Primer on Ecosystem Water Balances Lecture 2 Ecohydrology

Water Balance • Inputs (cross-boundary flows) – Rainfall • Stochastic in interval, intensity and duration – Runin/Groundwater? • Outputs – Evapo-transpiration – Surface runoff – Infiltration • Key internal stores/processes – – – Soil moisture Interception Stomatal regulation Sap-flow rates Boundary layer conductance Capillary wicking

Water Balance • P = ET + R + D + ΔS – P – precipitation – ET – evapotranspiration • Contains interception (I), surface evaporation (E) and plant transpiration (T) – R – runoff – D – recharge to groundwater – ΔS – change in internal storage (soil water) • Quantities on the RHS are functions of each other – ET, R and D are a function of ΔS, and vice versa – Plants mediate all of the relationships

Soil-Plant-Atmosphere Continuum • ET through a chain of resistances in series – – – Boundary layer (canopy architecture) Leaf resistance (stomatal dynamics) Xylem resistances (sapwood area, conductivity) Root resistances (water entry and transport) Soil (matrix resistance) • Individual plasticity and changes in composition (i. e. , species level variability) affect each process at different time scales. Creates important feedbacks between the ecosystem and it’s resistance properties

Figuratively • Driven by a vapor pressure deficit between the soil and atmosphere and net radiation • Soil evaporation is a minor (~5%) portion of total ecosystem water use Atmospheric Demand Boundary layer Leaf control – Most water passes through plant stomata even in wet areas with low canopy cover Stem control • Evolutionary control on resistances and response to stresses Root control – For example, cavitation of the SPAC in the xylen Soil resistance Soil Moisture

The SPAC (soil-plant-atmosphere continuum) Yw (atmosphere) -95 MPa Yw (small branch) -0. 8 MPa Yw (stem) -0. 6 MPa Yw(soil) -0. 1 MPa Yw (root) -0. 5 MPa

How Does Water Get to the Leaf? Water is PULLED, not pumped. Water within the whole plant forms a continuous network of liquid columns from the film of water around soil particles to absorbing surfaces of roots to the evaporating surfaces of leaves. It is hydraulically connected.

Radiation, Wind - Vapor Pressure Deficit Rainfall + - + + Boundary, + Leaf, Stem, Soil Conductance Intercepted Water - + Primary Production - + Infiltration Soil Moisture + - Runoff

Vapor Deficit (Dm = es – ea) • Distance between actual conditions and saturation line – Greater distance = larger evaporative potential • Slope of this line (s) is a term in ET prediction equations – Usually measured in mbar/°C

Key Regulatory Processes • Interception – I = S + a*t – Interception (I) is canopy storage (S) plus rain event evaporation rate * time • Mean I ~ 20% of P – Strong function of forest structure • Annual I in forests > crops and grasses because of seasonal effects Zhang et al. (1999) EF Plot 4 GS- Plot 4

Key Regulatory Process - ET • Penman-Monteith Equation ENERGY AERODYNAMIC • Ω is a decoupling coefficient (energy vs. aerodynamic terms; 0 -1) – Vegetation controls this; higher in forests, lower in grasslands • s is the slope of saturation vapor pressure curve, γ is the psychrometric constant, ε is s/γ, Rn is net radiation, G is ground heat flux, ρ is the density of air, Cp is the specific heat capacity of air, Dm is the vapor pressure deficit, rs is the surface resistance and ra is the aerodynamic resistance

ET and Surface Resistance • ra is the resistance of the air to ET, controlled by wind speed and surface roughness • rs is resistance for vapor flow through the plant or from the bare soil surface • Vegetation effects ET (indexed to PET) from a dry canopy as a function of surface resistance (rs) at constant aerodynamic resistance (ra) – Leaf area index (LAI) – Stomatal conductance – Water status (wilting)

Albedo Effects • Species type affects ecosystem energy budget Net-radiative forcing of boreal forests following fire is dominated by albedo effects (Randerson et al 2006)

Stomata – “Ecohydrologic Engineers” • Air openings, mostly on leaf under-side – 1% of leaf area, but ~ 60, 000 cm-2 – Function to acquire CO 2 from the air – Open and close diurnally, and in response to soil H 2 O tension • React to wilting (loss of leaf water) Guard cells (shape change with turgor pressure)

