REVISED MS - MULTISCALE GEOSPATIAL ANALYSES - EMA.DOC

1 Critical Role for Hierarchical Geospatial Analyses in the Design of Fluvial Research, Assessment, and Management James H Thorpa, Joseph E Flotemerschb, Bradley S Williamsa, and Laura A Gabanskic a Kansas, Lawrence, KS, USA b 10 Kansas Biological Survey and Department of Ecology and Evolutionary Biology, University of U.S Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA c U.S EPA, Office of Water, Washington, D.C., USA 11 12 Corresponding Author: Prof James H Thorp 13 Kansas Biological Survey and Department of Ecology and Evolutionary Biology, University of 14 Kansas, Higuchi Hall, 2101 Constant Ave., Lawrence, KS 66047-3759 USA 15 Email: thorp@ku.edu; Tel: 1-785-864-1532; Fax: 1-785-864-1534 16 17 Keywords: aquatic ecoregions • functional process zones • GAP analysis • hydrogeomorphic 18 patches • riverine ecosystem synthesis • stream classification assessments -1- 19 Abstract 20 scales from reach to basin levels as long as the project goals and questions are matched correctly 21 with the study design’s spatiotemporal scales and dependent variables These project goals 22 should also incorporate information on the hydrogeomorphically patchy nature of rivers which is 23 only partially predictable from a river’s headwaters to its terminus This patchiness significantly 24 affects a river’s habitat template, and thus community structure, ecosystem function, and 25 responses to perturbations 26 River science and management can be conducted at a range of spatiotemporal Our manuscript is designed for use by entry-level river scientists through senior 27 administrators at government agencies It analyzes common challenges in project design and 28 recommends solutions based partially on hierarchical analyses that combine geographic 29 information systems (GIS) and multivariate statistical analysis to enable self-emergence of a 30 stream’s patchy structure These approaches are useful at all spatial levels and can vary from 31 primary reliance on geospatial techniques at the valley level to a greater dependence on field- 32 based measurements and expert opinion at the reach level Comparative uses of functional 33 process zones (FPZs = valley-scale hydrogeomorphic patches), ecoregions, hydrologic unit codes 34 (HUCs), and reaches in project designs are discussed along with other comparative approaches 35 for stream classification and analysis of species distributions (e.g., GAP analysis) Use of 36 hierarchical classification of patch structure for sample stratification, reference site selection, 37 ecosystem services, rehabilitation, and mitigation are briefly explored -2- 38 Introduction 39 40 Policies for managing watersheds, establishing or enforcing environmental policies, and 41 rehabilitating riverine landscapes have inherent assumptions that the grain and extent of the 42 spatiotemporal sampling scale employed and the data variables selected are appropriate to their 43 study goals (cf Kondolf 1998) They may also assume implicitly while selecting monitoring sites 44 that the physical characteristics of the river channel and its valley change continuously and 45 predictably from headwaters to the river terminus Too often, however, these vital assumptions 46 are never critically examined, with the result that many studies are conducted at questionable 47 spatiotemporal scales, using less compatible dependent variables (cf Williams et al 1997; Dollar 48 et al 2007), and ignoring river patchiness while introducing systematic sampling errors (Thorp et 49 al 2006, 2008) Our manuscript’s goals are to help improve the protection, management, and 50 rehabilitation of “rivers”, which are defined here as all fluvial systems from headwater streams to 51 great rivers 52 53 Common spatiotemporal scales and designs in river assessment and management 54 Historical focus in bioassessment and management 55 56 Since passage of U.S federal legislation mandating improvements in water quality (e.g., the 57 Federal Water Pollution Control Amendments of 1972), bioassessment approaches have usually 58 concentrated on smaller streams (e.g., Barbour et al 1999) The primary independent variables 59 were often stratified by stream order and derived from field-based habitat analyses of reaches, -3- 60 such as the still popular Rosgen Method in the USA (Rosgen 1994, 1996) and the River