Multiple Stressors in River Ecosystems 23 # 2019 Elsevier Inc

CHAPTER 2

Climate Change and Interactions With Multiple Stressors in Rivers

Sherri L. Johnson, Brooke E. Penaluna US Forest Service, Pacific Northwest Research Station, Corvallis, OR, United States

2.1 INTRODUCTION

Freshwater ecosystems have been subjected to multiple stressors over time (Fausch et al., 2010; Ormerod et al., 2010; Strayer and Dudgeon, 2010; Malmqvist and Rundle, 2002). Most rivers have been physically modified by humans, with only a few large rivers remaining free flowing (Nilsson et al., 2005). Although rivers and streams provide drinking water to millions of people, these same systems have historically been used as drainage systems, for transpor- tation and as a way to get rid of waste and pollutants. Exotic or nonnative species have been introduced to the majority of freshwater systems, which has shifted trophic dynamics in many river networks. In addition to these existing multiple stressors (Chapter 1), river ecosystems are also being impacted by climate change. Our changing climate is presently affecting rivers around the globe (Milly et al., 2005; van Vliet et al., 2013). Global circulation patterns are fluctuating, air temperatures are increasing, glaciers are melting, sea levels are rising, and precipitation patterns are shifting (IPCC, 2014). Because climate change is affecting habitat quality, species thermal tolerances, rates of ecosystem processes and phenological cues, researchers are therefore stretched to quantify drivers and responses in ecologically relevant ways. The identification of long-term trends in rivers systems are complicated by changes in land use, land cover, and/or water demands. Hydrologists are conducting modeling at global to local scales to try to predict the magnitude, timing, and duration of changes in temperature and precipitation. Aquatic ecologists are working to predict future responses across species to ecosystems and to chronic responses to existing change (Chapter 3). In this chapter, we discuss examples of projected changes in hydrology and stream temperature associated with a changing climate. We compare the mechanisms of and responses to existing multiple stressors with those predicted to solely occur as a result of climate

Multiple Stressors in River Ecosystems 23 # 2019 Elsevier Inc. All rights reserved. https://doi.org/10.1016/B978-0-12-811713-2.00002-9 24 2. CLIMATE CHANGE AND INTERACTIONS dynamics. We also discuss a range of net cumulative responses to multiple stressors and climate change. As a case study, we highlight examples of responses to a drought in a river scape with multiple stressors; drought is a surrogate for the predictions of increased magnitude and duration of low flows across continents from climate change.

2.2 OBSERVATIONS AND PREDICTIONS OF CLIMATE CHANGE IN RIVERS

The climate of Earth is being exposed to increased carbon dioxide and other gases. Air temperatures are increasing, while precipitation patterns, seasonality, and magnitude are shifting (IPCC, 2014). With increased air temperatures, evapotranspiration and the water holding capacity of the air also increase. This leads to precipitation events that deliver more moisture and are predicted to become more intense (Diffenbaugh et al., 2017), which leads to higher peak flows and increased risk of flooding (Trenberth, 2011; Taye et al., 2011; van Vliet et al., 2013). In areas with historic winter snowfall, higher temperatures are predicted to shift precipitation from snow to rain, which can lead to higher winter flows. Where there is earlier snowmelt, lower flows are expected the following summer. Extreme droughts and low flows are also broadly expected to become more common in many ecosystems (Diffenbaugh et al., 2017; Milly et al., 2005). Although a global phenomenon, climate change will have more im- mediate effects in some regions and types of ecosystems than in others (Fig. 2.1, IPCC, 2014; van Vliet et al., 2013)(Chapter 7).

2.2.1 Disentangling the Effects of Climate Change From Other Stressors in Rivers

Direct observations of climate impacts on rivers are challenging to disentangle from the concurrent changes in other factors that also affect runoff and water temperature. Because large numbers of rivers have had changes in land use and riparian vegetation cover, modi- fications to channel morphology, damming, and increased water extraction, clear identification of changes to discharge and water temperature that can be attributed only to climate change are limited (Arismendi et al., 2012; Argerich et al., 2013). Knowing the landscape history is essential when trying to disentangle trends associated with land use and multiple stressors from factors associated with climate change. The identification of climate impacts to rivers using changes in trends over time requires two things: (a) long-term data that have been collected consistently, and (b) landscapes or river networks where human-related disturbances have not substantially impacted the long-term record. In many regions, it is challenging to find a river that has not been influenced by multiple anthropogenic stressors (Chapters 8 and 9). Remote rivers and headwater forested rivers that have been protected are often the best options. The history of land use can be used to identify minimally impacted or reference sites (Falcone et al., 2010). To tease apart the effects of human impacts on runoff from those potentially deriving from climate change, Milly et al. (2005) compared observed trends in the annual mean runoff from predictions using an ensemble of global climate models (GCMs) for the same time periods. They concluded that a significant portion of the change in the 20th century was related to 2.2 OBSERVATIONS AND PREDICTIONS OF CLIMATE CHANGE IN RIVERS 25

