Designing a long-term monitoring program to support effective management of Minnesota lake resources

Designing a long-term monitoring program to support effective management of Minnesota lake resources January 2007 Problem Our climate is changing, and doing so rapidly Since 1900 global temperatures have increased 0.6° C, whereas during the previous 300-500 years global temperatures only fluctuated approximately 0.25° C (Hamilton and Johnson 2003) By 2100, we expect to see global temperatures rise on average 1° - 5.6° C In Minnesota, temperatures have increased by 0.44° C since 1900 (Hamilton and Johnson 2003) The consequences on aquatic resources have been measurable (Johnson and Stefan 2006; Magnuson et al 2000) and changes to systems are projected to increase at greater rates given current climate projections (Houghton et al 2001; McGinn 2002) Principal among these changes are shorter periods of ice duration and warmer water temperatures (Magnuson et al 2000, Johnson and Stefan 2006), and greater variability in precipitation and discharge (Johnson and Stefan 2006) It is expected that these factors will lead to measurable changes in water quality and lake productivity (Gitay et al 2001) In north temperate lakes, much work over the past decade has focused on modeling habitat changes and predicting the consequences for fish populations and communities (Stefan et al 1996, DeStasio et al 1996, Casselman 2002, Shuter et al 2002, Jackson and Mandrak 2002) In general, there is consensus among researchers that we will observe a poleward migration of species ranges due primarily to changes in thermal habitat (McGinn 2002) Minnesota populations of coldwater species such as Lake Trout and Cisco could experience the greatest reduction in inland lakes because of their narrow thermal and dissolved oxygen habitat requirements Stefan et al 1996 projected that northern Minnesota could see a 41% reduction in cold water habitat with a doubling of atmospheric CO2 concentrations The International Panel on Climate Change projects this doubling could easily occur by 2100 and perhaps sooner (IPCC 2001) Displacing coldwater species will initially be cool water species (e.g., walleye, yellow perch, and northern pike) and eventually warm water species (e.g., Largemouth bass, smallmouth bass, bluegill, and crappie) By extension, we can expect current coolwater fisheries to be increasingly dominated by warm water species Stefan et al (1996) expected that seasonal average epilimnetic water temperatures to increase by approximately 3° C with a doubling of CO2 concentrations With this increase, Casselman (2002) projected that recruitment of coolwater species will decline greater than 18x Conversely, Casselman (2002) predicted that recruitment of warmwater species would increase by approximately 15x Losses of fish biodiversity are projected to occur along with shifts in species assemblages (Jackson and Mandrak 2002) Typically, benefits for opportunistic species comes at the expense of intolerant ones through predation, competition, and habitat loss In Minnesota, a displacement of walleye by smallmouth bass and other warm water centrarchid species is currently being observed in Green Lake in Kandiyohi Co The decline of naturally reproducing walleye in this popular lake has ignited a controversy among anglers and managers regarding the potential cause of the walleye decline Currently, other confounding factors such as harvest regulations, the invasion of Eurasian watermilfoil, and changes in water quality cloud the picture (B Gilbertson, Spicer Fisheries Area Manager, pers comm.) Unfortunately, the lack of monitoring data on other lake functions in Green Lake and others forces managers to rely on anecdotal evidence for diagnosis of many management issues Not only is climate change affecting lake resources today and into the future, but other major drivers of change continue to alter fish populations and habitat statewide The cumulative effects of development, agricultural practices that are growing more intensive and extensive, and invasive non-native species continue to be significant threats to the integrity of fish communities and habitats in Minnesota High popularity of lakeshore, high demand for cropland to provide energy and food for a growing population, and a mobile society that is a vector of spread for nonnative species continues to contribute to declines in water quality and losses of fish habitat A call to action – Global climate change and increased development and agriculture represents a quiet crisis for natural resource managers Impacts are expected to