Mapping the Potential Distribution of the Invasive Red Shiner, Cyprinella Lutrensis (Teleostei: Cyprinidae) Across Waterways of the Conterminous United States

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Aquatic Invasions (2012) Volume 7, Issue 3: 377–385 doi: http://dx.doi.org/10.3391/ai.2012.7.3.009 Open Access

Research Article

Mapping the potential distribution of the invasive red shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States

Helen M. Poulos1*, Barry Chernoff 2, Pam L. Fuller3 and David Butman4 1 College of the Environment, Wesleyan University, Middletown, CT 06457, USA 2 Departments of Biology and Earth and Environmental Studies, Wesleyan University, Middletown, CT 06547, USA 3 USGS, Nonindigenous Aquatic Species Program, Southeast Ecological Science Center, Gainesville, FL 32653, USA 4 Yale School of Forestry and Environmental Studies, New Haven, CT 06511, USA E-mail: [email protected] (HMP), [email protected] (BC), [email protected] (PLF), [email protected] (DB) *Corresponding author

Received: 1 September 2011 / Accepted: 26 April 2012 / Published online: 9 May 2012

Abstract

Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion. Key words: invasive fishes; maximum entropy; Cyprinella lutrensis; species distribution modeling

Introduction Forecasting the potential geographic distribution of aggressive invaders is a crucial component of Alien invasive fishes have contributed to the habitat conservation. Species distribution global decline in stream fauna through predation, modeling (SDM) offers a method for generating competition, and hybridization (Miller et al. spatially explicit information to prioritize 1989; Allendorf et al. 2001). The number and invasive species management efforts by rate of new introductions have increased identifying habitats that are likely to be invaded. dramatically since the 1950s through the Recent advances in geographic information propagation and transportation of species around systems (GIS), data mining methods, and data the world (Fuller et al. 1999). Predicting the availability have lead to the proliferation of a future spread of non-native aquatic species wide array of SDM approaches. continues to be a high priority for natural Maximum entropy (Maxent) is a high resource managers striving to maintain performing SDM method that uses species biodiversity and ecosystem function. Invasive occurrence and environmental data for predicting species can have myriad impacts on native potential species distributions (Phillips et al. aquatic community structure including reducing 2006; Elith et al. 2006). Maxent is a machine- native species diversity and abundance (Gordon learning algorithm that compares presence 1998; Wilcove et al. 1998, 2000), modifying locations to environmental variables at those hydrology (Ricciardi and MacIsaac 2000) and locations and then across the study region to nutrient cycling (Simon and Townsend 2003; generate predictions of species distributions in Strayer 2010), and altering food web dynamics un-sampled locations. It has performed well for (Baxter et al. 2004; van Reil et al. 2006). mapping invasive species (Ward 2007; Stohlgren

