REPORT FROM THE 2009 GILA SCIENCE FORUM PANEL

Tasking The general purposes of the 2009 Gila Science Forum were to identify, discuss, and recommend (1) ways of determining the potential effects of flow modification on aquatic and riparian resources of the Gila River (including risks and uncertainty), and (2) how information gleaned from such efforts might be integrated to provide an ecosystem-based assessment of the effects. Four Specific Questions: 1.In broad and general terms, what are the potential effects of flow modification on the biological, hydrological, and geomorphological attributes of southwestern rivers? 2.What tools and methods are available to assess the biological, hydrological, and geomorphological responses of a river to human-induced flow modification? What are the advantages and disadvantages, risks and uncertainties associated with each tool and method? 3.How might information obtained from biological, hydrological, and geomorphological studies be best assimilated and integrated to understand the effects of flow modification on ecosystem function? 4.Recognizing that time and resources are limited (to about one year and $1 million), what are the most pressing tasks (including, potentially, filling information gaps) that we need to address in order to assess the effects of modified flows on aquatic resources of the Gila River?

Forum Panelists Dr. William Fagan, Ecology, University of Maryland Dr. Keith Gido, Aquatic Ecology, Kansas State University Dr. Robert Glass, Hydrology, Sandia National Laboratory Dr. Paul Marsh, Aquatic Ecology, Marsh & Associates Dr. Waite Osterkamp, Geomorphology, U.S. Geological Survey Dr. Ron Ryel, Biostatistics, Utah State University Panel struggled with the general nature of the questions. The 2006 Science Forum provided a good foundation to address these general questions. Included a Plan of Action to facilitate progress towards goals

Potential effects of Flow modification We know from the work of many in this field what the critical influences of flow modification may be, e.g., Bunn and Arthington (2002)…

* Adapted from Bunn & Arthington (2002) Environmental Management 30, Invasion of non-native species is facilitated by alteration of the temporal and spatial structure of flow Principle 4 Time Discharge Temporal and Spatial Structure of Flow is Critical channel form habitat complexity patch disturbance biotic diversity Principle 1 drought Temporal and spatial structure of flow determines the physical habitat, water quality and ecosystem composition & diversity floods Longitudinal and Lateral connectivity is a critical aspect of temporal and spatial structure and determined by flow Principle 2 access to floodplains continuity discontinuity triggers predictability Principle 3 spates variability dispersal stable baseflows Species have evolved life history strategies based on the temporal and spatial structure of flow Aquatic Terrestrial seasonality reproductive triggers Space

Potential effects of Flow modification We know from the work of many in this field what the critical influences of flow modification may be, e.g., Bunn and Arthington (2002)… But the devil may be in the details… such as the location, timing and magnitude of the modification Flow modification can be good or bad depending on the system measures (economic, biodiversity, etc) and some modifications can offset the influence of others. Example: ditch irrigation channels increasing health of riparian vegetation within valley leading to better habitat for birds (listed and nearly listed species) but poorer habitat for fish (two listed species).

Tools and methods? There are no predictive tools or methods to assess reliably and quantitatively the biological responses of flow modification ahead of time. (this goes for hydrologic and geomorphic tools too). Huge uncertainty.

Model Detail: More can be less Model Detail Amount Coverage of Model Parameter Space 1.Recognize the tradeoff 2.Characterize the uncertainty with every model 3.Buy detail when and where it’s needed Understanding Chance of Error Cost Direct and indirect Measurements of system state (river flow, wetted area, depth, groundwater recharge & outflow, level throughout landscape, water quality, topography, vegetatative structure and composition of riparian zone and watershed, etc.) Modeling (conceptual, mathematical) of system state (variables same as above) Experiments that combine Measurements and Modeling Quantifying Uncertainty? Applies to both measurements and modeling and Experiments: Assumptions, bias, spatial and temporal coverage, etc. Focus on determining Policy Choice that is Robust to Uncertainty Assessment approaches for ecosystem response