Styles 61 approach in Australia (e.g., Brierley et al 2002) On-site hydrogeomorphic analyses were often 62 combined with land use and coverage data obtained from aerial or satellite imagery The primary 63 dependent variables reflected the smaller extent and grain of the spatial scale and focused 64 initially on physicochemical measurements of water quality and later on biotic metrics, 65 especially related to easily collected macroinvertebrates Later variables included the abundance 66 and diversity of fish (longer-lived organisms with greater home ranges) and Chl-a biomass 67 estimates of algae (rapid turnover) 68 With the transition to a new century, scientists and government agencies (e.g Newson 69 1992; Gardiner et al 1994; Council of the European Union 1999; Hooper 2005) increasingly 70 recognized the need to expand the diversity of monitoring and assessment from a primary focus 71 at the reach level to larger (grain and extent) spatial scales needed for watershed management 72 (Tarlock 2008; Thorp et al 2008; Heathcote 2009; Southerland et al 2009) As a partial result, 73 government agencies are increasingly developing sampling protocols for large rivers (Humphries 74 et al 1998; Parsons et al 2004; Flotemersch et al 2011), but a consensus on ideal protocols for 75 rivers lags behind those for shallow streams Protocols for sampling non-wadeable rivers were 76 not even published by the U.S Environmental Protection Agency (EPA) until the current century 77 (Lazorchak et al 2000) 78 79 Typical bioassessment project designs 80 -4- 81 The motivation for quantitative bioassessments at basin-wide scales probably stems from both 82 legal mandates requiring watershed assessments and a growing recognition of threats from 83 multiple and co-varying stressors (e.g., pollutants, habitat destruction, altered flow regimes, 84 channel modifications, invasive species, and climate change) Bioassessment allows evaluation 85 of a waterbody’s biological integrity, as defined by the ability to support and maintain a 86 balanced, integrated, and adaptive community having a biological diversity, composition, and 87 functional organization comparable to those of natural aquatic ecosystems in the region (Frey 88 1977; Karr and Dudley 1981; Karr et al 1986) 89 Bioassessments occur at spatial scales ranging from targeted site-specific sampling for 90 particular program needs (e.g., compliance or stressor-specific studies of the EPA's National 91 Pollutant Discharge Elimination System) to sampling at national scales, such as EPA’s National 92 Aquatic Resource Surveys (USEPA 2010) When assessment objectives emphasize a spatial 93 extent beyond individual sites, sample surveys using stratified random site selection help account 94 for spatial variability and control bias, and they contribute to more objective statements of area- 95 wide conditions (Larsen 1997; Urquhart et al 1998; Larsen et al 2007) Common sample area 96 categories used in such survey designs include those based on ecoregions, physiographic 97 provinces, vegetative classes, stream size or order, and other natural biogeographic factors 98 directly influencing ecosystem structure, with the spatial grain and extent of sample units ideally 99 approximating information needs, as defined by assessment objectives (Barbour et al 1999; 100 Flotemersch et al 2006) Sampling has also been stratified by political boundaries (e.g., U.S 101 EPA’s Missouri River EMAP) 10 -5- 11 102 Although biomonitoring has mostly occurred at the reach level in wadeable streams, 103 reach definitions and boundaries are often arbitrary (Frissel et al 1986; Flotemersch et al 2011) 104 Nineteenth-century river boat captains defined reaches as straight stretches of variable length 105 between river bends (see Life on the Mississippi by the former riverboat pilot Samuel L Clemens 106 [Mark Twain]) To 21st century lotic scientists, a reach could be, for example: (a) a repeatable 107 stream unit (e.g., pool-riffle sequences); (b) a specified number of wetted channel widths (e.g., 108 40); (c) the distance between two minimum-sized tributaries; (d) a consistent, pre-selected 109 stream length around a mid-point determined from a geospatial grid; or (e) an operationally 110 defined, arbitrary sample segment length for a specific study Reaches can also be defined more 111 precisely as a stream length between