Impacts of Acidification and Potential Recovery on the Expected Value

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Impacts of acidification and potential recovery on the expected value of recreational fisheries in Adirondack lakes (USA) Jesse Caputo, Colin M. Beier, Habibollah Fakhraei, and Charles T. Driscoll Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05274 • Publication Date (Web): 30 Nov 2016 Downloaded from http://pubs.acs.org on December 6, 2016

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Environmental Science & Technology

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Impacts of acidification and potential recovery on the expected value of recreational

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fisheries in Adirondack lakes (USA)

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Jesse Caputo*1, Colin M. Beier2, Habibollah Fakhraei3, Charles T. Driscoll3

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1 – Family Forest Research Center, University of Massachusetts Amherst, 160 Holdsworth Way,

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Amherst, MA 01003

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2 – Department of Forest and Natural Resources Management, SUNY College of Environmental

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Science and Forestry, 1 Forestry Drive, Syracuse, NY 13210

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3 – Department of Civil and Environmental Engineering, Syracuse University, 151 Link Hall,

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Syracuse, NY 13244

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*CORRESPONDING AUTHOR: [email protected], 413.545.3966 (phone) ,

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413.545.4358 (fax).

ACS Paragon Plus Environment


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ABSTRACT

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We estimated the potential economic value of recreational fisheries in lakes altered by acid

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pollution in the Adirondack Mountains (USA). We found that the expected value of recreational

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fisheries has been diminished because of acid deposition, but may improve as lakes recover from

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acidification under low emissions scenarios combined with fish stocking. Fishery value increased

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with lake pH, from a low of $4.41 angler day-1 in lakes with pH < 4.5, to a high of $38.40 angler

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day-1 in lakes with pH > 6.5 that were stocked with trout species. Stocking increased the expected

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fishery value by an average of $11.50 angler day-1 across the entire pH range of the lakes studied.

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Simulating the future long-term trajectory of a subset of lakes, we found that pH and expected

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fishery value increased over time in all future emissions scenarios. Differences in estimated

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value among pollution reduction scenarios were small (< $1 angler day-1) compared to fish

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stocking scenarios (> $4 angler day-1). Our work provides a basis for assessing the costs and

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benefits of emissions reductions and management efforts that can hasten recovery of the

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economic and cultural benefits of ecosystems degraded by chronic pollution.


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INTRODUCTION

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Since the implementation of the Clean Air Act Amendments of 1970 (U.S. Public Law 91-604),

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atmospheric deposition of nitrogen and sulfur has been declining throughout the United States

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(National Atmospheric Deposition Program 2015a, U.S. Environmental Protection Agency

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2013,). It has long been known that lake acidification associated with deposition has resulted in

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adverse impacts to aquatic ecosystems and particularly fish populations across the eastern United

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States (Lovett et al. 2009, Driscoll et al. 2001) and, therefore, it has been expected that chemical

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and biological recovery would follow from reductions in deposition. Recovery of some aquatic

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ecosystems has already begun (e.g. Sutherland et al. 2015, Josephson et al. 2014) and is likely to

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continue under a wide range of proposed emissions reduction scenarios (Driscoll et al. 2001).

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The Adirondack Park of New York State has proven especially sensitive to acidification. Driscoll

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et al. (2001) found that 41% of Adirondack lakes had ANC values below 50 µeq L–1, compared

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to less than 15% of lakes in the nearby Catskills and the New England states. Critical loads for

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acidity of surface water in the Adirondacks remain low compared to the surrounding region and

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the entire country (National Atmospheric Deposition Program 2015b), reflecting the sensitivity

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of Adirondack lakes to even moderate levels of deposition. Zhou et al. (2015) simulated the

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recovery of water chemistry and fish assemblages in the Adirondacks under continued

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reductions in acid deposition and found that species richness (# fish species) was unlikely to

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recover under all but the most stringent pollution reduction scenarios (~100% reduction relative

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to current levels).

