Dealing With Uncertainty When Assessing Fish Passage Through Culvert Road Crossings
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- Anderson, G.B., Freeman, M.C., Freeman, B.J. et al. Environmental Management (2012) 50: 462. doi:10.1007/s00267-012-9886-6
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Assessing the passage of aquatic organisms through culvert road crossings has become increasingly common in efforts to restore stream habitat. Several federal and state agencies and local stakeholders have adopted assessment approaches based on literature-derived criteria for culvert impassability. However, criteria differ and are typically specific to larger-bodied fishes. In an analysis to prioritize culverts for remediation to benefit imperiled, small-bodied fishes in the Upper Coosa River system in the southeastern United States, we assessed the sensitivity of prioritization to the use of differing but plausible criteria for culvert impassability. Using measurements at 256 road crossings, we assessed culvert impassability using four alternative criteria sets represented in Bayesian belief networks. Two criteria sets scored culverts as either passable or impassable based on alternative thresholds of culvert characteristics (outlet elevation, baseflow water velocity). Two additional criteria sets incorporated uncertainty concerning ability of small-bodied fishes to pass through culverts and estimated a probability of culvert impassability. To prioritize culverts for remediation, we combined estimated culvert impassability with culvert position in the stream network relative to other barriers to compute prospective gain in connected stream habitat for the target fish species. Although four culverts ranked highly for remediation regardless of which criteria were used to assess impassability, other culverts differed widely in priority depending on criteria. Our results emphasize the value of explicitly incorporating uncertainty into criteria underlying remediation decisions. Comparing outcomes among alternative, plausible criteria may also help to identify research most needed to narrow management uncertainty.
KeywordsCulvertFish passageStream habitatImperiled fishesBayesian belief network
Fragmentation of stream systems by dams and other human-made structures is a major cause of declining aquatic biodiversity worldwide (Strayer 2006; Dudgeon and others 2006; Helfman 2007). The effects of dams as barriers to migrations and dispersal of a variety of species (plants, mussels, fishes) are well documented (Ward and Stanford 1979; Petts 1984; Poff and Hart 2002; Freeman and others 2003), but managers are increasingly focused on the smaller and more pervasive barriers created by road crossings on streams, especially where crossings are constructed with culverts. These structures frequently constrict the stream through a hardened structure such as a metal or concrete pipe that can impede movements by fishes and other aquatic or semi-aquatic organisms (Derksen 1980; Belford and Gould 1989; Utzinger and others 1998; Warren and Pardew 1998; Toepfer and others 1999; Schaefer and others 2003; Gibson and others 2005; Benton and others 2008; Norman and others 2009). Consequently, federal and state resource-management agencies have developed programs to identify and remediate culverts that are barriers to stream biota movements. Examples include the U.S. Fish and Wildlife Service’s National Fish Passage Program and the U.S. Forest Service’s National Inventory and Assessment Procedure (Clarkin and others 2005), the latter of which focuses specifically on road crossings as barriers in streams. State fish and wildlife agencies, including those in Alaska, California, Maine, Massachusetts, Oregon, Washington, and Vermont, have similarly developed guidelines for recognizing and avoiding construction of culverts likely to impede fish movement (Mirati 1999; Taylor and Love 2003; Reback and others 2004; Milone & MacBroom, Inc 2009; WDFW 2009; ADF&G 2010).
Deciding where to invest restoration resources on culvert remediation (i.e., removal or replacement with an alternative structure) poses a distinct problem from designing road crossings that will not impede passage by stream biota. Current thought on design dictates placing culverts so that the streambed maintains natural channel characteristics as it passes under the road, with similar depths, bed sediments and water velocities to those upstream and downstream of the crossing (Bates and others 2003; Norman and others 2006; River and Stream Continuity Partnership 2006). However, a program to reduce fragmentation of habitat and populations by replacing existing poorly designed culverts involves the initial questions of (1) which culverts are barriers to organism movement, and (2) which structures would, if remediated, most benefit aquatic biota. Addressing these questions provides a foundation for considering other benefits (e.g., reducing crossing maintenance and increasing safety), along with the costs of remediation and additional considerations (e.g., public and partner support).