occur slowly over time and managers risk infection by the insidious Shifting Baseline Syndrome (Pauly 1995) if they don’t posses historical data to fight this institutional disease The tenet of the shifting baseline syndrome paradigm is that without historical data, current and future generations lack understanding of the unimpaired state of the resource and a reference point for restoration (i.e., “the invisible present”; Magnuson et al 2006) A framework is needed that will unveil the invisible present and identify vulnerable habitats, and provide information for how to best protect the resiliency of fish populations and habitats such that we fulfill our mission of managing our lakes in a way that provides Minnesotan’s a sustainable quality of life We propose a long-term monitoring program that should provide such a framework Mission for a Long-term monitoring program for lakes: To monitor the condition of Minnesota lake habitats and fish populations using key lake ecosystem indicators that are most responsive to human and environmental stressors, and evaluate whether our division’s response to changes to lake habitats and fish populations is successful at delivering the ecosystem products and services important to the DNR’s mission About the mission of the long-term lake monitoring program: As societies work towards reducing greenhouse gas emissions and lowering the impact of development and agricultural practices; natural resource managers are faced with the large task of anticipating and adapting to changes to the ecosystems we manage Accordingly, DNR Fisheries is interested in pursuing a concerted effort towards preventive health care of lakes that identifies risk factors for lakes and takes action to protect the resiliency of lakes that are most vulnerable (Figure 1) Continual monitoring after management actions is a necessary check to ensure that management is working or to suggest new directions What separates this mission from other lake monitoring programs currently underway (Table 1) is a concentration of resources towards comprehensive monitoring of key lake health indicators that are sensitive to a host of stressors Due to budgetary constraints and the large number of lakes in the state, the DNR Fisheries Lake Survey Program has relied on highly variable and infrequent ‘snapshots’ of net catches of game fish to assess the condition of fish populations in lakes Even fewer resources have been available to adequately assess conditions of lake habitats such as aquatic plant cover, composition, and abundance Consequently, DNR Fisheries is currently in a weak position to address the future impacts of anthropogenic and environmental changes on fish populations and lake habitats Figure Conceptual framework for developing a preventive health care framework for Minnesota lakes using data collecting from long-term monitoring (source: UNEP 2006) Table Some current lake monitoring programs administered by Minnesota state agencies The following link lists monitoring programs compiled by the PCA (http://www.pca.state.mn.us/hot/pubs/climatesymposium-listofactivities.pdf) Activity Lake water quality monitoring http://www.pca.state.mn.us/water/lakeprogra ms.html#clean Aquatic plant monitoring State Wildlife Action Plan monitoring Shallow lake monitoring Fish/lake habitat monitoring - Fish populations - Aquatic plants - Water quality - Shoal substrates - Shoreline/watershed characterization Contaminants in fish Agency and contact person PCA Steve Heiskary Programs Citizen LakeMonitoring (CLMP); Lake Assessment Program (LAP); Regional and Trend Analysis; Clean Water Partnership Program DNR – Ecological Services Point-intercept Donna Perleberg surveys; Invasive Species Program DNR – Ecological Services State Wildlife Daren Carlson Action Plan DNR – Wildllife Shallow Lakes Nicole Hansel-Welch Program DNR – Fisheries Fisheries Lake Survey Program Data resources Data available online at Department of Health Pat McCann http://www.health.state.mn.us/divs/eh/fish/index.html Fish advisory program http://www.pca.state.mn.us/data/edaWater/index.cfm Microsoft Access database In planning Aquatic vegetation abundance, water quality, depth, waterfowl use http://www.dnr.state.mn.us/lakefind/surveys.html Proposed goals for a long-term lake monitoring program: Assess the past and present physical, chemical, and biological characteristics of selected study lakes, make inferences about the current health of habitats and fish in Minnesota lakes, and classify lakes according to their sensitivity to stressors Monitor changes in physical, chemical, and biological