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Healthy fish populations provide people with opportunities for recreational fishing, a highly

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valued ecosystem service (Hughes 2015). Fishing provides material benefits in the form of edible



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protein, as well as cultural benefits related to recreation, aesthetics, and connection with nature

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(MA 2005). However, not all fish species are actively or equally sought by recreational anglers

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(Boyle et al. 1999), and several of the most important game fish may be either more resistant to

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acidification or more able to recover as pH recovers. In the Adirondacks, brook trout (Salvelinus

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fontinalis) – one of the most highly sought-after game fish – has been shown to be somewhat

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tolerant to waters with low pH, whereas several of the most sensitive species are small native

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cyprinids that are not typically targeted by fishermen (Schofield and Driscoll 1987).

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Furthermore, trout populations in several lakes have demonstrated the capacity for recovery after

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local extinction, both where fish populations persisted in tributary streams from which they were

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able to repopulate lakes (Josephson et al. 2014), as well as where such refugia were not available

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(Sutherland et al. 2015). On the other hand, other important game fish, such as smallmouth bass

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(Micropterus dolomieui) for example, may be less tolerant to acidification than trout (Schofield

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and Driscoll 1987).

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Stocking of trout and other gamefish has been widely promoted in the northern hemisphere as a

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means of accelerating the rehabilitation of fish stocks in acidified waters (Snuchins and Gunn

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2003, Tammi et al. 2003, Lachance et al. 2000, Gunn and Mills 1998). Trout in particular have

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been a focus of stocking programs for streams and lakes of the Adirondack region (Lampman et

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al. 2011, Van Offelen et al. 1993, Cone et al. 1988). If successful, stocking has potential to be a

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cost-effective means of improving recreational fishing opportunities in moderately acidified

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waters or accelerating biological recovery in waterbodies that have already achieved chemical

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recovery – a process which, unaided, can entail significant delays (Sutherland et al. 2015,

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Josephson et al. 2014). It is important to note here that, strictly speaking, the term ‘recovery’ –

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whether of water chemistry, fish stocks, or ecosystem services – refers to the restoration of a


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historical condition. The establishment of trout and other gamefish in historically fishless lakes,

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for example, would indicate the emergence of novel ecosystems – not biological recovery. If

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establishment of these stocks improved opportunities for recreational fishing, then the value

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associated with that activity could be said to have increased, but not to have recovered – since

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fishless lakes did not historically provide this benefit.

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In this study, we estimated changes in the economic value of recreational fisheries in response to

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the chemical recovery of lakes altered by acid pollution in the Adirondack region of northern

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New York State, one of the ‘hot-spots’ for acid deposition effects in North America (Driscoll et

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al. 2001). Recent progress in reducing acid deposition to pre-industrial levels has promoted the

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recovery of aquatic ecosystems in the Adirondacks, and in turn, the renewal of the many benefits

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provided by these ecosystems to society (Driscoll et al. 2016, Driscoll et al. 1996). However,

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such progress may be difficult to sustain – given both the fiscal and political costs of increasingly

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stringent emissions regulations via cap-and-trade programs – if neither the economic damages of

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acid deposition, nor the benefits of reducing its impacts on human well-being, are elucidated in

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ways that are relevant to decision-makers and the general public.

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Here we sought to bridge this gap by evaluating recreational fisheries as an ecosystem service,

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which has both ecological (i.e., impacts of acidification on fish assemblages) and societal (i.e.,

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cultural preferences for recreational fish species) components. We use a data-driven

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methodology based on recent efforts to integrate long-term ecological research with empirical

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proxies of societal demand for ecosystem benefits (Caputo et al. 2016a, Beier et al. 2015).

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Drawing on extensive and long-term monitoring, we analyze the relationships among lake pH,

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fish stocking, and the presence of game fish for 52 Adirondack lakes. Next we use benefit

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transfer to estimate the expected value of recreational fishing in stocked and un-stocked lakes



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across a range of pH values. Lastly, using both simulations of future lake pH and scenario

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modeling, we estimate how recovery of water chemistry, through both reduced emissions and

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active restoration efforts, could influence the expected values of recreational fishing in

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Adirondack lakes. Although much of the biological research on lake acidification has focused on

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fish species of recreational value, and while ongoing efforts to stock lakes with desirable species

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has in part sought to address acid-mediated degradation of sport fisheries, this study develops a

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more integrated understanding of how acid rain has shaped the ecology, economics and

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management of Adirondack sport fisheries.