377 H.M. Poulos et al. et al. 2010; Jarnevich and Reynolds 2011), degraded habitats, including low or intermittent although Maxent has not been used extensively flows, excessive turbidity and sedimentation, and for predicting the potential habitat of aquatic natural physiochemical extremes, which are invaders (but see Kumar et al. 2008; Oliviera et conditions eschewed by many native minnows al. 2010; Feria and Faulkes 2011; Poulos et al. (Cross 1967; Sublette 1975; Matthews and Hill 2012). 1979; Baltz and Moyle 1993; Douglas et al. We used Maxent software to model the 1994). Red shiners are generally uncommon or potential distribution of a widely distributed absent from upland, clear water streams having invasive minnow, the red shiner (Cyprinella moderate or high species richness (Matthews and lutrensis Baird and Girard, 1853). This species is Hill 1979; Matthews 1985; Yu and Peters 2002). a hardy cyprinid that thrives in a wide range of This species can tolerate extreme thermal shock habitats (Marsh-Matthews and Matthews 2000). ranging from -21 to 10°C, as well dissolved Red shiner invasion outside its native range has oxygen as low as 1.6 ppm (Matthews and Hill caused major shifts in fish assemblage structure 1977), and it has been observed in hot springs through competition and extensive hybridization with temperatures as high as 39.5°C (Brues with native congeners (Hubbs and Strawn 1956; 1928). Heckman et al. 1987; Karp and Tyus 1990). We chose to model potential red shiner distribution Presence records because of the threat it poses to native fish diversity and ecosystem structure. We compiled spatial red shiner occurrence data The red shiner is native to the Great Plains, from within its native range using records from American southwest, and Mexico in tributaries the Sam Noble Museum of Natural History in of the middle and lower Mississippi River basin, Oklahoma, the Kansas Aquatic Gap Database, and Gulf of Mexico drainages westward to the the Fishes of Texas Project, the Texas Natural Rio Grande, including several endorheic basins History Collection, the Illinois Natural History in Mexico (DFC 2010). Red shiners have been Survey Fish Collection, and the Tulane Univer- widely introduced outside their native range sity Museum of Natural History (1000 native primarily through bait bucket (Hubbs and Lagler records total). Records from within the species’ 1964; Jennings and Saiki 1990; Walters et al. invaded range (133 non-native records) were 2008) and aquarium releases (Moore et al. 1976; taken from the Nonindigenous Aquatic Species Jenkins and Burkhead 1994). Initial introduction (NAS) database (http://nas.er. usgs.gov) (Figure is often followed by the species' rapid population 1). We included both native and non-native growth, dispersal, and aggressive colonization records in our modeling effort because it (Hubbs and Lagler 1958; Minckley and Deacon encompassed the most comprehensive estimation 1968; Minckley 1973). Where introduced, red of red shiner’s ecological niche. Ibañez et al. shiner can dilute the gene pools of native (2009) highlighted the utility of this approach for Cyprinella via hybridization (Mettee et al. 1996; modeling the potential distribution of alien Fuller et al. 1999), and it has also affected the invasive plants and Wolmarans et al. (2010) distribution and abundance of native fishes demonstrated that modeling invasive species including spikedace (Meda fulgida Girard, distributions using records from a species’ native 1856), woundfin (Plagopterus argentissimus and invaded range did not significantly affect Cope, 1874), and Virgin River chub (Gila model performance or result in overfitting. seminude Cope and Yarrow, 1875) (Moyle 1976; Deacon 1988) through various mechanisms Environmental data including larval predation and direct competition We derived a set of 20 raster-based climatic, for habitat use. topographic, and spectral habitat predictor variables from a range of raster data sources (Table 1) in order to explore the environmental Methods influences on species distribution patterns across the continental United States. We chose these Species biology candidate environmental predictors based on Red shiners are habitat generalists, primarily their relevance to riparian systems and their occurring in creeks and small rivers. They are biological importance to red shiner. For example, tolerant of harsh environmental conditions and both summer temperature and summer

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Figure 1. Map of Red Shiner presence locations used in the Maxent model. The native distribution of Red Shiner (NatureServe 2010) is shown in dark gray.

Table 1. Environmental predictor variables evaluated for inclusion in the red shiner species distribution models, their native spatial resolution, and data sources. Variables marked with asterisks were those that were included in the final Maxent model. Native spatial Predictor variables Description Source resolution Ppt* mean precipitation 1980-1997 1 km Daymet1 Tmax mean maximum air temperature 1980-1997 1 km Daymet1 Tmin* mean minimum air temperature 1980-1997 1 km Daymet1 Jantmin mean minimum air temperature of the coldest month 1 km Daymet1 Augtmax* mean maximum air temperature of the hottest month 1 km Daymet1 Sumprecip average summer precipitation 1 km Daymet1 Summheat* summer heat: (mean warmest month temperature)/(mean 1 km Daymet1 summer precipitation/1000) RH relative humidity 1 km Daymet1 Frostdays number of frost days 1 km Daymet1 Upstream flow flow length toolbox in ArcGIS 30 m National Hydrography Dataset2 Downstream flow* flow length toolbox in ArcGIS 30 m National Hydrography Dataset2 Flow accumulation* flow accumulation from ArcHydro extension of ArcGIS 30 m National Hydrography Dataset2 Watershed slope* slope of the watershed in degrees 30 m National Hydrography Dataset2 Downslope elevation calculated as the difference between a cell’s elevation in 30 m National Hydrography Dataset2 change* meters and the lowest elevation Stream power index erosive power of overland flow measured as the area of 30 m National Hydrography Dataset2 the catchment area multiplied by the tangent of the slope calculated using Whitebox Geospatial Analysis Tools (Lindsay 2009) Upslope neigh number of upslope neighbors 30 m National Hydrography Dataset2 Sed trans sediment transport capacity index (Burrough and 30 m National Hydrography Dataset2 McDonnell 1998) Impervious % impervious surfaces 30 m USGS3 Baseflow* baseflow index grid from USGS stream guages, expressed 30 m USGS3 as percentage of baseflow relative to total flow Saturation overland estimated by TOPMODEL (Beven and Kirkby 1979) Vector USGS3 flow* dataset data sources: 1Daymet: http://www.daymet.org 2National Hydrography Dataset: http://www.horizon-systems.com/nhdplus 3United States Geological Survey (USGS): http://landcover.usgs.gov/usgslandcover.php