substantial geomorphic breaks in channel slope, local side- 112 slopes, valley floor width, riparian vegetation, and bank material (e.g., Frissell et al 1986), 113 although this is a more time-intensive and expensive approach While this variability in reach 114 definitions poses challenges for extrapolating among projects and sites (especially among 115 hydrogeomorphically distinct areas), the reach stream unit is useful for describing medium- and 116 long-term effects of human activities (Frissell et al 1986), at least for local disturbances or 117 rehabilitation projects 118 119 Matching the appropriate concepts, scales, and variables in study designs 120 River concepts influence study design 121 122 River science progresses by building and improving on past conceptual models and empirical 123 studies, with their associated sampling strategies A decade into this new millennium, most 12 -6- 13 124 published environmental research and assessment studies seem to have assumed that physical 125 conditions change gradually and mostly continuously from headwaters to the mouth, as proposed 126 by the river continuum concept, or RCC (Vannote et al 1980) Consequently, past study designs 127 incorporated random sampling or data collection stratified by linear downstream segments, as 128 has been employed in many studies including the Missouri River EMAP project (Schweiger et al 129 2005) A reasonable assumption that followed from the RCC’s important but scale-free 130 conceptual model was that adjacent areas were more similar to each other than they were to more 131 distant patches (but see Poole 2002) Many monitoring studies also focused on the main channel 132 and intentionally ignored lateral, and often species rich areas of the riverine landscape to 133 simplify sampling strategies, data interpretation, and costs 134 Conceptual ecological studies in the last two decades and access to high resolution data at 135 the basin scale (Fonstad and Marcus 2010) are altering our perspective of rivers from linear, 136 main channel systems to complex, 4-dimensional riverine landscapes (Ward 1989) composed of 137 a hierarchically nested, hydrogeomorphic patch structure (e.g., Montgomery 1999; Poole 2002, 138 Carbonneau et al 2011) Rivers can also be considered as “directionally nested networks” 139 (Melles et al 2011) to account for differences in hierarchical interactions within upstream vs 140 downstream components of the river network These hierarchical patches may be repeatable and 141 only partially predictable in position according to the riverine ecosystem synthesis (Thorp et al 142 2006, 2008) This patch perspective engendered the hypothesis that ecosystem structure, 143 function, and services will be more comparable in two distantly separated patches of the same 144 hydrogeomorphic type than in adjacent patches with different physical structure (Poole 2002; 145 Thorp et al 2006, 2008, 2010) Modern landscape perspectives also emphasize the importance of 14 -7- 15 146 considering the two major components of the riverine landscape: the riverscape (sub-flood 147 components, including main channel, side channels, and the mostly isolated backwaters; cf 148 Leopold and Marchand 1968; Wiens 2002) and the floodscape (floodplain lakes, isolated 149 oxbows, wetlands, and the normally terrestrial floodplains; Thorp et al 2008) 150 Effective river management demands an appreciation of the system’s hierarchical 151 organization in order to select proper variables and sampling designs For example, a river 152 scientist needs to understand how effects of biotic or physicochemical processes on system 153 functioning vary with the study’s focal scale (Parsons et al 2004; Dollar et al 2007) Past studies 154 were often shaped by widespread views of rivers as continuous gradients of physical structure 155 and by limited access to geospatial techniques and models that would enable the project designer 156 to understand better the river’s patch structure In some cases, investigators can reinterpret old 157 sampling data using new hydrogeomorphic analyses as long as the sampled variables conformed 158 to the correct spatiotemporal scales 159 160 Examples of mismatched spatiotemporal scales 161 162 A mismatch of scales, ecological processes, and dependent variables may occur if dependent 163 variables are not simultaneously expanded in scale with