FIG. 2.1 Change in average surface air temperature (A) and change in average precipitation (B) based on multimodel mean projections for 2081–2100 relative to 1986–2005 under the RCP2.6 (left) and RCP8.5 (right) scenarios. The number of models used to calculate the multimodel means is indicated in the upper right corner of each panel. Stippling (i.e., dots) shows regions where the projected change is large compared to natural internal variability and where at least 90% of the models agree on the sign of the change. Hatching (i.e., diagonal lines) shows regions where the projected change is less than one standard deviation of the natural internal variability. From Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Figure SPM.7) [Core Writing Team, Pachauri, R.K. and Meyer, L. (Eds.)]. IPCC, Geneva, Switzerland. climate change and that larger changes are to be expected in the future. Safeeq et al. (2013) focused on unregulated watersheds in the western United States to evaluate changes in multiple metrics of runoff over time. They noted the influence of geologic and watershed-specific characteristics that drive responses to changes in climatic variables; for example, snow- dominated systems showed declining trends in summer runoff ratios over time while rain-dominated basins exhibited less consistent trends. In northern Canada, Dery et al. (2016) observed no trends in annual discharge for specific rivers, but for the average across all the sites, they observed a declining trend in discharge. Studies have identified trends of earlier snow melt in alpine rivers as well as those with a strong snowmelt hydrograph. Zampieri et al. (2015) observed an earlier spring peak discharge in the Rhine, Danube, and Rhone rivers. In the Mackenzie River of northern Canada, Yang et al. (2015) showed that snowmelt peaks had advanced by several days over 26 2. CLIMATE CHANGE AND INTERACTIONS four decades. They also noted decreases in maximum spring flows and an increase in cold season (winter) base flow, all of which they attributed to climate variations and changing proportion of precipitation falling as rain instead of snow. Similarly, Ashraf et al. (2016) compared runoff in regulated versus pristine forested river networks in the subarctic. Using In- dicators of Hydrologic Alteration (IHA, Richter et al., 1996), they found significant changes in flow, including increases in winter flow and increases in minimum flows that they attributed to climate change and climate variability. They also noted that flow regime alternations were not apparent using monthly data, but daily data showed significant changes. The length of record, specifically the beginning and end time periods of data used in an evaluation, can also influence the magnitude of trends (Hodgkins, 2013). Several analyses of historical records have reminded us that trends over time are not necessarily unidirectional (Argerich et al., 2013; Tananaev et al., 2016). As additional years were added into an analysis of trends in discharge and nitrogen from reference forested watersheds across the United States, trends changed in significance and direction. Some trends showed decreases for certain periods but not others, and increasing trends also shifted at other sites (Argerich et al., 2013). In the Lena River in northern Eurasia, Tananaev et al. (2016) noted general increases in the annual mean and minimum discharge and found abrupt changes in trends of flows during the 1990s and 2000s, where the basin is underlain by permafrost. As with discharge, it is challenging to determine the current magnitude of impact of climate change on stream temperatures (Webb, 1996). Finding consistent, long-term stream temperature data for unimpacted streams and rivers is difficult. In addition, shifts in instru- mentation over time can compromise our ability to evaluate temporal trends in temperature. Current methods for measuring stream temperatures have a much higher resolution than what was common in the past. Increases in air temperature and decreases in summer streamflow have been projected to result in increased stream temperature. Although stream water temperatures generally increase when discharge decreases (Arismendi et al., 2013b; van Vliet et al., 2013), that is not always the case (Webb and Walling, 1993). Where glacial melt is providing the majority of streamflow, summer daytime streamflows increase, and water temperatures are colder than in streams dominated by other types of flows (Milner et al., 2009; Brown et al., 2007). Another example of an exception to increased temperatures at a reduced baseflow are streams with groundwater inputs. As summertime discharge declines, the temperatures can get cooler in these types of streams because the proportion of flow shifts from being dominated by surface flows to being dominated by groundwater (Safeeq et al., 2014). Fine scale patchy temperature distributions are most likely to occur during low flow; cold water refugia can occur at tributary junctions even when surface flows have ceased in the tributaries (Ebersole et al., 2015). Some studies have noted trends over time in stream temperatures and attributed them to changing climate, but they were unable to unable to identify whether there were land use or riparian cover changes during the study periods (Arora et al., 2016; Kaushal et al., 2010; Isaak et al., 2012; Soto, 2016). Others have used air temperature over time as a surrogate of stream temperatures (Durance and Ormerod, 2007); these may overestimate or underestimate stream temperature trends. In the Arctic, where land use changes over time were not an influence, Park et al. (2017) noted a trend of increased river temperatures of 0.16oC per decade. Arismendi et al. (2012) calculated monthly metrics for minimally human-influenced forested sites in the northwestern United States and observed that sites with longer time series showed increasing temperature trends, while sites with more recent data did not show the same trends. 2.2 OBSERVATIONS AND PREDICTIONS OF CLIMATE CHANGE IN RIVERS 27 2.2.2 Modeling Future Scenarios of Precipitation and Runoff