characteristics in selected study lakes, and forecast changes to lake indicators in response to stressors Publish annual reports on the current and potential future status of monitored lakes Evaluate whether management actions or policy decisions are maintaining high quality habitats and fish populations in the face of human and environmental stressors Use results from monitoring to inform future management and policy decisions Publish annual reports that evaluate whether management is achieving desired goals Justification To quickly and accurately anticipate or diagnose problems, implement solutions, and evaluate actions To illustrate this point, let us revisit the analogy to preventive health care Certain factors predispose people to a range of ailments or diseases Identifying who is at risk and monitoring basic bodily functions relevant to the ailment or disease with which they are at risk has prolonged or saved countless lives in developed parts of the world Similar health care questions could be asked of lakes For example, what types of lakes are most sensitive to degradation? Could a “habitat profile” of numerous indicators in a lake give us similar diagnostic information a blood profile can give a health care professional about a patient? Monitoring in the health care industry is a critical function to maintain healthy people Monitoring key indicators in lakes is a critical function to maintain healthy lakes Monitoring data is also needed to evaluate the effectiveness of statewide policy and whether it continues to fulfill the DNR’s mission Systematic and regular evaluation of the condition of habitats and fish populations across the state is necessary to evaluate the effectiveness of local, regional, and statewide policy Climate change, development, agriculture, and invasive species will continue to put new pressures on systems and policy that has worked in the past is not guaranteed to work in the future In other words, we must adapt early and often and have the structures in place that will allow us to so Coordination and collaboration to more efficiently assess the state of lake resources Currently, there are several formal and informal lake or fish monitoring programs carried out by multiple divisions within and outside of the DNR (Table 1) Each program monitors one to a few variables that give some insight into the “condition” of the systems they are monitoring The Minnesota Pollution Control Agency monitors water quality throughout the state and judges whether a lake is impaired based on its nutrient levels The shallow lakes program in the DNR Section of Wildlife Shallow Lakes Program monitors several variables to assess the condition of shallow lakes The lake survey program in the DNR Section of Fisheries monitors the condition of fisheries by assessing the abundance of game fish in lakes New efforts in the DNR Division of Ecological Services include monitoring sensitive fish and wildlife habitats in lakes The result of this uncoordinated work has been a loose collection of data scattered over numerous lakes across the state Drawing on the health care industry again this is akin to monitoring blood pressure on one patient, cholesterol on another, and blood sugar on yet another As a result, no program is seeing the full picture of the condition of their patient/lake, thus precluding accurate diagnoses or assessments of risk for future ailments Accordingly, coordination and collaboration will be critical to achieve the goals of this program To provide public educational opportunities Aside from gains in efficiency, a long-term monitoring program will provide a wealth of education and awareness tools and opportunities Probably the best and most relevant examples of what long-term monitoring has done to increase awareness of climate change is long-term lake ice records and what is famously known as the “hockey stick” graph that depicts global temperature changes over the last 1000 years (Figure 2; IPCC 2001) As a result of warming temperatures, long-term ice records show a slow but steady decline in the number of days that ice covers lakes across the entire northern hemisphere, (Figure 3; Magnuson et al 2000) These examples, among other alarming monitoring-based climate statistics are generating international interest and momentum to act Long-term monitoring can have local educational benefits as well The success story of Lake Christina in Douglas Co (Box 1; Figure 4) represents an example where the public was engaged in the process of this lake’s rehabilitation from a turbid fish-infested shallow lake with no aquatic plants to a