Stomatal Conductance • Rate of CO 2 (H 2 O) exchange with air (mmol m-2 s-1)

Specific Variation • Conductance properties vary by species – Feedbacks between water use and succession – Comparative climate change vulnerability

For est So il Rooting Depth

Rooting Depth Effects Surface 2 months later

Hydraulic Redistribution • Roots equilibrate soil moisture (even when stomata are closed) – Cohesion-tension theory, where tension is exerted by potential gradients, and water forms a continuous “ribbon” because of cohesion forces • Water transport from well watered locations to dry locations – Local spatial variation in irrigation – Deep water access via tap-roots (“hydraulic lifting”) • Facilitation effects (deep-rooted plants supplying shallow moisture) Richards and Caldwell (1987)

Soil Moisture Dynamics: Consumption and Hydraulic Redistribution Field Capacity Wilting Point

Watching ET Occur • Across depths, integrate to quantify Total Soil Moisture (TSM) • Assess 24 -hr change in TSM, due to: – ET – Hydraulic lift

A Simple Catchment Water Balance • Consider the net effects of the various water balance components (esp. ET) – At long time scales (e. g. , > 1 year) and large spatial scales (so G is ~ 0): P = R + ET • The Budyko Curve – Divides the world into “water limited” and “energy limited” systems – Dry conditions: when Eo: P → ∞, ET: P → 1 and R: P → 0 – Wet conditions: when Eo: P → 0 ET → Eo

Budyko Curve

Evidence for One Feedback – Forest Cover Affects Stream Flow CO 2 Jackson et al. (2005) H 2 O 1 : 300

Moreover – Species Matter

Evidence for Another Feedback – Composition Effects on Water Balances • Halophytic salt cedar • Pataki et al. (2005) studied stomatal invades SW riparian conductance for both species in response areas to increased salinity • Displaces cottonwoods, de-waters riparian areas Pataki et al. (2005)

Adding Processes (and Feedbacks) • Organic matter affects soil moisture dynamics • Vegetation affects soil depth (erosion rates) • Soil moisture affects nutrient mineralization (esp. N) • Inter- and intra-specific interactions (facilitation, inhibition)

Coupled Equations to Describe Plant. Water Relations in a Forest • Peter Eagleson (1978 a -g) – 14 parameter model links rain to production via soil moisture – Posits three “optimality criteria” at different scales

In Equation Form (yikes)

Eagleson’s Optimality Hypothesis #1 • Vegetation canopy density will equilibrate with climate and soil parameters to minimize water stress (= maximize soil moisture) – Idea of an equilibrium is reasonable • “Growth-stress” trade-off • Stress not explicitly included in the model – Evidence is contrary to maximizing soil moisture • Communities self-organize to maximize productivity subject to risks of overusing water between storms – Tillman’s resource limitation hypothesis predicts excess capacity in a limiting resource will be USED

Optimality Criteria #2 • Over successional time, plant interactions with repeated drought will yield a community with an optimal transpiration efficiency (again maximizing soil moisture, because that is how a plant community buffers drought stress) – Actually impossible (or nonsense at least) • A community that uses less water will replace a community that uses more (contradicts all of successional dynamics) • The equilibrium occurs at “zero photosynthesis” because that is the state at which transpiration loss is minimized. – While the central prediction is probably in error, the basic idea of some non-obvious equilibrium emerging from the negotiation between climate, plants and soils is an idea that others have built on

Optimality Criteria #3 • Plant-soil co-evolution occurs in response to slow moving optimality – Changes in soil permeability and percolation attributes – Assumes no change in species transpiration efficiencies – First inkling that, embedded in the collective control of plant communities on abiotic state variables has evolutionary implications • Selection based on group criteria • Constraints of efficiency • Unlikely to hold in Eagleson’s formulation (presumes stasis in environmental drivers over deep time, which is inconsistent with climate dynamics), but as a prompt to think more deeply about plant-water relations, it is a huge milestone permeability Pore “disconnectedness”

Simplifying Complex Dynamics • Emergent behavior from reciprocal adjustments between soil moisture and ecosystem “resistances” (water use, biomass growth) in response to climate (rainfall) • Read Porporato et al. (2004)

Next Time… • Arid land ecohydrology