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MATERIALS AND METHODS

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The Adirondack Lake Survey Corporation (ALSC) was established in 1983 to collect baseline

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data on the environmental status of aquatic ecosystems in the Adirondacks and changes

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associated with atmospheric deposition, including fish populations and water chemistry

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(Lampman et al. 2011). For the current analysis, we used data collected from a subset of 52 lakes

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included in the ALSC’s Adirondack Long-Term Monitoring (ALTM) program; this data consists

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of fish surveys (presence/absence by species) and measurements of lake pH. Our analysis was

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conducted in three broad stages: 1) we analyzed the relationship between presence of game fish,

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fish stocking, and pH using logistic regression; 2) we estimated the expected value of

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recreational fish stocks using benefit transfer; and 3) we used outputs from a biogeochemical

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model to estimate changes in fish stocks (and associated values) based on simulated long-term

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changes in pH and hypothetical stocking scenarios.

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At each of the 52 ALTM lakes, one or more fish surveys were conducted between 1984 and

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2005. For each lake, we examined the list of fish species found during the most recent survey


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and determined the presence/absence of two broad groups, trout and game species (Table 1). We

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use the term ‘trout’ to designate brown trout (Salmo trutta) in addition to the chars or true trouts

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(Salvelinus spp.) because of the close association of the two taxa among lay people and because,

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importantly, the benefit transfer equations we adopted did not differentiate between these (Boyle

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et al. 1999, see below). We also determined from ALTM records (Lampman et al. 2011) whether

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the lake had ever been stocked with trout species at any time prior to the most recent survey.

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There is no record of any of the study lakes being stocked with any game fish other than trout

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species.

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Lake pH was sampled on a monthly basis from 1984-2012. Individual lakes were not always

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sampled every month during this 29-year period, however. Each lake was sampled 1-12 times

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each year for 20-22 years. We calculated annual pH values for each lake as the mean of the

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monthly values. When a lake was not measured at least once in a given year, we filled the

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resulting gap in the data using linear interpretation. Across the 52 lakes, there were 45 gaps of 1

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or more years. These 45 gaps ranged from 4-8 years in length. No lakes were dropped from the

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dataset based on the length of a gap. We ended up with a full time series for each of the 52 lakes

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from 1984 to 2005 (the year of the final fish survey). For each lake, we then selected the pH

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value corresponding to the year of the most recent fish survey for that lake to use as an

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independent variable (along with fish stocking status) in statistical modeling.

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We used logistic regression to predict the likelihood of the presence of trout in a lake given its

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pH value (a continuous variable) and whether the lake was unstocked or not (a binary categorical

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variable). We also predicted the likelihood of other game fish (not including trout) given the lake

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pH. The resulting regression equations allowed us to estimate the probability of the presence of



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trout (Equation 1) and game fish (Equation 2) from pH (coefficient=β1) , stocking status

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(coefficient=β2), and an intercept term (β0).

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Equation 1. P(trout) = 1 / (1 + e – (β0+β1*pH+β2*unstocked))

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Equation 2. P(gamefish) = 1 / (1 + e – (β0+β1*pH))

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To estimate the value of recreational fishing, we used the recreational fishing benefit function

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developed by Boyle et al. (1999). When doing benefit transfer, benefit functions – derived from

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formal meta-analysis of primary valuation studies – are considered preferable to direct transfer of

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values from a single study (Plummer 2009). Boyle et al.’s (1999) function was derived from a

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meta-analysis of 70 primary valuation studies estimating willingness-to-pay (WTP) for

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recreational fishing across the conterminous USA and Alaska (n=1,002 individual welfare

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estimates). Constituent studies relied on a mixture of travel cost (n=624) and contingent

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valuation (n=378) methods to derive individual welfare estimates (Boyle et al. 1999). The

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resulting benefit function is in the form of a linear model predicting total consumer surplus ($

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angler day-1) based on fish species group and water type (p pH 6.5, there was more than a 75%

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probability that trout and other game fish would be present in the sport fishery. Below pH 5.6,


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we estimated a probability of less than 50% that lakes contained any suitable game fish. Trout

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were more likely to be present than other kinds of game fish in lakes with pH greater than 6.3,

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and at pH less than 6.3, the reverse was found to be true. In lakes where trout were historically

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stocked, on the other hand, trout were more likely to be present than game fish across the entire

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pH range observed. Unsurprisingly, we found a greater probability of trout being present in

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stocked vs. un-stocked lakes; above pH 6.9, the probability of trout presence in stocked lakes

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approached 99%. All independent variables in the logistic regression analyses had low p-values

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(P < 0.001) and deviance tests for both models were not significant at any reasonable α level (P >

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0.4), suggesting no evidence for lack of fit in either model (Table 2). Estimates of regression

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parameters were similar to those calculated as part of earlier research in the same region

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(Driscoll et al. 1991, Baker et al. 1988).