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precipitation were included in the analysis deviations of the 25 runs following Jarnevich because this species is distributed across some of and Reynolds (2011). We also displayed the the hottest and driest parts of the United States. model prediction results across US hydrologic Grids were clipped to the extent of the USGS units (USGS 8-digit HUC units) because of their hydrography dataset to avoid modeling fish value to managers for assessing red shiner distributions outside riparian areas (USGS 2003). invasion potential following DeVaney et al. We also resampled each grid to 1 km from its (2009). The potential distribution of red shiner in native spatial resolution, which ranged from 30 each HUC unit was displayed using a suitability m to 1 km using ArcMap v9.3 (ESRI 2008). We threshold to derive projected presence-absence chose this resolution based on our intent to distributions from the logistic outputs. The thres- model national-scale species distributions and hold indicating maximum training sensitivity because it was the coarsest native resolution of plus specificity is considered a robust approach any single dataset. (Lui et al. 2005), so we used it to conduct the The entire dataset of raster predictor variables conversion into presence-absence predictions. was reduced through pairwise evaluation to Maxent evaluates model performance by reduce multi-collinearity among the predictors as calculating the area under the curve (AUC) of suggested by Elith et al. (2010). We followed the receiver operating characteristic plot. The methods outlined by Stohlgren et al. (2010), AUC is a threshold-independent measure of which used the correlation matrix as a means of model performance that ranges from 0 to 1. identifying highly correlated pairs of habitat Values > 0.9 indicate high accuracy, values of predictors (r > 0.7). For correlated pairs, we 0.7-0.9 indicate good accuracy, and values below removed the variable that captured less 0.7 indicate low accuracy (Swets 1988). Average information. For example, if January minimum AUC values for the 25 runs were reported. temperature and mean minimum temperature were highly correlated, we kept mean minimum temperature since it captured a longer record of Results winter temperature as a whole. Model performance Species distribution modeling The average testing AUC value across the 25 Maxent uses a deterministic algorithm that finds iterations of the Maxent model was 0.86 (SD = the optimal probability distribution (potential 0.009). August maximum temperature, summer distribution) of a species across a study area precipitation, and summer heat were the most based on a set of environmental constraints. important predictors of potential red shiner Maxent determines the best potential distribution habitat (Table 2). Baseflow, mean minimum by selecting the most uniform distribution temperature, and down slope elevation change subject to the constraint that each environmental were other minor environmental predictor variable in the modeled distribution matches its variables. empirical average over the known distributional Maxent predicted that red shiner was capable data (i.e. presence data). Maxent is sensitive to of spreading well outside its native range (Figure sampling biases in clustered or disparate datasets 2). In the West, red shiner could spread such as the one we use in this study. We throughout all of the major California river addressed this issue by limiting the spatial extent systems, the Snake River in Idaho, the Gila, from which Maxent could select background Snake and Santa Cruz rivers in Arizona, and in points to locations within 50 kilometers of an Nevada it could invade the Carson and Humboldt existing red shiner record (sensu Jarnevich and rivers, and tributaries of the Colorado River. Our Reynolds 2001). model predicted that this species could colonize We ran each model by randomly dividing many rivers in the southeastern US including all occurrence data into training and testing datasets of the major rivers in Mississippi and Alabama, (70% and 30% of localities, respectively). We the headwaters of the major river systems in produced maps for the conterminous US Georgia (Altamaja, Oconee, Ocmulgee, and Flint averaged across 25 model runs with random sub- rivers) and South Carolina (Savannah, Saluda, setting of the data at each iteration, including a Brood, and Catawba Rivers), and the Peedee, map of suitable habitat and a map of the standard Haw, and Tar rivers in North Carolina. The

380 Mapping the potential distribution of the invasive red shiner

Figure 2. Maxent results for red shiner including A) the habitat prediction map, and B) the standard deviation among the 25 model iterations using different subsets of point data to test for model sensitivity to presence locations, and C) the presence-absence habitat prediction map for each hydrologic unit (USGS 6-digit HUC) in the United States. The threshold for conversion to binary predictions was derived using the maximum sensitivity plus specificity criterion. The native distribution of C. lutrensis is shown in gray.

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Table 2. Relative contribution of the environmental variables to the Maxent model. Percent Contribution reports the gain of the model by including a particular variable at each step of the Maxent algorithm The permutation importance reports the contribution for each variable to the final Maxent model which is determined by randomly permuting the values of that variable among the training points (both presence and background) and measuring the resulting decrease in training AUC. The percent contribution and permutation values are normalized to percentages.