Identifying whether a culvert is a barrier can be difficult because aquatic organisms vary widely in their ability to traverse steep grades or move against high velocity currents. Additionally, organisms may require passage only at particular times, for example to reach spawning, rearing or overwintering habitats (Fausch and Young 1995) or only periodically to facilitate re-colonization (Meffe and Sheldon 1990; Detenbeck and others 1992; Roghair and Dolloff 2005; Albanese and others 2009) and genetic exchange (Gagen and Rajput 2002). Thus, a culvert that is a barrier to movement at extreme low flows might provide passage at higher flows adequate to maintain populations. These considerations have led to differing criteria for identifying culverts as barriers, even for fishes with well-studied leaping and swimming abilities. For example, standards for designating a culvert as impassable by adult salmonids have included a drop from the culvert outlet to the water surface of 0.24 m (WDFW 2009), 0.3 m (NMFS Southwest Region 2001; Milone & MacBroom, Inc. 2009), and 0.6 m (Taylor and Love 2003; Coffman 2005). For fishes with lesser leaping or swimming abilities, thresholds for what constitutes barriers are even less clear. Most standards recognize uncertainty in identifying culverts as impassable, and several recognize that passage might not be a binary state (i.e., passable vs. impassable) (Coffman 2005; Diebel and others 2010; WDFW 2009; Kemp and O’Hanley 2010).
In typical landscapes with multiple road crossings on streams, culverts may be prioritized for remediation to maximize expected benefit to aquatic organisms, perhaps while minimizing costs or meeting other objectives. Often, culvert remediation decisions are based on scoring and ranking schemes that are independent of spatial arrangement of the culverts or other barriers (O’Hanley and Tomberlin 2005; Kemp and O’Hanley 2010). However, the remediation of a barrier within close proximity of another barrier may do little to improve stream connectivity. By considering the spatial context of culverts and other barriers (e.g., impoundments), the amount of habitat potentially reconnected by remediation could be incorporated in prioritization scores. For example, Cote and others (2009) propose the Dendritic Connectivity Index (DCI) as a measure of how multiple barriers decrease the probability that an organism is able to move between two randomly selected points in a stream network. Simulating DCI with each barrier in a watershed eliminated in turn can identify barrier removal that would maximize network connectivity, thus accounting for the spatial context of each barrier (Cote and others 2009; Bourne and others 2011). Diebel and others (2010) provide a similar measure of culvert effects on watershed-wide stream connectivity, in this case summed across habitat types (e.g., stream orders) and weighted by habitat quality and distance between stream segments. Measures of network connectivity also can be used in optimization models to rank barriers for removal with the goal of maximizing watershed-wide stream connectivity given economic constraints (O’Hanley and Tomberlin 2005; Diebel and others 2010; Kemp and O’Hanley 2010).
Our objective has been to develop an approach for prioritizing culverts for removal or replacement to benefit small-bodied species of imperiled stream fishes, recognizing the interrelated challenges posed by uncertainty in assessing culverts as barriers, and the influence of the spatial arrangement of culverts and other barriers on potential benefits. Managing for persistence of small-bodied imperiled stream fishes may differ from maximizing basin-wide connectivity for anadromous or migratory (potomodromous) fishes (O’Hanley and Tomberlin 2005; Cote and others 2009; Bourne and others 2011). Many imperiled stream fishes occur in small, often disjunct areas within a basin, where local habitat fragmentation may reduce gene flow, effective population size (Allendorf and Luikart 2007) and recolonization potential (Albanese and others 2009), and increase the potential for inbreeding, genetic drift, and loss of ecological and genetic diversity. In these cases, the availability of unfragmented stream habitat in the areas occupied by each species of concern may be more relevant to species conservation than basin-wide connectivity (which could include connectivity to areas beyond the dispersal distances of target species). Therefore, our approach has involved estimating potential gain in connected habitat for targeted species of conservation concern from remediating individual culverts, accounting for spatial context relative to upstream and downstream barriers. We also explicitly examine how the choice among alternative, plausible criteria for evaluating fish passage at a culvert may influence relative rankings of culverts for remediation in an actual river system. Our analysis illustrates a general approach for prioritizing culvert remediation to benefit aquatic species, the potential importance of explicitly recognizing uncertainty in how culverts form barriers, and areas where research could narrow that uncertainty.