Changes in future annual precipitation and runoff are being modeled for many regions using ensembles of GCMs. Models show a wide range of projected changes in precipitation across regions and time periods (IPCC, 2014; Milly et al., 2005). Models of runoff under future climate scenarios build on models of precipitation, but become more complex through incor- porating temperature dynamics, radiation inputs, vegetation type, and uptake of water (Cai and Cowan, 2008; Taye et al., 2011). At a very coarse scale, precipitation and runoff are predicted to be spatially variable, with high latitudes and the equatorial region (RCP8.5 model) showing increases and mid latitudes showing patchy areas with decreases (IPCC, 2014; Milly et al., 2005; Fig. 2.1). Large-scale and annual metrics are commonly used for both predicting change and for summarizing metrics of current conditions. An analysis of change in flow regimes across the United States (Dhungel et al., 2016) highlighted that shifts in regimes are more likely in some regions than others, and fine-scale spatial and temporal resolutions of timing, magnitude, duration, and frequency (Richter et al., 1996; Arismendi et al., 2013a) will be the most relevant scales for predicting responses and ecosystem processes (Chapter 16). Modeling annual metrics can mask the severity or variability of climate impacts within the year. Faramarzi et al. (2013) predicted increased mean total water resources in Africa with climate change, but also predicted an increase in the number of dry days and the duration of drought. Similarly for the northwestern United States, if annual precipitation changes but arrives during fewer but more intense rain events, there could be an increase of both floods and a longer duration of low flows at sites (Mantua et al., 2010; Wu et al., 2012). In an urban portion of a desert region, models predicted decreases of annual precipitation in the future, but extreme storms for that region were expected to be more intense (Acharya et al., 2013). Using an ensemble of climate model scenarios, they expect that extreme storm events will result in large changes to streamflow (varying from increases of 40% to 150% in peak and total runoff ) in the future. Even if the total amount of precipitation does not change, changes in the form or timing of precipitation could have implications for river hydrographs. For example, in regions that currently get the majority of their precipitation as snow, projected changes to the form of precipitation (e.g., from snow to rain) could increase stream flows during the winter, as well as have the potential effect of decreasing flows the following spring and summer (Shrestha et al., 2012; Mantua et al., 2010; Barnett et al., 2005; Mote et al., 2005). Other regions are also predicted to have longer periods and lower summer flows (Papadaki et al., 2016). Decreased summer flows and shifts in timing of precipitation within the year could impact the habitat and key phenological responses of biota. Alternatively, it is possible that changes in timing of the precipitation within a year associated with climate change could dampen hydrologic extremes across the seasons and lead to more consistent aquatic habitats. Each GCM includes assumptions about future climate, and using an ensemble of GCMs can lead to wide variability in predicted outcomes. The high uncertainty and variability are challenging aspects of predicting river responses to changes in climate at all biomes (Wenger et al., 2013). Zhang et al. (2015) modeled monthly hydrology in future scenarios for the Yellow River of China. Although some months in all scenarios showed low relative changes in precipitation, for other months, model scenarios showed high variability among GCMs. The maximum relative increase in precipitation within a month ranged 28 2. CLIMATE CHANGE AND INTERACTIONS from 10% to 50%. The relative change in runoff had even less concurrence. For example, in 1month, a certain model suggested 15% decrease in runoff, while other models predicted 25% and 40% increases. Shrestha et al. (2012) noted more concurrence in the direction of change in runoff among future model scenarios for the Frasier River Watershed, Canada. However, they still observed differing predictions among GCM scenarios. Taye et al. (2011) also observed a wide variability of hydrologic responses using an ensemble of models for the Nile Basin. This divergence among model scenarios is partially a result of challenges in modeling complex feedbacks between air temperature, the water holding capacity of the air, the jet stream patterns that transport moisture laden air, evapotranspiration, soil moisture, and interactions between precipitation, clouds, and radiation (IPCC, 2014). The spatial variability of predictions has also been noted. Raje et al. (2014) used an ensemble of GCMs for the macroscale modeling of runoff in India. They projected an increasing trend in runoff during the summer monsoons in the central river basins of India, but a decrease in the runoff for southern India. They also noted high uncertainty and key differences arising from the GCMs and scenario variability. Shrestha et al. (2012) also noted spatially variable responses and projected the shifting of hydrologic regimes across the Fraser River basin in future scenarios. Forecasting species responses to changes in hydrology under future climates has consid- erable uncertainty, a portion of which is a function of the uncertainty of magnitude and direction of hydrologic changes under future climates (Wenger et al., 2013). Studies have documented species responses to changes in low flows; Kovach et al. (2015) provide one overview. They noted that Brown Trout (Salmo trutta) and Brook Trout (Salvelinus fontinalis) showed a strong relationship between summer streamflow and demography and between streamflow and growth (Kovach et al., 2015). They found few studies that had time series data of responses to flow that could be attributed to climate change. Observations of responses to high flow suggest that the timing of the flow event relative to the life stage of the fish is a major determinant of response (Pearsons et al. 1992). Other studies have modeled responses of biota (Penaluna et al., 2015; Woodward et al., 2010)ortheirhabitat (Papadaki et al., 2016) to changes in flow under changing climate. Wenger et al. (2011) suggested that climate change impact on flow is also having a noticeable effect in altering fish distributions. Additionally, phenological shifts have been reported by Kovach et al. (2013); one such example is where changes in flow and water temperature were concurrent (Arismendi et al., 2013b). Overall, hydrologic models of future climate predict changes in discharge, shifts in timing, and an increase in extreme events, both peak flows and low flows. However, the timing, magnitude, and duration of projected changes in precipitation and runoff show high variability among current ensembles of GCMs.