increases in the physical area sampled 164 and the temporal scale of the research or management question This problem most often occurs 165 when reach scale analyses are employed to answer valley or basin scale questions The following 166 four examples illustrate some of the many areas where mismatches may occur 16 -8- 17 167 Home range: Reach-level monitoring studies may be appropriate only when the 168 dependent variables are equally limited in scale For example, if the spatial extent of 169 environmental impacts is local, it is appropriate to measure the density and diversity is of benthic 170 invertebrates because these organisms generally have very limited home ranges In contrast, most 171 fish species have larger home ranges than invertebrates, and some migrate long distances, 172 especially diadromous species Therefore, measurement of fish species at the reach level may be 173 problematic in terms of cause-and-effect determinations (cf Fausch et al 2002; Boys and Thoms 174 2006; Springe et al 2006) unless the species in question has a reach-scale home range 175 Regulation by density independent disturbances: A temporal mismatch can easily result if 176 researchers focus on short-term processes affecting species diversity and density because the 177 community may be subject to periodic reset from natural, density independent processes These 178 include, in particular, hydrologic flow and flood pulses as well as droughts that reduce or 179 eliminate discharge, especially when surface water channels dry to isolated pools, as in many 180 arid-zone rivers of Australia (e.g., Bunn et al 2006; Feld and Hering 2007) 181 Measurement and interpretation of ecosystem processes: If a study focuses on responses 182 of ecosystem function (e.g., system metabolism and nutrient spiraling) to disturbances, then 183 system-level sampling that is restricted to, or interpreted for the reach level is misleading at best, 184 especially if the spatiotemporal scales not encompass major flow fluctuations and lateral 185 connections with floodscape and riverscape slackwater components Reach-level perturbations 186 can alter local measurements, but information on upstream and lateral processes are needed to 187 adequately interpret disturbance to ecosystem function (e.g., Feld and Hering 2007) 18 -9- 19 188 Watershed impacts: River scientists and managers have long recognized the importance 189 of terrestrial components of watersheds to community structure and ecosystem function While 190 the local riparian zone can alter reach-level structure and function, the larger floodscape and the 191 local terrestrial basin (i.e., floodscape plus valley side-slopes) exert their influences much farther 192 up- and downstream from local sample areas and over longer periods through the flow of water, 193 sediment, and organic matter 194 195 Recommended improvements to study design 196 Hierarchical designs for a hierarchical world 197 198 Designing and conducting hierarchical studies require a multi-stage process which proceeds from 199 goal establishment, through determining appropriate spatiotemporal scales and data variables, to 200 final conclusions – with opportunities for reassessment of scales and questions as more 201 knowledge is gained An example of this step-by-step process, Figure shows a decision tree 202 which uses ecosystem management of riverine Least Terns (a federally endangered shore bird) 203 Some factors influencing study design are described below 204 Every activity within a riverine landscape has a primary governing domain (e.g., 205 scientific, policy/management, or conservation) with various organizational categories and 206 levels For instance, the river management domain could include functional levels related to 207 policy development, implementation, monitoring/assessment, and enforcement (e.g., see the first 208 two steps in Figure 1) These functional levels are often associated with specific hierarchical 209 spatial levels, most of which can be defined hydrogeomorphically, as shown in Table for a 20 -10- 45 446 river section to enhance biocomplexity or improve ecosystem services should be affected in a 447 sometimes non-linear fashion by the patch structure of that river section (Thorp et al 2010), the 448 type of mitigation (e.g., dam removal and levee set-backs), and the relative value placed on 449 different