Fish species used to prioritize culvert remediation within priority sub-systems of the Upper Coosa River system
Family common name
Maximum total length (cm)
Minimum watershed size (km2)
Hybopsis sp. cf. H. winchelli
Macrhybopsis sp. cf. M. aestivalis
Etheostoma sp. cf. E. brevirostrum
Site Selection for Culvert Assessment
We created a stream drainage network based on a 30-m resolution digital elevation model and the 1:24,000 National Hydrography Dataset (NHD) for the project area. Streams were created using ArcHydro 9 Toolbox with ArcGIS 9.2 (Esri, Redlands, California) and were set to originate at 120 cells (i.e., 0.1 km2 drainages). Using the 1997 1:24,000 Georgia Department of Transportation (GDOT) road coverage, we recorded the intersection of all streams and road crossings. We also mapped locations of impoundments using National Inventory of Dams, NHD, and dams identified in aerial photography of the study area (Appendix). To narrow the pool of sites for field inspections, we omitted all road crossings likely to be bridges based on drainage area over 52 km2 (based on GDOT policy). Additionally, all crossings within 500 m downstream of an impoundment were eliminated from further consideration; dams were considered impassable by fishes, and thus habitat gained by remediating a near-by downstream culvert would be minor. Similarly, because impoundments did not provide suitable habitat for the target fish species, road crossings upstream of an impoundment were eliminated if: (1) the crossing was within 250 meters of the impoundment border (exclusive to impoundment outlines documented within the NHD); (2) the crossing was within 250 meters of any plotted impoundment; or (3) the drainage size above the impoundment was less than 1 km2 (i.e., considered too small to support populations of target fish species).
We calculated the smallest stream size likely to be occupied for each target species based on minimum drainage areas upstream of known occurrences (Table 1). We eliminated from consideration all stream crossings where the upstream drainage area was too small for target species, excepting the coldwater darter, Etheostoma ditrema, which primarily inhabits springs and spring runs, but also occurs in the mainstem Conasauga River. Thus, for sub-basins (12-digit USGS hydrologic units, or HUC12s) containing the coldwater darter, we included crossings between springs identified on USGS topographical maps and the nearest connected stream that had a drainage greater than 52 km2, and any road crossings upstream or downstream of a known occurrence of the coldwater darter.
The included stream crossings were prioritized for field surveys based on conservation priority in the Etowah and Conasauga River systems (Wenger and others 2009; Wenger and others 2010), location relative to impoundments, and drainage area if located above an impoundment. The highest priority areas in the Etowah and Conasauga systems were those that support federally-protected fishes. Stream crossings within these areas were surveyed first; lowest priority sites for field assessment were those nearest to dams and those located in relatively small drainages upstream from an impoundment. A total of 404 road crossings within the priority sub-basins of the Upper Coosa River system were visited between June 7, 2006 and March 12, 2008. Of the road crossings visited, 256 culverts were assessed for potential to impede passage by small-bodied fishes. The sites not assessed: lacked access or there was no road (n = 45); had a bridge, bottomless culvert, ford, or no crossing (n = 76); or were dry, intermittent or impounded streams (n = 23). An additional four sites were omitted from analysis due to incomplete data. Most sampled sites were in the Etowah River system (n = 195), with 48 sites assessed in the Conasauga River system and 13 within the Coosawattee River system.
Surveys were conducted from June 2006 to March 2008 by a team of three or four people, usually at baseflow conditions. Characteristics recorded at each crossing included type (freespan bridge, bottomless culvert, pipe culvert, or box culvert), culvert material (smooth metal, corrugated metal, or concrete), number of culvert openings, and occurrence of a concrete “apron” beneath the culvert. All fords, freespan bridges, and bottomless culverts encountered were assumed passable and omitted from further analysis. For all culverts, the length and diameter (or width) of each opening were measured from inside the culvert, along with the wetted width, the width of deposited sediment (if any), and the distance from the top of the pipe or box to the water surface and to the streambed sediments. If either end of the culvert was perched above the stream, the distances from the pipe or box lip (or apron lip, if applicable) to the water surface and to the streambed sediments were measured. At each outlet, water depth and velocity were measured in the center main flow from the pipe or box using a Marsh-McBirney Inc. FLO-MATETM Model 2000 portable flow meter with a top-setting wading rod at 60 % stream depth.
Stream metrics were also collected upstream, downstream and adjacent to the culvert. Average stream width was measured and the dominant bed sediment type noted upstream and downstream of the culvert. Width and depth of any scour pools adjacent to the culvert were measured, along with maximum stream width. We noted apparent bank erosion or occurrence of sediment deposits near the culvert.