fishless waterfowl-friendly basin with abundant aquatic plants Figure The “Hockey Stick” of climate change Graph represents departures from average temperature over the last 1000 years (source: IPCC 2001) Figure Long-term trends in ice on and ice off dates across the northern hemisphere (Source: Magnuson et al 2000) Figure Long-term trends in aquatic plant occurrence in Lake Christina, Douglas Co Box Case History of Lake Christina, Douglas Co Lake Christina is one Minnesota’s most important waterfowl staging lakes Aquatic plant abundance and waterfowl use have been monitored since the 1940s This lake has been actively managed to promote aquatic plants and waterfowl habitat since the 1960’s Monitoring expanded in 1985 in conjunction with a planned rotenone treatment Since that time, a suite of water chemistry parameters, zooplankton, and water clarity have been monitored annually throughout the open water season Much of this monitoring has been done by North Dakota State University and largely funded by the MN DNR and the Minnesota Waterfowl Association The data have demonstrated that management of this basin has restored water clarity, increased aquatic plant abundance and waterfowl use and served as a model for other shallow lake management projects in the state In addition, this monitoring has contributed to the basic understanding of shallow lake ecology and management in the International community of Shallow Lake Ecologists (Christina is included in the only Shallow Lake Ecology text book) Monitoring of Lake Christina specifically helped clarify the mechanisms involved in shifting a shallow lake from the turbid water condition to the clear water condition through biomanipulation Submerged Aquatic Plants - Lake Christina 1959 - 2005 100 90 70 60 50 40 30 20 Sago Pondwee d 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 10 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 Percent Occurrence 80 Chara To contribute to the National Fish Habitat Initiative (NFHI) for Midwestern Lakes An unprecedented coalition of anglers, conservation groups, scientists, state and federal agencies and industrial leaders forged the National Fish Habitat Action Plan (www.fishhabitat.org) The stated mission of the NFHI is to “protect, restore, and enhance the nation’s fish and aquatic communities through partnerships that foster fish habitat conservation and improve the quality of life for the American people.” This effort is focused on: • Supporting existing fish habitat partnerships and fostering new efforts • Mobilizing and focusing national and local support for achieving fish habitat conservation goals • Setting national and regional fish habitat conservation goals • Measuring and communicating the status and needs of fish habitats • Providing national leadership and coordination to conserve fish habitats Currently, the MN DNR is coordinating a regional effort under the NFHI umbrella to assess the status and prioritize habitat protection and restoration in lakes across the Midwest Our monitoring data from Minnesota lakes would feed information into this regional effort Consequently, national and regional grants from the NFHI may help shoulder the burden of paying to protect or restore Minnesota lakes Sampling Design Considerations The optimum sampling design can vary with desired scale of inference (i.e., the “population” of lakes represented by the data.) Spatial scales can range from the individual lake, to specific lake strata, to management regions, up to the entire population of lakes in Minnesota The desired scale of inference, available resources, and other logistical constraints help determine the relative benefits of competing sample designs such as cluster or stratified sampling schemes The choice of sampling design can also be affected by temporal concerns inherent in a long-term monitoring program; e.g., how to effectively detect trends in critical factors at the desired spatial scale; or, how to deal with seasonal fluctuations in measured variables for relevant comparisons between years The type of analysis desired (i.e., the ‘question’ we want to answer) also affects the optimum design Data analyses can be broken down into three broad categories: 1) summary statistics (e.g., mean total phosphorus) and their changes over time, 2) multivariate statistical analysis to elucidate complex relationships among variables, and 3) model development/testing/refinement as in an adaptive management strategy The type of analysis will affect choice of sample design, variables measured, and allocation of sampling effort For example, a simple random