2.2.3 Modeling Future Scenarios of Stream Temperatures

General circulation models (GCMs) generally predict that the high latitudes in the northern hemisphere will experience the greatest increases in air temperatures in the future (Fig. 2.1). There is a much greater concurrence across ensembles of models for air temperatures in the future than for precipitation (IPCC, 2014). Predicted increases in stream temperature with 2.2 OBSERVATIONS AND PREDICTIONS OF CLIMATE CHANGE IN RIVERS 29 increasing air temperatures are frequently in the range of 2–3oC(Isaak et al., 2012; Mantua et al., 2010). The areas projected to have the greatest water temperature increases are the United States, Europe, eastern China, and parts of southern Africa and Australia (van Vliet et al., 2013). Many projections of future scenarios for stream temperature build on a relationship between air temperature and water temperature. Some have suggested that an increased air temperature will lead to a similar magnitude of increase in stream temperature (Ficke et al., 2007; Mohseni et al., 2003; Eaton and Scheller, 1996). However, Luce et al. (2014) calculated that existing cold streams show lower sensitivities to air temperature variations, while warm streams could be insensitive or sensitive depending on geological or vegetation con- text. In modeling tropical streams in Malaysia, Danladi Bello et al. (2017) projected that stream temperatures would be most sensitive under low flows and that changes in land use would also be important. Whether an increase in air temperature translates into an increase of water temperature will depend on a combination of direct and indirect factors. It is unlikely that increases in water temperatures will equally match those of air temperature or be the stable relationships over time that are assumed (e.g., Mantua et al., 2010). Arismendi et al. (2014) documented a range of relationships, from linear to sinusoidal relationships, between air and water temperatures at various sites. They also noted that correlational relationships between air temperatures and water temperatures were not consistent over time. Diabat et al. (2013) found a differential sensitivity of stream temperature responses to models that implemented consistent increases of air temperature over 24-h cycle versus day-only increases and night-only increases. Predictions for future stream temperatures need to be based on multiple factors (Arismendi et al., 2014; Webb et al., 2008). Water temperatures are most responsive to the intensity and duration of exposure from incoming solar radiation ( Johnson, 2004; Sinokrot and Stefan, 1993). Riparian vegetation is a major influence for the solar exposure of streams and rivers. The density and height of the vegetation relative to the width of the river and solar angle determine the shading of river and riparian surfaces from direct radiation. Riparian forests can also moderate air temperatures near streams and rivers (Brosofske et al., 1997; An- derson et al., 2007). Streams with intact riparian forests can have strong microclimates, with air temperatures several degrees cooler than at a distance from the stream, higher relative humidity, and lower wind speeds (Anderson et al., 2007). Increased air temperature at unshaded sites will not necessarily correspond to similar increases of air temperature within riparian areas. Although there can be strong correlations between air and water temperature patterns, the convective and conductive processes that exchange heat between air and water are not as efficient as solar radiation in warming water ( Johnson, 2004). A combination of climate stressors, including changes in riparian cover, precipitation and streamflow, will add to the variability in potential responses of stream temperatures across systems (van Vliet et al., 2013; Webb et al., 2008). The warming of streams has been projected to result in a reduced habitat especially for cold water fish species in the future (Almodovar et al. 2012; Isaak et al. 2012, 2016; Santiago et al. 2016). Loss of habitat for trout that are currently at their thermal edge of distribution has been projected to increase 38%–56%, depending on the type of stream (Santiago et al. 2016). Freixa et al. (2017) suggested that nighttime increases in water temperature might have the greatest effect on microbial activity and associated food webs. Increased temperature is predicted to 30 2. CLIMATE CHANGE AND INTERACTIONS result in phenological shifts, including earlier emergence or smaller size at emergence, as well as possible mismatches of resources between prey and predators. Pyne and Poff (2017) modeled changes in invertebrate communities in response to GCM projections of maximum stream temperatures and streamflow changes for 250 minimally perturbed streams in the United States. They predicted 30%–40% loss of taxa in dryer, warmer ecosystems and 10%–20% in cooler, wetter regions. However, responses may not be as predictable as assumed; experimental temperature increases showed a variety of phenological responses that differed across invertebrate taxa (Li et al., 2011). There is generally a strong agreement that stream temperatures will increase with climate change, but the magnitude of change has a high uncertainty because of the interactions of drivers of temperature with multiple other factors, including discharge, source of streamflow, and status of riparian vegetation.

2.3 CLIMATE CHANGE IN RIVERS: SIMILARITIES TO EXISTING STRESSORS AND SURPRISES

The majority of impacts of climate change will be occurring in river networks that are currently impacted by other stressors or have a legacy of impacts. How can we best predict what the responses might be? Climate change impacts on stream and rivers may be analogous to the impacts of existing stressors. However, multiple stressors with the addition of climate change can interact in predictable or unpredictable ways.