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The expected value of recreational fishing increased with increasing pH, from $4.41 angler day-1

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to $35.73 angler day-1 in un-stocked lakes and $15.80 angler day-1 to $38.40 angler day-1 in

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stocked lakes (Figure 2). Stocking increased the expected value of recreational fishing relative to

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un-stocked lakes by an average of $11.50 angler day-1 across the entire pH range. This pattern

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was not unexpected, given that reported values for trout fishing were almost three times higher

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than fishing for alternative freshwater species (Boyle et al. 1999). It is important to reiterate here

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that these value estimates are based solely on the presence or absence of a fishery. Models that

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took into account the size and quality of the fishery (as well as demand-side criteria such as lake

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accessibility) would result in more nuanced (and hopefully more precise) estimates of fishery

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value. Unfortunately, the ecological and economic data necessary to develop such models are not

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currently available the for the ALTM lakes.



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Using the simulated pH data for the sub-sample of 21 lakes, we found that the expected value of

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recreational fishing increased over time in all scenarios in response to increasing pH (Figure 3).

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It is quite likely, however, that this methodology overestimates the rate of this increase. By

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applying regression equations derived from current conditions to point estimates of pH over

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time, we are essentially making the assumption that probability of fish presence changes

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instantaneously in response to changes in lake acidity. Research has shown, however, that

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recovery of fish populations in the Adirondacks can lag behind chemical recovery for several

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decades (Sutherland et al. 2015, Josephson et al. 2014). In addition to impacts on the actual

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presence of gamefish, such temporal lags could have implications for user groups’ perceptions of

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the quality and availability of the sport fishery resource, leading to lower demand and/or

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estimates of monetary value than our models would suggest. In other words, while the lake

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ecosystem recovers, if Adirondack anglers have already decided that visits to other lakes would

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be more rewarding, the recreation benefit of establishing healthy trout populations in historically

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acidified lakes may not be captured by its key beneficiaries.

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Although expected fishing value increased over time in all scenarios, the mean difference in

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value among the acid deposition reduction scenarios was minimal (< $1.00 angler day-1) because

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of the slow recovery of pH predicted by Fakhraei et al. (2014). In 2000, the mean pH across the

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21 ponds was 5.7. By 2200, the difference between the 0% reduction (pH 5.9) and the 100%

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reduction scenarios (pH 6.2) was less than 0.3 units of pH. On the other hand, stocking level had

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a greater effect on fishing value over time. Throughout most of the time series, expected value

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was approximately $4 angler day-1 higher when it was assumed that all lakes had been stocked.

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Long-term changes in recreational fishery value due to reductions in acid deposition to lakes also

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highlight the importance of fish stocking (Figure 3). In these projections, 95% confidence


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envelopes overlap throughout much of the beginning and end of the time series. By the end of

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the simulation in 2200, for example, we observed significant dispersion among the 21 individual

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lakes that were modeled (Figure 4). We observed less variance in the ‘all stocked’ scenarios than

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in the ‘current stocking’ scenarios. In the latter, differences in sport fishery value were

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exaggerated among lakes stocked with trout versus un-stocked lakes, whereas in the former

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scenario, all lakes were stocked with these highly valued species. Within both sets of stocking

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scenarios, we also found that the scenarios with greater reduction in acid deposition exhibited

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lower variance in the expected value of the fishery. This was likely due to differences in the

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underlying geology and, consequently, differences in acid sensitivity among lakes (Fakhraei et

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al. 2014, Jenkins et al. 2005). Seepage lakes (n=1) and lakes underlain by thin till (n=13) are

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more sensitive to changes in deposition than lakes underlain by medium or thick till (n=7). As

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acid deposition decreases, thin till and seepage lakes increase in pH (and therefore fishery value)

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and thus become more similar to medium-thick till lakes, which are less sensitive to acidification

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and therefore began with higher pH.