ecosystem services and goods It should be possible to predict with some degree of 450 certainty the final FPZ state as long as the ecosystem drivers have not changed appreciably 451 Two common mitigation procedures for leveed rivers are setting back or gating existing 452 levees to form lateral channels or wetlands, as in the Emiquon Project on the Illinois River in 453 midwestern USA (e.g., Reuter et al 2005) If we assume that mitigation costs of setting back a 454 river levee will rise in proportion to increases in channel width, then a goal should be to restore 455 sufficient services while minimizing the cost-benefit ratio To achieve this goal, we need to 456 know: (1) what new kind of FPZ and associated services are likely to result from the engineering 457 action; and (2) how the cost-benefit ratio will vary with the services evaluated and their 458 responses to changes in the nature and extent of the new FPZ 459 Mitigation of environmental disturbances seems less common in rivers than in wetlands, 460 but river managers need a defensible basis for permittee-responsible mitigation, mitigation 461 banking, and in-lieu mitigation to ensure compliance with Sections 401 and 404 of the U.S 462 Clean Water Act (cf., http://www.epa.gov/owow/wetlands/pdf/CMitigation.pdf) For example, 463 compensating for destruction of an anastomosing section of a river by restoring an equivalent 464 linear stretch of a meandering or constricted section of a river is unlikely to produce comparable 465 improvements in natural ecosystem attributes or ecosystem services (Thorp et al 2010) 466 Therefore, the identification of the hydrogeomorphic structure of multiple river sections helps 467 ensure fairer asset trading based on defensible credit-debit ratios 46 -22- 47 468 469 Acknowledgements Development of this article was aided by an EPA student services contract 470 to BSW and an EPA “intermittent expert” contract to JHT We appreciate the work of Dr Martin 471 Thoms and personnel in his Riverine Landscape Laboratory at the University of New England, 472 Armidale, N.S.W, Australia for their pioneering work on ArcGIS analysis of the 473 hydrogeomorphic structure of rivers We thank Brad Autrey, Heather Golden, and Tony Olsen at 474 EPA, and anonymous reviewers for comments on an earlier manuscript draft 475 476 The views expressed in this paper are those of the authors and not necessarily reflect the views or policies of the U.S Environmental Protection Agency 477 478 References 479 480 Abell, R.A., Olson, D.M., Dinersten, E., Hurley, P.T., Diggs, J.T., Eichbaum, W., Walters, S., 481 Wettengel, W., Allnutt, T., Loucks, C.J & Hedao, P (2000) Freshwater ecoregions of 482 North America: a conservation assessment Island Press, Washington, D.C., 318 p 483 Bailey, R.G Avers, P E., King, T & McNab, W.H (eds) (1994) Ecoregions and subregions of 484 the United States (map) Washington, DC, USDA Forest Service 1:7,500,000 With 485 supplementary table of map unit descriptions, compiled and edited by W H McNab and 486 R G Bailey 487 488 Barbour, M.T., Gerritsen, J., Snyder, B.D & Stribling, J.B (1999) Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates 48 -23- 49 489 and fish Second edition EPA 841-B-99-002 U.S Environmental Protection Agency, 490 Office of Water, Washington, DC 491 492 493 494 495 Belbin, L (1993) PATN technical reference CSIRO Division of Wildlife and Ecology, Canberra, Australia Belbin, L., McDonald C (1993) Comparing three classification strategies for use in ecology Journal of Vegetation Science 4, 341-348 Boys, C.A & Thoms, M.C (2006) A hierarchical scale approach to the assessment of fish 496 assemblages and their habitat associations in large dryland rivers Hydrobiologia 572, 11- 497 31 498 Brenden, T.O., Wang, L & Seelbach, P.W (2008) A river valley segment classification of 499 Michigan streams based on fish and physical attributes Transactions of the American 500 Fisheries Society 137, 1621-1636 501 Brierley, G., Fryirs, K, Outhet, D & Massey, C (2002) Application of the river styles 502 framework as a basis for river management in New South Wales, Australia Applied 503 Geography 22, 91–122 504 505 506 507 508 Bunn, S.E., Thoms, M.C., Hamilton, S.K & Capon, S.J (2006) Flow variability in dryland rivers: boom, bust and the bits in between River Research and Applications 22, 179-186 Carbonneau, P., Fonstad, M.A., Marcus, W.A & Dugdale, S.J (2011) Making riverscapes real Geomorphology (In Press; 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657 Williams , B.S., D’Amico, E., Kastens, J.H., Thorp, J.H., Flotemersch, J.E & Thoms, M.C 658 Automated riverine landscape characterization: GIS-based tools for watershed-scale 659 research, assessment, and management In Review 64 -31- 65 660 Williams, J.E., Wood, C.A & Dombeck, M.P (1997) Understanding watershed-scale 661 restoration Pages 1-16 in: Williams, J.E., C.A Wood, and J.E., Dombeck (eds.), 662 Watershed Restoration: Principles and Practices, American Fisheries Society, Bethesda, 663 MD 664 Zorn, T.G., Seelbach, P.W & Wiley, M.J (2002) Distribution of stream fishes and their 665 relationship to stream size and hydrology in Michigan’s Lower Peninsula Transactions 666 of the American Fisheries Society 131, 70-85 66 -32- 67 667 Table Examples of the division of a major basin into hierarchical levels based in part on 668 hydrogeomorphic structure HP = hydrogeomorphic patch; FPZ = functional process zone Major 669 basins are ones terminating in the ocean, a large lake, or an interior basin Political boundaries 670 are not included, but these could be incorporated if desired into a sample design Freshwater 671 ecoregions follow those in Abell et al (2000) 672 Spatial Hierarchical Levels Examples Freshwater Ecoregion Major Basin Mississippi River Basin Upper Missouri to Mississippi Embayment Missouri River Upper Missouri, Middle Missouri, etc Kansas River Middle Missouri Republican River Middle Missouri Lowland Braided Middle Missouri Geomorphic: (a) HP area delineated within an FPZ, (b) specific multiples of channel width (for single channels riverscapes), or (c) repeating sequence of functional units; Arbitrary Sample Units: (i) island-to-island area, (ii) tributary node-to-node; (iii) other more arbitrary units Middle Missouri pool, riffle, run, falls, etc Middle Missouri boulder, wood snag, etc Middle Missouri Major Sub-Basin Major Tributary Secondary Tributary Functional Process Zone Reach Functional Unit Macro-Microhabitat 673 674 Table Examples of some independent and dependent variables appropriate for measurement at 675 different spatial levels in river monitoring and assessment studies Some overlap between 68 -33- 69 676 adjacent columns occurs for both independent and dependent variables Not all possible variables 677 are listed N/A = not applicable 70 -34- 71 678 72 -35- 73 679 680 681 Figure Legends Figure A decision tree for designing environmental projects, with examples for projects 682 involving attributes of a single bird species, rehabilitation of a river section, and 683 condition assessment Not shown is the initial step of identifying the environmental 684 problem or issue of concern For ease of illustration, this is shown for management of the 685 Least Tern rather than for the desired overall ecosystem management; however, 686 successful protection and rehabilitation of this endangered species requires management 687 of major ecosystem processes, including timing and extent of floods 688 Figure Hierarchical levels within riverine landscapes and associated hydrological and 689 ecological processes operating at different spatiotemporal scales This information can be 690 employed in developing the project design for monitoring and assessment projects and 691 other studies In such applications, the management focus is at one level but sampling is 692 undertaken at the hierarchical level immediately below Modified in part from Thorp et 693 al (2008) 694 Figure Functional process zones (FPZs) for the highly constricted Kanawha River Basin 695 located primarily in the Appalachian Mountains of the eastern USA The best statistical 696 solution shows seven FPZs for this 31,690 km2 basin 74 -36- ... bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates 48 -2 3- 49 489 and fish Second edition EPA 841-B-9 9-0 02 U.S Environmental Protection Agency,... Biology 52, 523 138 0-1 399 524 Flotemersch, J.E., Stribling, J.B & Paul, M.J (2006) Concepts and approaches for the 525 bioassessment of non-wadeable streams and rivers EPA 600-R-0 6-1 27 U.S 526 Environmental... assessment, and management In Review 64 -3 1- 65 660 Williams, J.E., Wood, C.A & Dombeck, M.P (1997) Understanding watershed-scale 661 restoration Pages 1-1 6 in: Williams, J.E., C.A Wood, and J.E., Dombeck