Estimating Culvert Effects on Passage
Field measurements taken at culverts were used to estimate the probability that each culvert impeded passage by small-bodied fishes, using literature-derived criteria and hypotheses. We assumed all species of concern in our study system would be equally impeded by any given culvert, and thus estimated probability of passage for a generalized small-bodied (i.e., having maximum total length typically ≤10 cm; Table 1) fish species.
Alternative criteria sets used to assess the probability that culverts impede passage (“mostly impassable”) by small-bodied fishes, listing the probabilities of impassability assigned to different culvert conditions under the two-level and three-level criteria
Outlet drop (m)
Baseflow velocity (m/s)
Mostly impassable probability
Criteria narrative: culvert has some probability of blocking movement by small bodied fishes if:
High drop from culvert to water surface
Fast velocity at base-flow
Any drop from culvert to water surface
Moderate velocity at base flow
High drop to water surface, especially with evidence of Fast high-flow velocity
Moderate or Fast velocity at base flow with evidence of Fast high-flow velocity
Any drop to water surface and evidence of Fast high-flow velocity
High drop to water surface, especially with evidence of Fast velocity at high flows
Conditional probabilities for estimating the presence of fast velocity in culverts during high flows, based on observed velocity at baseflow and on occurrence of extensive scour or sediment deposition, or of sediment in the culvert
High flow velocity
Base flow velocity:
Extensive scour or sediment deposition
High flow velocity:
Sediment in culvert
High flow velocity:
We used the software Netica (Norsys Software Corp., Vancouver, British Columbia) to build the BBNs and to evaluate the probability of fish passage at each culvert using hypothesized conditional probabilities. The conditional probabilities are central to a BBN (Marcot and others 2006), specifying outcome probabilities in each node (model component) for all possible combinations of the factors immediately linked to that node. For our two- and three-level criteria, the probabilities of passage conditional on culvert out-flow drop, baseflow velocity or high-flow velocity were not known, nor were the probabilities of downstream scour or upstream deposition, or occurrence of sediment in the culvert, conditional on fast velocity during high-flow conditions. Therefore, we assigned conditional probabilities (Tables 2, 3) using plausible, judgment-based values, and then evaluated sensitivity of model outcomes to changes in those assigned probabilities. Specifically, we defined the combination of no drop from the culvert outlet and evidence of fast velocities at high flow as “possibly a barrier, but unlikely”, with probability of impassability defined as 0.20. Probability a culvert was impassable given either a large outlet drop or evidence of fast velocities at any flow was set to 0.50 (Table 2). We assigned a 0.75 probability of impassability for culverts with intermediate outlet drop in combination with evidence of fast, high-flow velocities (Table 2). One level up in the BBN (Fig. 2c, d), we assigned a 0.90 probability that fast high-flow velocity resulted in scour downstream or deposited sediment upstream from the culvert, and a 0.30 probability of these conditions in the absence of fast velocity at high flow (Table 3). We assumed fast high-flow velocity was 80 % likely to remove sediment from the culvert, whereas sediment was equally likely to occur or not (i.e., 50 %) in the absence of fast velocity at high flow (Table 3).
To evaluate the sensitivity of projected culvert impassability to conditional probability values used in the BBN for the two- and three-level criteria, we conducted a one-way sensitivity analysis (van der Gaag and Coupé 2000; Coupé and van der Gaag 2002). Specifically, we increased and decreased the conditional probabilities underlying conditions of (1) fast velocities at high flow, (2) extensive scour or sediment deposition, (3) occurrence of sediment in the culvert, and (4) the probability of culvert impassability, by increments of 0.10, up to a total change of plus and minus 0.50. The full dataset was re-analyzed to estimate mean culvert impassability for each incremental change in the conditional probability.