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In all scenarios, expected value of the sport fishery follows a non-normal distribution skewed

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towards the higher end of the range. Although the majority of lakes have relatively high fishing

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value (the median value of all scenarios > $32 angler day-1), there are several outliers within each

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scenario, i.e., lakes that still have relatively low-value fisheries after 200 years of chemical

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recovery (Figure 4). We found that the lakes that experience limited or no improvement of sport

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fisheries are consistent with the ‘unrecoverable’ lakes (as defined by Fakhraei et al. 2014) with

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low rates of base cation supply and/or high inputs of naturally occurring organic acids, which

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were likely chronically acidic before the industrial revolution and the advent of acid deposition,

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and therefore are not expected to respond to decreased deposition.



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For those lakes that are not ‘unrecoverable’, the application of lime (CaCO3) has been explored

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as one potential solution for accelerating chemical – and hopefully biological – recovery. Menz

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and Driscoll (1983) estimated that a 5-year liming program in the Adirondacks would cost

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between $93.00 ha-1 and $1750.00 ha-1 (adjusted to 2015 dollars). Based on an estimated benefit

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of an additional $15 angler day-1 by increasing a lake’s pH from 5 to 6 (Figure 2), the lake would

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need to provide between 6 and 116 angler days ha-1 to offset the cost of liming. Where lakes are

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more easily accessible, liming costs are lower and also it becomes more likely that the lake will

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be used by a sufficient number of anglers to warrant the investment. At remote lakes, on the

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other hand, it is questionable whether enough fishing will take place to justify the much greater

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cost of liming.

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Dynamic, interactive visualizations allowing an exploration of the outputs from this analysis are

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available on the web at http://www.forestecoservices.net/fishing.php. Users can adjust base

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parameters and interactively explore how recreational fishing value in the Adirondacks changes

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across time and space under the complete suite of pollution reduction and stocking scenarios. It

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is important to note here that these visualizations (as well as the simulation modeling on which

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they are based) do not take into all possible confounding factors, such as climate change. Future

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work focused on simulating future presence of fish stocks under multiple scenarios of climate

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change and pH recovery would add an important layer to our understanding of how recreational

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fishing values may change in the future.

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Overall, our results suggest that direct intervention has significant potential to mitigate loss of

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particular environmental benefits in degraded systems and to assist in their recovery. In this case,

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we found that stocking with trout has a greater potential for improving the value of recreational

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fishing in acid-impaired Adirondack lakes compared to gains that would be realized via a


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complete cessation of acid deposition (based on model simulations; Fakhraei et al. 2014). A key

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caveat to this interpretation is that our analysis was at the scale of individual lakes. Hundreds of

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water bodies have been impacted by acid deposition in the Adirondacks alone (Strock et al.

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2014, Driscoll et al. 2001). Pollution reductions will passively improve conditions in all surface

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waters sensitive to acidification, while stocking must be actively performed on a lake-by-lake

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basis, typically on an annual basis, and not all water bodies are amenable to stocking. Although

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stocking fish is an established and cost-effective management practice, it is not a feasible

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solution for restoring fisheries across the broad geographic impact of acidification in a remote

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landscape such as the Adirondacks. By contrast, eliminating all emissions sources that cause acid

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deposition poses a categorically different and more complex challenge (Kahl et al. 2004). Of

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course, these are not mutually exclusive strategies. Making progress on emissions reductions and

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chemical recovery of surface waters should increase the likelihood that fish stocking will result

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in the creation of self-sustaining fisheries of significant cultural and economic value. In terms of

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economic value, however, it is important to note here that the value estimates published here are

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measures of the gross value of the fishery – in other words, the value of the ecosystem service as

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realized by its beneficiaries (see Caputo et al. 2016b). A full cost-benefit analysis, on the other

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hand, would require measures of the operational, transaction, and opportunity costs associated

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with both fish stocking and emissions reductions to be taken into account in order to calculate the

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net value of the current or future fisheries.