sample of many lakes may be preferred for estimating mean total phosphorus in Minnesota Lakes, while intensive data collection at a few lakes (or even a single lake) may be optimum strategy for an adaptive management experiment A split-panel design is an example of a versatile design that will allow inference over a range of spatiotemporal scales in all three categories of analysis questions The design consists of yearly measurement of a small set of lakes, supplemented by a stratified random sample of remaining lakes of interest This general design should be a good starting place for discussing relevant questions of interest, scale desired, and the trade-offs among different designs It is tempting to delay model development and testing (i.e analysis category #3 above) until there is more data available on the systems The process of building models of climate-lake interactions, however, could be very beneficial despite current lack of data Model building, even if limited to verbal descriptive models, will require explicitly denoting what is known and unknown about lake dynamics, a process that will help to detect pertinent gaps in understanding and determine what data are potentially important for detecting climate-driven changes Some pertinent questions to consider in determining optimum design: • What we want to know? (i.e., summary statistics, multivariate analysis, model testing?) • What lakes we want the data to represent? (e.g., deep lakes vs shallow lakes? Softwater lakes vs hard-water lakes, lakes in the NE vs lakes in SW, or a “class” or “type” of lake that incorporates many features – Schupp Lake Class) • At what scale? (e.g., spatial - local, regional, statewide; temporal – seasonal, interannual, and generational dynamics) Expected dynamics? (e.g., relevant variables in various lake types, their expected distribution and temporal variation, relationships among variables, models of systems, what is known/unknown?) • Proposals for a monitoring program administered by DNR Fisheries The Long-term monitoring committee will use feedback from fisheries managers and researchers in other agencies and academia from three meetings to draft two proposals The first proposal will be a semi-ambitious proposal that will be submitted to the Legislative Citizen’s Commission of Minnesota’s Resources (LCCMR) during the 2007 request for proposals (deadline November 2007) A second, scaled-down proposal will also be drafted that will propose a long-term monitoring program using current levels of staffing The LCCMR proposal will include funding for one to two full-time positions and multiple seasonal positions The LCCMR proposal will likely include a proposal to monitor more indicators, more lakes, more frequently than the scaled-down proposal The scaled-down proposal may require some management areas to reallocate some resources to address the objectives of the monitoring program Both proposals will require a programmer to design the database and a program manager to manage and analyze the data and produce annual reports Parallel to these efforts is an effort to partner with the University of Minnesota to resurrect the Lake Itasca Biological station as center for long-term monitoring and research As such, lakes near the station will be considered as candidate lakes for monitoring Timeline: 10/02/06 11/29/06 01/08/07 02/14/07 04/01/07 04/30/07 LTM comm Mtg w/ repsWorkshop to Fisheries Draft proposals Revised formed from other brainstorm Training to be sent outproposals to be programs and focus Session – keyto wkshp sent to mgmt staff proposals feedback on participants proposal from fisheries managers 09/01/07 11//07 Final Submission to revisions to LCCMR LCCMR proposal Spr 2008 Begin data collection Literature Cited Casselman, J.M 2002 Effects of temperature, global extremes, and climate change on year-class production of warmwater, coolwater, and coldwater fishes in the Great Lakes basin Pages 39-60 in N.A McGinn, editor Fisheries in a changing climate American Fisheries Society Symposium 32 Bethesda, Maryland DeStasio, B.T Jr., D.K Hill, J.M Kleinhans, N.P Nibbelink, and J.J Magnuson 1996 Potential effects of global climate change on small north-temperate lakes: physics, fish, and plankton Limnology and Oceanography 41: 1136-1149 Gitay, H and 20 co-authors 2001 Ecosystems and their goods and services Pages 237-342 in J.J McCarthy, O.F Canziani, N.A Leary, D.J Dokken, and K.S White, editors Climate Change 2001: impacts, adaptation, and vulnerability Cambridge University Press, Cambridge, U.K Hamilton, J.D and S Johnson Playing with fire: climate change