Tools and methods? There are no predictive tools or methods to assess reliably and quantitatively the biological responses of flow modification ahead of time. (this goes for hydrologic and geomorphic tools too). Huge uncertainty. Select the best tools based on questions to be answered, funding, access to sites, etc. (requires details of flow modification) Use the best models but remember they may not be predictive of details Then MONITOR and adjust as you go: Adaptive Management

Plan of Action Systems Framework for Decision Making Aspiration: find an acceptable balance within the set of stakeholder values that also meets various legal constraints Requires definition of possible flow modifications Requires definition of criteria that allow valuation of “benefits”, “costs”, “adverse impacts” Rank alternative flow modifications or combinations of flow modifications, land use modifications, etc (call this a “policy”) Use uncertainty in ranking to drive additional studies (a decision!)

Aspirations Define Analysis Evaluate Performance Define and Evaluate Alternatives Define Conceptual Model Satisfactory? Done Action A Performance Requirement Action B Performance Requirement Decision to refine the model Can be evaluated on the same Basis as other actions Model uncertainty permits distinctions Action A Performance Requirement Action B Performance Requirement Model uncertainty obscures important distinctions, and reducing uncertainty has value Systems Framework with Spiral Development

Conceptual Model of Interdependencies There is no general-purpose model for the task at hand: Managing an “socioeconomic-agro-ecosystem” under human pressure with always unforeseen and unintended consequences of human action. A model describes a system for a purpose Interdependency modeling forces assimilation and integration to be concise Model application within Systems Framework allows identification of critical areas where funds should be focused System What to we care about? What can we do? Additional structure and details added as needed Interdependency Model

Example starting point Figure 3.2 of the Integrated Research Plan of the US Long Term Ecological Research program (USLTER 2007)

Detailed Component modeling as needed Model constructed with a range of stakeholders to explore interplay between water extraction and diverse stakeholder values in Gila River watershed (Sun et al. 2008)

Aspirations Define Analysis Evaluate Performance Define and Evaluate Alternatives Define Conceptual Model Satisfactory? Done Action A Performance Requirement Action B Performance Requirement Decision to refine the model Can be evaluated on the same Basis as other actions Model uncertainty permits distinctions Action A Performance Requirement Action B Performance Requirement Model uncertainty obscures important distinctions, and reducing uncertainty has value Analysis and Evaluation

Aspirations Define Analysis Evaluate Performance Define and Evaluate Alternatives Define Conceptual Model Satisfactory? Done Action A Performance Requirement Action B Performance Requirement Decision to refine the model Can be evaluated on the same Basis as other actions Model uncertainty permits distinctions Action A Performance Requirement Action B Performance Requirement Model uncertainty obscures important distinctions, and reducing uncertainty has value 1 year – two cycles of spiral application

Step 1) Start with as full a set as possible of stakeholder values, legal constraints and possible water management policies. These would be defined before the start of the modeling effort and conceptualized during this first step. (month 1) Step 2) Configure the overall preliminary conceptual model that connects stakeholder values to water management policies. (month 1) Step 3) Refine sub-components of overall model in critical areas as needed. Make use of as much available information as can be assimilated during the period including both process-level understanding and specific data from the Gila or other similar watersheds. Examples of specific types of information for hydrologic and ecosystem components that could be needed for an appropriate socio-economic- ecosystem conceptual model is listed in Table 1. (months 2-3) Step 4) Define and accomplish analysis that considers a matrix of policy options for a baseline set of model parameters, evaluates the ability of the system to simultaneously satisfy diverse stakeholder values, and ranks the policy options based on that ability. Repeat the analysis for a range of alternatives that include model uncertainty and parameter uncertainty. Evaluate the analyses with regard to the ability to rank policies robustly with respect to this uncertainty. (months 4-5) Step 5) Evaluate the sufficiency of the analysis. (month 6) Step 6) Repeat steps 1-5. Include additional data as necessary. (months 7 through 12)

Suggested Implementation Stakeholders Experts Systems team (where most of the work is done)