Summary statistics for sampled culverts in the Upper Coosa River system
Wetted width (m)
Sediment width (m)
Top to water surface (m)
Top to bed sediments (m)
Lip to bed sediments (m)
Lip to water surface (m)
Assessment and Prioritization
Counts of road crossings tabulated by level of impassability by small-bodied fishes, maximum priority score (weighted habitat gain in km), and counts of crossings with priority scores of at least 20, 10 and 5 km, as assessed using each of four criteria sets
Probability (impassable) = 0
>0.00 & <0.30
>0.30 & <0.60
>0.60 & <0.90
Probability (impassable) = 1.0 or >0.9
Maximum priority score
Number of crossings, priority score (km):
Small differences were observed in the scores assigned by culvert type (i.e., pipe or box) within each criteria set. Under the Wide criteria, 40 % of pipe culverts and 41 % of box culverts were considered impassable, compared to 62 % of pipe culverts and 63 % of box culverts under the narrow criteria. For both criteria sets, 46 culverts were deemed impassable because of high baseflow velocity. Forty-four culverts were deemed impassable due to outlet drop (i.e., >15 cm) under the wide criteria, compared to 72 under the narrow criteria (i.e., outlet drop > 0 cm). Ten and eight culverts were assessed as impassable under the wide and narrow standards, respectively, due to both velocity and outlet drop. Most pipe culverts assessed as impassable exceeded the velocity criterion, whereas outlet drop was the primary reason box culverts were deemed impassable. Using the two-level standards, probabilities of “mostly impassable” for pipe culverts and box culverts averaged 0.14 and 0.21, respectively, compared to 0.33 and 0.29 for the three-level standards.
Average culvert impassability was most sensitive to changes in conditional probabilities of impassibility in the absence of a high outlet-drop and absence of fast velocity at high-flow and baseflow (No/Elev. OD, Not-Fast HF, Slow or Slow/Mod BF; Fig. 4). Incrementally increasing the probability that the culvert was impassable for these conditions from 0 in the current analysis, to as high as 0.5 increased mean culvert impassability from 0.16 to > 0.4 or from 0.31 to 0.47 for two- and three-level criteria, respectively (Fig. 4). Although this represented a more than doubling of the mean probability of impassability under the two-level criteria, the change in conditional probability (from 0 to 0.5) in this case amounted to changing the criteria set (i.e., by removing the requirement for a high outlet drop for a culvert to be considered a barrier to passage; Table 2). Net effects of all other assessed changes in conditional probabilities were substantially smaller (Fig. 4).
Culverts ranking among the top five in priority for remediation under at least one criteria set
Priority rank (probability [mostly impassable], priority score)
Type (# of outlets)
Outlet drop (m)
Base flow velocity (m/s)
Probability [fast high-flow velocity]
No. species affected (# listed)
1 (0.94, 57.5)
1 (0.94, 57.4)
2 (1.0, 60.8)
2 (1.0, 60.1)
2 (0.59, 20.4)
3 (0.59, 20.3)
4 (1.0, 30.4)
4 (1.0, 30.4)
3 (0.91, 14.1)
6 (0.91, 14.1)
6 (1.0, 15.4)
7 (1.0, 15.4)
4 (0.91, 11.1)
7 (0.91, 10.8)
7 (1.0, 11.9)
9 (1.0, 11.9)
5 (1.00, 7.3)
9 (1.00, 7.3)
15 (1.0, 7.3)
17 (1.0, 7.3)
51 (0.00, 0)
2 (0.75, 40.4)
1 (1.0, 77.2)
1 (1.0, 77.2)
51 (0.00, 0)
4 (0.75, 20.0)
5 (1.0, 24.8)
5 (1.0, 24.8)
51 (0.00, 0)
5 (0.50, 19.6)
3 (1.0, 37.2)
3 (1.0, 34.8)
This study compared assessment outcomes using alternative, plausible criteria to estimate the ability of small-bodied fishes to pass through culvert road crossings, for a dataset of 256 measured culverts in a river system containing multiple species of conservation concern. We found that use of alternative criteria sets could influence culvert rankings for remediation. Using previously developed binary criteria (Millington 2004) as many as 155 culverts (61 % of the total) were identified as probable barriers to small-bodied fishes, because of high baseflow velocity or elevation of the culvert outlet above the water surface at baseflow. Using models that explicitly incorporated uncertainty in effects of baseflow velocity and outlet drop on fish passage (i.e., our two-and three-level criteria), 27 culverts (11 %) were estimated as >90 % likely to be impassable. Out of the 256 culverts assessed, only nine culverts were identified as complete barriers (i.e., probability of impassability = 1) by all four criteria sets used, but relatively little habitat would be reconnected if these structures were to be replaced; thus, they did not rank highly in replacement prioritization. Based on the priority strategy used in this study, up to 77 km of stream habitat summed for priority species could be reconnected through replacement of a single culvert (CONC-155) in the study area. However, assessing which culverts would provide the most benefit (or even any benefit) depended on criteria used to assess impassability.