Permutation Environmental predictor % contribution AUC with just this variable importance Augtmax 59.7 49.1 0.80 Summer precipitation 13.9 14.2 0.67 summer heat 11.3 12.2 0.63 Baseflow 5.9 4.4 0.72 Tmin 2.7 3.7 0.72

Figure 3. Environmental response curves for variables contributing greater than 5% to the red shiner model. Red lines indicate mean values for the 25 iterations of the Model. Blue shading indicates the range of environmental values of the 25 iterations of the model.

model also predicted that red shiner could spread (Figure 3). Rivers with high August maximum eastward from its native range into western temperatures, annual minimum temperatures, and Kentucky and Tennessee. summer precipitation had a high red shiner The environmental response curves for red potential distribution. Locations with high shiner were consistent with this species’ baseflow were also more likely to be within the biological tolerances and habitat preferences potential distribution of red shiner.

382 Mapping the potential distribution of the invasive red shiner

Discussion rubrofluviatilis Fowler, 1916), Colorado pikeminnow (Ptychocheilus lucius Girard, 1856), The wide potential distribution of red shiner spikedace (Meda fulgida Girard, 1856), and across the United States demonstrates its razorback sucker (Xyrauchen texanus Abbott, adaptation as a site generalist, which facilitates 1861), most of which are endangered. It is a its success in newly invaded habitats. This well-known consumer of larval fish and it is an species is the most thermotolerant minnow in opportunistic drift feeder (Sublette 1975). The North America (Brues 1928; Matthews and Hill displacement of native cyprinids by red shiner is 1979), and our maps suggest that red shiner has also well documented. For example, Douglas et the potential to spread to other hot environments al. (1994) demonstrated that biotic interactions in the United States. The predicted habitat is between spikedace and red shiner involved consistent with the wide-ranging habitat associ- interference competition for space, and that ations of red shiner in its current native and spikedace were displaced to less favorable invaded ranges (Marsh-Matthews and Matthews habitats in the presence of this invader. Mooney 2000). Sites with mean minimum temperatures and Cleland (2001) suggested that such niche above freezing, high mean maximum summer air displacement of natives by exotic fishes can have temperatures, and a high summer heat index major evolutionary consequences on native (August temperature/summer precipitation) are populations and in some cases invasive potential sites for invasion by red shiner. competitiveness can lead to native fish extinction The potential spread of this species both (Ricciardi and Rasmussen 1998; Ricciardi et al. eastward and westward beyond its native and 1998). currently invaded ranges could threaten the Potential distribution maps like the red shiner stability of native US minnow populations with map produced in this study can be used by similar habitat requirements because of red resource managers for rapid response and early shiner’s ability to outcompete (Greger and mitigation of non-native fish invasion. Prohi- Deacon 1988) and hybridize with natives (Burr biting the sale of red shiner as bait or aquarium and Page 1986; Larimore and Bayley 1996). fish in highly susceptible areas is one potentially Overlaps in the potential distribution of red effective method for reducing the risk of new shiner and native minnow species richness occur introductions to sensitive habitats (Keller and predominantly in the western United States, with Lodge 2007) as is limiting urban sprawl as a the areas of highest minnow diversity and red means of minimizing the availability of disturbed shiner habitat suitability occurring in Arizona, habitat since this species does well in such New Mexico, and southern California locations. While commerce remains a top policy (NatureServe 2004). This suggests that cyprinid priority for lawmakers (NISC 2008), restricting congeners in these areas may be the most heavily the movement of known aggressive invaders in impacted by red shiner spread. Walters et al. highly vulnerable regions could protect (2008) demonstrated that red shiner success can uninvaded habitats from experiencing major be facilitated through introgression in locations shifts in ecosystem structure as a result of new where congeners are present. Red shiner species introductions. establishes first in locations with congeners, and then its subsequent expansion is driven primarily by hybrid minnows into new habitats. Limiting Acknowledgements new introductions by prohibiting red shiner sales as aquarium and bait fish in these regions could The authors wish to thank Michael Retzer of the Illinois Natural History Survey Fish Collection, Alexandra Snyder of the Museum lower the risk of red shiner introduction and of Southwestern Biology, Adam Cohen of the Texas Natural hybridization with native species. History Collection, Keith Gido from Kansas State University, Red shiner expansion could also have large- Hank Bart Jr. at Tulane University, and Edith Marsh-Matthews of scale impacts on the abundance and distribution the Sam Noble Oklahoma Museum of Natural History for providing red shiner distribution data. They also thank Dr. Jane of other native fishes because of its negative Elith, Dr. Noel Burkhead, and one other anonymous reviewer influences on native larval fish survival (Ruppert from USGS for helpful comments on this manuscript. Support for et al. 1993; Douglas et al. 1994; Gido et al. this project was provided by a grant from the Mellon Foundation 1999; Marsh-Matthews and Matthews 2000) and and support for Environmental Studies by Robert Schumann. Any use of trade, product, or firm names is for descriptive purposes habitat use (Douglas et al. 1994). Red shiner only and does not imply endorsement by the U.S. Government. occupies nursery habitats of young native fishes including the Red River pupfish (Cyprinodon

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