2.3.1 Current Stressors as Analogs for Future Climate Change

Changes in precipitation and streamflow are a common prediction for climate change across biomes, but stream flows in the majority of rivers have already been greatly modified by anthropogenic activities, and many rivers no longer have natural flow regimes (Arthington et al., 2006; Poff et al., 2006; Meyer et al., 1999). Dams are frequent structures on river networks and modify downstream flow regimes by storing seasonally abundant water and releasing it at other times of the year. Dams can augment low flows during dry seasons (Rolls et al., 2012), dampen flood pulses and high flows (Kupferberg et al., 2012) and lead to many other permutations of flow; species responses to dams might be similar to their responses to climate change. Dams have led to the regional homogenization of assemblages and create conditions that favor the spread of nonnative species at the expense of locally adapted native biota (Poff et al. 2007). Following the impoundment from dams in Texas, habitat generalist species dominated assemblages during periods of reduced flood frequencies, and regionally endemic species declined (Perkin and Bonner, 2011). The potential impacts of climate change on stream flows (Zampieri et al., 2015; Doll€ and Zhang, 2010) similarly in- volves shifts in the timing and magnitude of hydrographs (Dhungel et al., 2016). However, dams tend to dampen or modulate extremes, while climate change is predicted to lead to more extremes and a wider variability of flows with higher or longer durations of peak flows and lower and longer periods of low flows (Doll€ and Zhang, 2010). With the increased probability of hydrologic events that are more extreme under climate change (Diffenbaugh et al., 2017, Milly et al., 2005), more floods, landslides, and droughts 2.3 CLIMATE CHANGE IN RIVERS: SIMILARITIES TO EXISTING STRESSORS AND SURPRISES 31 may occur. Floods and landslides could result in major changes in the physical structure of rivers, with implications for instream habitat, stream temperature, flow dynamics, and ultimately impacts to stream biota and trophic interactions. Increased channel complexity can provide refugia to fish and other biota during high flows (Pearsons et al., 1992). However, many river channels have already been simplified, straightened, downcut, and dewatered, and their banks have been hardened. This existing channel simplification may be greater than what might occur from flooding and droughts with climate change. Many biota are adapted to some level of flooding, and there are instances of floods benefitting specific life stages of fish (Dodds et al., 2012), while other species or life stages can be negatively impacted (Wenger et al., 2013). Low flows from the extraction of water from rivers for industry, irrigation, or human consumption is another analog of future climate change; one that is currently resulting in decreased stream flows and dry rivers in a similar manner as climate change. Groundwater extraction has also been linked to loss of flowing surface water in streams over time and ultimately changes in species assemblages (Perkin et al., 2017). Riparian zones are predicted to be impacted by climate change, temperature changes, and changes in water regimes in the future. Current and likely similar impacts to riparian zones from human activities, including urbanization, forest harvest, agriculture, grazing, water extraction and stream channelization, have already occurred. Climate change may impact current riparian vegetation through shifts in temperature and moisture regimes (Weed et al., 2013), which can lead to plant stress and increasing susceptibility to insect infestations. Intro- duced plants presently dominate many riparian zones, and introduced insect pest species such as Emerald Ash Borer (Agrilus planipennis) and Wooly Adelgid (Adelges tsugae) are expanding and impacting key overstory vegetation in others (Valenta et al., 2017; Webster et al., 2012). Reduced stream flow has been shown to impact riparian vegetation and streamside water tables (Merritt and Cooper, 2000). With lower summer flows predicted with climate change, riparian vegetation may be similarly affected. Ongoing impacts to riparian zones have resulted in the loss or removal of streamside vegetation, which can reduce shade over streams and contribute to a higher stream temperature ( Johnson and Jones 2000), as well as reduced litter inputs to support allochthonous food webs (Webster et al., 2012). Biodiversity loss in freshwater ecosystems has occurred broadly and additional decreases in biodiversity from climate change are predicted to be especially high in high-latitude regions (Woodward et al., 2010), where the greatest increases in temperature and precipitation are expected to occur. In other regions, existing stressors involving changes in habitat, flow, water quality, and food resources may produce similar effects to those from climate change. Warmer streams under climate change may lead to the expansion of species beyond their native ranges, as has already occurred with the anthropogenic warming of streams and the purposeful in- troductions of fish and vertebrates to new habitats. The resulting homogenization of aquatic communities across bioclimatic domains (Villeger et al., 2011) can have impacts on regional biodiversity and sensitive species, including a loss of biodiversity (Vilmi et al., 2017).