The four criteria sets used to assess culverts as barriers in this study reflect alternative ideas about how culverts may block passage by small-bodied fishes. Field studies of fish movements through culverts support the assertion that culverts perched above the bed sediments, or with strong velocity at baseflow or during high flow events may impede movement by small-bodied fishes (e.g., Toepfer and others 1999; Warren and Pardew 1998; Coffman 2005; Benton and others 2008; Norman and others 2009). However, even culverts with outlets elevated above the water surface at low flows may not form complete barriers to upstream movement by small fishes. For example, Norman and others (2009) report upstream movement by small-bodied minnows (Cyprinidae) through culverts with outlet drops at baseflows, but only during intervals including higher flows that eliminated the drops. Coffman (2005) similarly reports infrequent movements by minnows and also sculpin (Cottidae) through culverts that had been classified as impassable on the basis of outlet elevation or slope (and hence velocity), possibly facilitated by higher flows. Thus, binary classification of culverts as either passable or impassable is likely an over-simplification for many species, because passage may be possible during occasional periods when flow levels provide sufficient depth to submerge an elevated outlet without creating velocities that are too great for small fishes to swim against.
The two-level and three-level criteria evaluated in this study allowed some possibility of movement through culverts that would have been assessed as impassable under the binary (i.e., wide and narrow) criteria. Constructing the BBNs to assess impassability using the two- and three-level criteria required that we assign conditional probabilities relating observations of scour or sediment deposition to occurrence of high velocities at high flows, and fish passage to conditions of outlet drop and current velocities. However, estimated impassability on average was not greatly altered by changing those assigned conditional probabilities except when the changes amounted to changing from one criteria set to another. In contrast, our analysis was sensitive to the choice between the two-level and three-level criteria, in that different culverts ranked highly for remediation under the two criteria sets (Fig. 5). These criteria primarily differed in whether a culvert with an outlet drop < 15 cm either could (three-level) or could not (two-level) form a passage barrier. If moderate or high velocities were believed to impede fish passage to some extent even in the absence of an outlet drop, then it would be more appropriate to apply criteria like the three-level set. Although the three-level criteria provided similar estimates of weighted potential habitat gain as the two-level criteria, some structures with outlet drops < 15 cm ranked highly for remediation under the former criteria, but had no remediation value under the latter.
A primary lesson from this effort is the importance of making priorities on the basis of transparent and explicit criteria and management objectives. Selection of thresholds of culvert elevation or current velocity to assess a culvert as likely impassable clearly affects outcomes of the prioritization process; however, there is considerable uncertainty about how culverts impede passage by aquatic organisms. The ability of fish to pass through road crossings is generally assumed to depend on species-specific swimming and leaping abilities, and the timing of the movement relative to flow conditions (Coffman 2005; Bourne and others 2011). Although any plausible criteria may place high priority on remediating structures that provide little possibility of passage even to strong swimmers and that fragment large areas of habitat (Bourne and others 2011), some criteria may fail to identify opportunities to reconnect substantive habitat areas for smaller species. For the case study presented here, the species of special concern span adult sizes of about 5 to 10 cm. Criteria that allow some probability that an embedded culvert with moderate velocities may impede passage (such as the three-level criteria) may be more appropriate for smaller or benthic species, whereas requiring an outlet drop to consider a culvert a barrier could be more appropriate in reconnecting habitat for larger, stronger swimmers (Coffman 2005). Thus, the choice of criteria for assessing culvert impassability may reasonably differ depending on management objectives, e.g., increasing overall network connectivity (Cote and others 2009; Diebel and others 2010) or reconnecting habitat for specific species (as in the Upper Coosa River example). The swimming ability of non-game and small-bodied fishes has received less attention than game fishes, and estimates may vary depending on the experimental design of the study (Coffman 2005). Validating criteria for impassability for stream fishes and other aquatic organisms will be essential and may require, e.g., long-term assessments of movements (Norman and others 2009) or analyses of genetic variation among putatively fragmented populations (Neville and others 2006) in relation to stream culverts across a range of outlet drops and velocities to test hypotheses about what structures substantially fragment populations (Kemp and O’Hanley 2010). In the interim, managers who need information on actions most likely to benefit imperiled species will necessarily use models based on uncertain relations. For that reason, it is useful from the outset to understand the sensitivity of prioritization schemes to underlying assumptions.