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Despite the emphasis of this paper on recreational fishing, this is not the only ecosystem service

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provided by Adirondack lakes (nor necessarily the most important). Aquatic ecosystems provide

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a wide suite of cultural, regulating and support services that support human well-being (García-

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Llorente et al. 2011, MA 2005). For example, Van Houtven et al. (2014) estimated that



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improvements in water color, water clarity, odor, and frequency of algal blooms (in addition to

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increased access to game fish) were worth $60/household (95% CI= [$51, $70]) in Virginia,

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USA. In addition to this and other estimates based on human utility, many individuals place

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considerable value on species and ecosystems that do not currently – and perhaps will never –

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provide tangible benefits to people (Krutilla 1967). Zhou et al. (2015) studied the effects of

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pollution reduction on species richness in Adirondack lakes using a similar framework to the one

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we adopted – parameterization of regression models using outputs from PnET-BGC – and found

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that aggressive pollution reduction was necessary to ensure the recovery of fish and zooplankton

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richness. Therefore, ecosystem services associated with biodiversity per se (Cardinale et al.

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2012) may be more sensitive to acidification than those services (like recreational fishing) that

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depend primarily on a few high-value species. Whereas artificial stocking may be a viable means

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of promoting the latter, emission controls may still be the most effective means of recovering the

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former. Furthermore, stocking of gamefish in lakes where they were historically absent may

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result in significant changes to lake ecology (Knapp 2005, Whittier and Kincaid 1999) and

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consequently may reduce flows of cultural and supporting services that depend on functioning

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native ecosystems. Although we do not know which of the ALTM study lakes were historically

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fishless or troutless, it has been estimated that approximately 16% of acidified lakes in the

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Adirondacks had originally been without native fish populations (Jenkins et al. 2005). For these

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lakes, fish stocking – although it may improve recreational fishing values – would interfere with

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recovery of historical ecosystems, a valued objective in its own right.

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Lastly, our study highlights that ecosystem “recovery” is not a monolithic concept. Whether or

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not an ecosystem is seen as recovered depends largely on what indicators or benchmarks are

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used to assess and define that recovery – and choice of indicators is inextricably linked to the


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values, benefits and conditions that society is seeking to restore or improve. For example, the use

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of acid-sensitive cyprinids as indicators (instead of game fish) might result in the conclusion that

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a particular lake had not recovered, even though populations of less-sensitive game species (and

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therefore, recreational fishing values) may have recovered relative to historical conditions.

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Conversely, the use of trout as an indicator species may serve as a good indicator of whether

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trout fishing opportunities have recovered, but a poor indicator for the recovery of species and

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services that depend on the entire ecosystem and its species assemblages and food webs. In both

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these cases, the use of indicator species that were not necessarily present in all lakes prior to

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acidification risks confusing novelty with recovery – and such indicators may in fact be inversely

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related to some ecosystem services associated with native fishless ecosystems. When trying to

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understand the overall recovery of complex social-ecological systems – like freshwater systems

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in the Adirondacks – it is important to monitor and analyze a suite of indicators appropriate to

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the many ecosystem services, objectives, and conditions that society values.

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ACKNOWLEDGEMENTS

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This research was supported by a grant from the New York State Energy Research and

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Development Authority (NYSERDA) Environmental Monitoring, Evaluation and Protection

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(EMEP) program. The EMEP program provides principal support for the historical and long-

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term datasets produced by the Adirondack Lake Survey Corporation (ALSC), which made this

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research possible.



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LITERATURE CITED

361

Aber, J.D., and C.T. Driscoll. 1997. Effects of land use, climate variation, and N deposition on N

362

cycling and C storage in northern hardwood forests (Paper 97GB01366). Glob.

363

Biogeochem. Cycles. 11: 639–468.

364

Aber, J.D. and C.A. Federer. 1992. A generalized, lumped-parameter model of photosynthesis,

365

evapotranspiration and net primary production in temperate and boreal forest ecosystems.

366

Oecologia. 92: 463–474.

367 368

369

Aber, J.D. S.V. Ollinger, and C.T. Driscoll. 1997. Modeling nitrogen saturation in forest ecosystems in response to land use and atmospheric deposition. Ecol. Model. 101: 61–78. Baker, J.P., S.W. Christensen, C.S. Creager, W. Warren-Hicks, and L. Godbout. 1988.