2.3.2 Interactions of Climate Change With Other Stressors; Surprises and Nonlinear Responses

Disentangling the effects of multiple stressors is challenging, and with the addition of climate change the task becomes monumental (Chapter 1). Climate change is not a single 32 2. CLIMATE CHANGE AND INTERACTIONS stressor, but it is a shorthand for an exponential number of combinations of possible changes; two of the major influences to rivers are discharge and temperature. Although it is valuable to model what the combinations of multiple climate futures might mean for river and stream ecosystems, it is important to remember that there is a high variability or uncertainty in the predictions of hydrologic future scenarios. Future systems may not operate as those in the memorable past have operated because of shifting baseline conditions associated with new and existing stressors (Milly et al., 2008). A new normal may be underway and species distributions may be widening compared to historical ranges as extreme events become more frequent (van Vliet et al., 2013). Predicting whether interactions among climate change and other stressors will be linear, additive, synergistic, or some other combination is difficult. The literature examining responses to stressors is dominated by studies of single stressors and single response metrics (Folt et al., 1999), because the identification of responses to multiple stressors has a high uncertainty (Chariton et al., 2016; Ormerod et al., 2010). Adding an additional stressor into already compromised systems might result in surprising or unpredictable responses in freshwater ecosystems. Although more efforts are underway to understand the effects of multiple stressors (Segner et al., 2014; Fausch et al., 2010), it is only recently that the effects of climate change have been considered in addition to other stressors (Van den Brink et al., 2016; Jackson et al., 2016). Many of the projections regarding climate change responses assume that the responses to multiple stressors plus climate change are likely going to be linear or simply additive, where the net effects of multiple stressors are equal to the sum of their single effects ( Jackson et al., 2016; Fig. 2.2). For example, streams that no longer have riparian shading and have high water temperatures could face additional additive increases to water temperatures under climate change. Jackson et al. (2016) suggest that the nitrification of rivers is always an additive effect when combined with climate change. More floods and extreme hydrologic events have been predicted to result in an increased loading of nitrogen to rivers (Sinha et al., 2017). The loading of nitrogen is expected to be greatest in agricultural areas with high rainfall and current high

FIG. 2.2 Stylized depiction of possible interactions of climate change in combination with other stressors. The net effects of combinations of multiple stressors can be additive, synergistic, antagonistic, or reverse (Chapter 1; Jackson et al., 2016). Other possible stressors may include resource extraction, urbanization, rural development, hydropower, channel modification, water withdrawals, agriculture, water pollution, and extreme events of drought, flood, and fire. 2.3 CLIMATE CHANGE IN RIVERS: SIMILARITIES TO EXISTING STRESSORS AND SURPRISES 33 nitrogen application, such as the Northeast and upper Midwest of the United States, as well as India, China and Southeast Asia. The degradation of water quality from human activities is widespread. Attention has been focused on improving water quality over the last four decades, ranging from decreasing nutrient inputs to reducing water temperatures in streams and rivers (Brack et al., 2015; Malmqvist and Rundle, 2002). Because of climate change- associated shifts in water availability, coupled with the potential for an increased demand for water for agriculture or consumption, streams may again be increasingly vulnerable to factors that decrease water quality (Dyer et al., 2014; Whitehead et al., 2009). The extraction of water from low-flowing streams could result in the further warming of streams and rivers during crucial summer periods. Low flows may not be sufficient to dilute point source inputs to rivers. In urban headwater streams, Nelson and Palmer (2007) predicted an increase of water temperature surges with climate change. They noted that urbanization may be more of an impact to small streams than climate change, but that these stressors do work in concert with one another. A second option is that responses to climate change and an additional stressor could be synergistic, where the sum of the net effects are greater than the separate effects. Some studies have shown a prevalence of synergistic interactions in response to multiple stressors (Radinger et al., 2016; Harvey and Nakamoto, 2013). A third category of response types are antagonistic, where the net effect of multiple stressors could be less than the sum of their separate effects but are still in the same direction as the individual responses. For example, models of climate-related impacts to stream fish in conjunction with forest harvest suggested that increased flows associated with the harvest might compensate for the decline in base flow associated with climate change (Penaluna et al., 2015). A fourth option is that responses to climate change and other stressors could be a reversal, where the net response is in the op- posite direction from that expected for individual responses. For example, warming can shift mechanisms by which stressors affect biological receptors in animals; higher temperatures reversed the stimulatory effects of sublethal ammonia enrichment on juvenile trout (Linton et al., 1997). In a metaanalysis of responses to dual stressors in freshwater ecosystems, Jackson et al. (2016) found that antagonistic interactions were most common. In particular, they found that the overall mean net effect of warming combined with a second stressor was antagonistic. This accounted for 41% of the studies, compared to synergistic (28%), additive (16%), or reversed (15%) effects. A possible explanation for the majority of antagonistic responses is that freshwater ecosystems are exposed naturally to high environmental variability, which may foster an increased potential for resilience in responding to effects of multiple stressors ( Jackson et al., 2016). Alternatively, antagonist responses may be due to a high degree of asymmetry in the magnitude of underlying factors affected by stressors (Folt et al., 1999). Predictions of the combination of increasing water temperature and more extreme low flows from climate change are generally assumed to be additive responses that negatively impact species (Mantua et al., 2010). The proposed responses include a major contraction of ranges (Isaak et al., 2012), shifts in community composition (Pyne and Poff, 2017), and the loss of sensitive species or mismatches in food resources (Durance and Ormerod, 2007). Wenger et al. (2011) suggest that there will be large declines in trout habitat in the United States, but that the effects of increased temperature might be partially offset by changes in flow for some trout species. A shift in seasonality of temperatures (e.g., to warmer 34 2. CLIMATE CHANGE AND INTERACTIONS temperatures in springtime) might aid some fish at specific life stages. Climate change plus ongoing additional stressors may provide surprises. A metaanalysis examining effects of temperature on detrital decomposition found less responsiveness to temperature than predicted by metabolic theory (Follstad Shah et al., 2017). Kenna et al. (2017) also noted antagonistic effects on the rates of decomposition by comparing an introduced species and a native species across a range of temperatures. These nonlinear responses suggest that freshwater ecosystems may have some resilience to climate change and multiple stressors, but that the responses will be complex. Discussions of how to foster resilient aquatic ecosystems in light of the additional stress of changing climate with ongoing stressors are underway (Markovic et al., 2017; Timpane- Padgham et al., 2017). Instream habitat complexity may provide refugia during high flows (Pearsons et al., 1992), and many restoration projects are reintroducing channel complexity and wood. Some have suggested that mobile biota will reduce their ranges (Isaak et al., 2012) or shift their ranges to higher elevations in search of continued viable habitat conditions as climate change increasingly impacts their current habitats (Papadaki et al., 2016). However, not all aquatic species are highly mobile or adaptable. Even mobile species cannot always move long distances and expand or contract their home ranges to escape their changing environment because of stream drying or numerous barriers and dams that fragment habitats within river networks (Markovic et al., 2017; Mathews and Marsh-Mathews, 2003). These fragmented habitats can lead to a loss of diversity across regions (Perkin et al., 2017; Heino et al., 2009).

