slough landscape means resolving the mechanismsSlide42
An Abiotic Example – Sorted Stones
Pattern emergence in polar and high alpine environmentsSelf-organized (or by the Yeti)
Formed by freeze-thaw cycles
Activator = freezing is preferential where stones are sparse; freezing displaces stones
Inhibitor = ice moves stones and concentrates them
Shapes configured by the orientation of the inhibitorHillslopes = stripesFlat – labyrinth or circularKessler and Werner (2003)ScienceSlide43
Underlying Mechanisms
Frost heave expands soil (horizontally and vertically)Stones creep towards “stone domains” while soil creeps towards “soil domain”Stones fall away from “stone domain” centers (making stone piles of standard size)
Wider stone domains are pushed more, and therefore get taller, and therefore spread
Stones can get pushed along a stone domain if they are constrained against radial expansionSlide44
Simulation (Cellular Automata)
Vary initial stone density (high to low)
Vary lateral slope (low to high)
Vary lateral confinement (low to high)
Confinement = do stones stay in a stone domain; high values increase lateral transport along stone domains and lower radial diffusion Slide45
Time-Series
Emergence of pattern from random initial conditionsScale 10 x 10 m
High confinement, low slope
There are physical 6 parameters in their modelSlide46
Self-Organization of Sand Dunes
Self-organized morphologyActivator = wind and friction
Inhibitor = height increases gravitation loss, and increases wind velocity
Star formation when there are seasonally adjusting windsSlide47
Self-Organization of River Channels
Activator = water flow and erosion; variable depositionInhibitor = sustained differences in erosion/deposition over-bend the river, causing catastrophic resetting (ox-bows)
Biota confer bank stability which constrains channel movementSlide48
Next Time…
Humid Land Ecohydrology