in Minnesota Minnesotans for an Energy-Efficient Economy 2003 Intergovernmental Panel on Climate Change (IPCC) 2001 Climate change 2001: the scientific basis Contribution of working group I to the third assessment report Cambridge University Press, Cambridge U.K Jackson, D.A., and N.E Mandrak 2002 Changing fish biodiversity: predicting the loss of cyprinid biodiversity due to global climate change Pages 89-98 in N.A McGinn, editor Fisheries in a changing climate American Fisheries Society Symposium 32 Bethesda, Maryland Johnson, S.L and H.S Stefan Indicators of climate warming in Minnesota: Lake ice covers and snow melt runoff Climate Change: 75: 421-453 2006 Magnuson, J.J and 13 co-authors 2000 Historical trends in lake and river ice cover in the northern hemisphere Science 289: 1743-1746 Magnuson, J.J., T.K Kratz, B.J Benson 2006 The challenge of time and space in ecology Pages 3-16 in J.J Magnuson, T.K Kratz, and B.J Benson, editors Long-term dynamics of lakes in the landscape Oxford University Press, New York McGinn N.A editor 2002 Fisheries in a changing climate American Fisheries Society Symposium 32 Bethesda, Maryland Pauly, D 1995 Anecdotes and the shifting baseline syndrome of fisheries Trends in Ecology and Evolution 10: 430-435 Shuter, B.J., C.K Minns, N Lester 2002 Climate change, freshwater fish, and fisheries: case studies from Ontario and their use in assessing potential impacts Pages 77-88 in N.A McGinn, editor Fisheries in a changing climate American Fisheries Society Symposium 32 Bethesda, Maryland Stefan, H.G., M Hondzo, X Fang, J.G Eaton, and J.H McCormick 1996 Simulated long-term temperature and dissolved oxygen characteristics of lakes in the north-central United States and associated fish habitat limits Limnology and Oceanography 41: 1124-1135 United Nations Environment Programme (UNEP) 2006 Migratory species and climate change Impacts of a changing environment on wild animals UNEP and Secretariat of the Convention on the Conservation of Migratory Species of Wild Animals, Bonn, Germany Agenda for January workshop at the Kelly Inn in St Cloud: Monday, January 8th 1000 Welcome and why you are here 1015 Scoping a long-term monitoring program for MN lakes – background, mission, goals, outcomes from meeting 1030 David Staples – Discussing the “How” of monitoring: program and sample design considerations 1100 Don Periera – Climate change and fisheries 1130 Presentation and instructions for workgroups addressing “stressors” – assign members Workgroup discussions 1200 Lunch - provided 1300 Workgroups develop conceptual models 1430 Break 1445 Reconvene as large group Group leaders present results 1600 Discussion and instructions for next day (LTM co-chairs synthesize results) Tuesday, January 9th 0800 Synthesis of outcomes from the stressor workgroups – common themes 0900 Break into technical “indicator” groups – discuss technical issues related to sampling techniques, variables of interest, sensitivity of the indicator, “noisiness” of the indicator, what changes in the indicator indicate, frequency of sampling required, and personnel needs 1030 Reconvene as a large group – discuss next steps and how to address challenges 1200 Adjourn List of invited workshop participants DNR Fisheries Andy Carlson Brad Parsons Brian Herwig Donna Dustin Doug Kingsley Henry Drewes Jeff Reed Jerry Younk Peter Jacobson Dan Isermann Deb Sewell Paul Diedrich Tom Jones Brian Stenquist Don Pereira Jack Wingate Cindy Tomcko Rod Pierce Steve Persons Norm Haukos Tim Cross Douglas Dieterman John Hoxmeier Steve Klotz David Staples Melissa Drake Tim Cross Ray Valley Al Stevens DNR Ecological Services Robert Burdis Norm Aaseng Daren Carlson Brian Stenquist Ian Chisholm Donna Perleberg DNR Wildlife Nicole Hansel-Welch Mark Hanson PCA Steve Heiskary Bruce Monson Academic Institutions Susan Galatowitsch (UM) Kyle Zimmer (ST) Lucinda Johnson (NRRI) Ray Newman (UM) Minnesota Department of Health Pat McCann ... objectives of the monitoring program Both proposals will require a programmer to design the database and a program manager to manage and analyze the data and produce annual reports Parallel to these... (http://www.pca.state.mn.us/hot/pubs/climatesymposium-listofactivities.pdf) Activity Lake water quality monitoring http://www.pca.state.mn.us/water/lakeprogra ms.html#clean Aquatic plant monitoring State Wildlife Action Plan monitoring Shallow lake. .. in aquatic plant occurrence in Lake Christina, Douglas Co Box Case History of Lake Christina, Douglas Co Lake Christina is one Minnesota? ??s most important waterfowl staging lakes Aquatic plant abundance