2.4 VULNERABILITY OF RIVER ECOSYSTEMS: AN EXAMPLE OF DROUGHT AS A MANIFESTATION OF CLIMATE CHANGE IN ADDITION TO OTHER STRESSORS

Droughts or extended periods of extremely low flow are but one example of an extreme event that is expected to become more frequent and intense in the future due to climate change. Each drought is unique because of its duration and magnitude, as well as the type of hydrologic regime that it is interrupting. Drought may be one of the few natural disturbances that severely affects freshwater species and ecosystems. Drought has been suggested to have longer-lasting effects than floods on aquatic community dynamics due to changes in species associations and community structure (Marsh-Matthews and Matthews, 2017). Predictions of biological responses to drought by species and across regions would be informative for anticipating responses to climate change. However, our current understanding of species and ecosystem responses to drought is limited (Milly et al., 2008; Diffenbaugh et al., 2017; Mao et al., 2015). A recent multiyear drought in California added to the multiple stressors to which the southwestern rivers of the United States have been subjected (Chapter 9). In California and Arizona, most major streams have been channelized and diverted for agricultural and urban use (Reisner, 1993). Starting in the 1930s and extending into the late 1960s a series of large dams were constructed on major rivers to generate electricity and provide year-round water through aqueducts for irrigation and for supplying the cities. Following the construc- tion of the dams the downstream rivers have been consistently impacted by changes in their 2.4 VULNERABILITY AND BUFFERING OF MULTIPLE STRESSES FOR RIVER ECOSYSTEMS 35 hydrographs, including reduced flows, rapid fluctuations of flows when power is being gen- erated, or seasonal high flows (Kupferberg et al., 2012). Water temperatures in the impacted rivers are generally higher than they were predam, although where water releases occur from the bottom of the reservoir, temperatures can be colder or out-of-sync with natural seasonal temperature regimes. The reservoirs created by the impoundment of rivers form unique lentic or standing water bodies in previously lotic networks. They modify the downstream transport of sediments, nutrients, and organic matter. They block the upstream and downstream migration of native anadromous or amphidromous fish and create new warmer water habitats that are frequently stocked with nonnative species that make it difficult for the continued success of native species. Downstream of the reservoirs, altered water temperatures impacted the growth of native species and may have been a causative factor in the decline of an amphibian species of the Trinity River in California (Wheeler et al., 2015). The changes that occur because of reservoirs often undermine the natural processes that maintain native biodiversity ( Johnson et al., 2008)(Chapter 3). For example, invasive fishes showed preferences for reservoirs compared to rivers in the Guadiana River of the Iberian Peninsula, where reservoir communities were taxonomically homogenized relative to the river communities (Clavero and Hermoso, 2011). Introduced species can also lead to shifts in the composition of trophic levels (Eby et al., 2006). In addition to being a haven for invasive species, reservoirs are often stocked with high densities of hatchery fishes for recreational fishing. The modified trophic dynamics of a reservoir food web can impact native species, because the introduced species can displace, outcompete or consume native species. In reservoirs of the Columbia River, juvenile anadromous salmonids use the reservoirs for rearing (Gray and Rondorf, 1984), leading them to be vulnerable to predation by the introduced species. Juvenile salmonids can be stalled by the lack of flow in reservoirs on their downstream migration as well as be blocked by dams when migrating upstream as adults (Roscoe and Hinch, 2010). In other parts of the world, where upstream amphidromous fish or crustaceans release their planktonic eggs and larvae to float downstream to hatch in estuaries, reservoirs and dams pose unique challenges to successful downstream transport (Benstead et al., 1999; Roscoe and Hinch, 2010). In California, increasing human populations compete for limited water in a region that has large portions previously considered deserts. More and more demands for water lead to the dewatering and diversion of rivers and increased periods of time that river channels have minimal to no flow. In addition, higher populations often lead to increased amounts of waste and pollutants being discharged into rivers, resulting in a degraded water quality for aquatic ecosystems. In this region, reduced flows generally occur at times of warmest water temperatures, leading to stress and an increased potential for disease for aquatic biota (Arismendi et al., 2013b). The reduced availability of water in key periods also can impact the viability of streamside vegetation and riparian forests. In 2012, a multiyear drought started in this region and extended through 2016 (Fig. 2.3). Several years of low precipitation coincided with warmer than normal air temperatures to produce a drought event, the magnitude of which is predicted to occur more frequently in the future (Diffenbaugh et al., 2017; Fig. 2.4). During this time, storm patterns shifted, rains were limited in the valleys, and snowfall that feeds many rivers and reservoirs was very limited to nonexistent in the mountains. An increase in the frequency of droughts has occurred 36 2. CLIMATE CHANGE AND INTERACTIONS