The approach illustrated in this study was designed to allow managers to incorporate new information pertaining to model assumptions as it becomes available. For example, we have assumed that all streams above a minimum threshold size within an occupied HUC12 have the same probability of being occupied. Although watershed size has been shown to account for much of the variance within species distributions, other parameters including land use characteristics (Wenger and others 2008), downstream link (Osborne and Wiley 1992), and stream slope (Walters and others 2003) can be equally, if not more predictive. Several of the species of concern from this study have been shown to have distributions that are influenced by land use characteristics (e.g., impervious area, forest cover; Wenger and others 2008); the prioritization strategy used here could incorporate these characteristics, e.g., by using land use or modeled habitat quality to weight potentially reconnected stream kilometers according to habitat value. Additionally, our prioritization strategy assumes that culverts that block access to larger areas for these species have not been over-looked; our sampling approach aimed to minimize this possibility, but visiting each of the road crossings (n > 9900, including bridges) in the project area was beyond the scope of this project. Obviously, new information on species ranges, occurrence data for newly considered species, or data on additional culverts could be incorporated directly into the spatial database to modify prioritizations.
Our prioritization strategy did not account for differential costs among culverts for replacement or remediation, or other potential benefits (e.g., improving public safety or lowering maintenance costs by replacing problematic structures). Similarly, for illustration, we have weighted all species of concern equally in calculating culvert priority ranks, whereas resource managers may wish to weight species differently, depending on conservation objectives or degree of imperilment. Where spread of non-native species are of concern, maintaining culverts that block passage could become a priority (Fausch and others 2009). Other considerations including costs of remediation (O’Hanley and Tomberlin 2005), or age of the structure could be directly incorporated into prioritizations. Finally, whereas we have only ranked culverts by remediation benefit, the approach of estimating habitat gain by incorporating culvert position relative to upstream and downstream barriers could be used to optimize culvert remediation (O’Hanley and Tomberlin 2005; Kemp and O’Hanley 2010), incorporating decisions regarding species priorities and variation in resource availability or opportunities afforded by partners.
The prioritization scheme developed here for culvert remediation may provide a useful starting point for incorporating habitat connectivity for particular species into decisions for allocating limited road maintenance and conservation dollars. Our case study suggests that research on the extent to which small drops and high water velocity actually fragment populations (e.g., using genetic or movement studies) could narrow uncertainty that affects management choices for culvert remediation. Until such information becomes available, assessments that explicitly incorporate uncertainty in how culvert characteristics relate to impassability, as in the case of the BBNs illustrated here, could help managers more realistically estimate potential habitat gain by accounting for potential occasional passage at less restrictive barriers while also identifying severe barriers. Managers weighing other considerations, such as stakeholder support and project costs, or needs to improve habitat for particular critically imperiled species, may wish to compare degree of uncertainty in culvert impassability among restoration options and for differing criteria sets. Given the conservation emphasis on restoring connectivity for stream organisms and the accompanying uncertainty in identifying culverts as impassable, prioritization approaches that explicitly examine effects of uncertainty on expected outcomes may support better-informed management choices in addition to identifying research that could have the greatest effect in narrowing management uncertainty.
Many thanks to those who helped conduct field sampling: Christina Baker, Bill Bouthiller, Jeffery Garnett, Jason Hunt, Rachel Katz, Jason Lang, Sam Miles, Amanda Neese, James Norman, Nicole Pontzer, and Randy Singer. We also thank Brett Albanese and Katie Owens for supplying us with an impoundment layer for the Coosawattee River system. Brenda Rashleigh, William Fisher, Joe Anderson, Frank Dirrigl, Jr. and an anonymous referee provided insightful comments and helpful suggestions on an earlier version of the manuscript. Funding for this research was provided by a grant from the U.S. Fish and Wildlife Service. Use of trade, product, or firm names does not imply endorsement by the U.S. Government. The Georgia Cooperative Fish and Wildlife Research Unit is sponsored by the U.S. Geological Survey, the U.S. Fish and Wildlife Service, the Georgia Department of Natural Resources, the University of Georgia, and the Wildlife Management Institute.