FIG. 2.3 Examples of rivers during drought in Califor- nia. (A) Water levels in Lake Oroville on June 21, 2014 were 49 m below general high water mark. (B) Minimal surface flows in Van Duzen River during July 2014. (C) Dead fish in algae along the low banks of Lake Hemet on June 3, 2014. Reproduced with permission: (A and C) Allen J. Schaben, Copyright # 2014. Los Angeles Times. (B) Mike Dronkers.

during the past few decades, but this most recent drought was the most extreme on record (Diffenbaugh et al., 2015). Although the long-term effects of this multiyear regional drought remain unknown, the short-term responses include declines of aquatic populations and increases of less desirable species, such as cyanobacteria blooms (Power et al., 2015). More general responses of rivers to drought have been wide-ranging, including changes in populations and aquatic communities, loss of habitat, crowding in the remaining habitats, and reduced water quality (Lake, 2000). Most research on the biological responses to drought has evalu- ated the short-term effects by looking at the responses of less than 1 year (Matthews and Marsh-Matthews, 2003). 2.4 VULNERABILITY AND BUFFERING OF MULTIPLE STRESSES FOR RIVER ECOSYSTEMS 37

FIG. 2.4 Map of drought intensity in California and southwestern USA on September 29, 2015. Colors from yellow to dark red show increasing severity of drought with dark red representing the most extreme condition of exceptional drought. Modified from: www.droughtmonitor.uni.edu

Although many species have evolved to tolerate or be resilient to a broad range of stressors, including seasonal droughts (Scheffer and Carpenter, 2003), species vary in their ability to tolerate and recover from drought (Marsh-Matthews and Matthews, 2010; Bogan et al., 2015). For example, if hydroperiods are shortened in ephemeral pools found in streams, then there will be less breeding habitats to support local amphibian populations (Brooks, 2009). As drought becomes more extreme, the potential for community recovery decreases and short- lived strong dispersers replace long-lived weak dispersers (Bogan et al., 2015). Drought cre- ates harsh living conditions thereby reducing survival due to desiccation, predation, and in- tolerable conditions brought on by drought, including decreased flow and oxygen levels and increased water temperature (Magoulick and Kobza, 2003). Recovery over the long-term will also be influenced by the ongoing stressors, the legacy of prior stressors, the resiliency of the ecosystem, the adaptive capacity of biota to seasonal water stress, the connectivity of freshwater to source populations, and the extent to which humans participate in reintroducing taxa into freshwater systems. 38 2. CLIMATE CHANGE AND INTERACTIONS 2.5 CONCLUDING REMARKS

The fundamental importance of freshwater resources, the rapid rate of extinction for freshwater species, and the current exposure of rivers to multiple stressors raises concerns about the impact of additional stressors due to climate change. The predictions of future changes to hydrologic regimes under climate change show wide variability and low certainty. All of the papers reviewed are in agreement that more extreme events, including floods and droughts, have a high likelihood to become more common in the future. High summer stream temperatures, which often are limiting for taxa, are predicted to increase further and to affect species distributions and ecosystem processes. The predictions of responses to climate change, in conjunction with current ongoing stressors, assume that effects will be linear or additive. However, more complex responses may occur due to the interactions among stressors. Ulti- mately, the conservation of freshwater resources with climate change will depend on how well we understand and address the effects of multiple stressors on river ecosystems, especially as the scope of human pressures increases. Plans for the management of river ecosystems need to incorporate the variability across climate change scenarios and not rely on the averages of scenarios. Synchronously the projections of river responses to climate change need to account for current stressors, as well as the potential nonstationarity of relationships and nonlinear responses.

Acknowledgments

We thank Stephanie Schmidt for help with the bibliography and literature review and Kathryn Ronnenberg for as- sistance in preparing Fig. 2.2. The views expressed in this paper are those of the authors and do not reflect the official policy of the US government.

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