370

Identification of Critical Values for Effects on Fish Populations. Final Report submitted

371

to the US Environmental Protection Agency, Washington, DC.

372

Beier, C.M., J. Caputo, and P.M. Groffman. 2015. Measuring ecosystem capacity to provide

373

regulating services: forest removal and recovery at Hubbard Brook (USA). Ecological

374

Applications. 25(7): 2011-2021.

375

Boyle, K., R. Bishop, J. Caudill, J. Charbonneau, D. Larson, M.A. Markowski, R. E. Unsworth,

376

and R.W. Paterson. 1999. A Meta Analysis of Sport Fishing Values. Prepared for the

377

U.S. Department of the Interior, Fish and Wildlife Service, Economics Division. 64 p.

378

Caputo, J., C.M. Beier, P.M. Groffman, D.A. Burns, F.D. Beall, P.W. Hazlett, and T.E. Yorks.

379

2016a. Effects of harvesting forest biomass on water and climate regulation services: a


Page 19 of 32


19

380

synthesis of long-term ecosystem experiments in eastern North America. Ecosystems.

381

19(2): 271 – 283.

382

Caputo, J., C.M. Beier, T.J. Sullivan, and G.B. Lawrence. 2016b. Modeled effects of soil

383

acidification on long-term ecological and economic outcomes for managed forests in

384

Adirondack region (USA). Science of the Total Environment. 565: 401 – 411.

385

Cardinale, B.J., J.E. Duffy, A. Gonzalez, D.U. Hooper, C. Perrings, P. Venail, A. Narwani, G.M.

386

MacE, D. Tilman, D.A. Wardle, A.P. Kinzig, G.C. Daily, M. Loreau, J.B. Grace, A.

387

Larigauderie, D.S. Srivastava, and S. Naeem. 2012. Biodiversity loss and its impact on

388

humanity. Nature. 486: 59–67.

389

Cone, R. S., D.S. Robson, and C.C. Krueger. 1988. Failure of statistical tests to detect

390

assumption violations in the mark-recapture population estimation of brook trout in

391

Adirondack ponds. North American Journal of Fisheries Management. 8(4): 489-496.

392

Driscoll, C. T., C. P. Cirmo, T. J. Fahey, V. L. Blette, P. A. Bukaveckas, D. A. Burns, C. P.

393

Gubala, D. J. Leopold, R. M. Newton, D. J. Raynal, C. L. Schofield, J. B. Yavitt, and D.

394

B. Porcella. 1996. The experimental watershed liming study: Comparison of lake and

395

watershed neutralization strategies. Biogeochemistry. 32:143-174.

396

Driscoll, C.T., K. M. Driscoll, H. Fakhraei, and K. Civerolo. 2016. Long-term temporal trends

397

and spatial patterns in the acid-base chemistry of lakes in the Adirondack Region of New

398

York in response to decreases in acidic deposition. Atmospheric Environment. 146: 5-14.

399

Driscoll, C.T., G.B. Lawrence, A.J. Bulger, T.J. Butler, C.S. Cronan, C. Eagar, K.F. Lambert,

400

G.E. Likens, J.L. Stoddard and K.C. Weathers. 2001. Acidic deposition in the



Page 20 of 32

20

401

northeastern United States: Sources and inputs, ecosystem effects, and management

402

strategies. Bioscience. 51(3):180-198.

403

Driscoll, C.T., R.M. Newton, C.P. Gubala, J.P. Baker, and S.W. Christensen. 1991. Adirondack

404

Mountains. In Acidic Deposition and Aquatic Ecosystems (pp. 133-202). Springer New

405

York.

406

Driscoll, C.T., M.D. Lehtinen, and T.J. Sullivan. 1994. Modeling the acid-base chemistry of

407

organic solutes in Adirondack, NY, lakes. Water Resour. Res. 30: 297–306.

408

Fakhraei, H., C.T. Driscoll, P. Selvendiran, J.V. DePinto, J. Bloomfield, S. Quinn, and H.C.

409

Rowell. 2014. Development of a total maximum daily load (TMDL) for acid-impaired

410

lakes in the Adirondack region of New York. Atmospheric Environment. 95: 277-287.

411

Fakhraei, H., and C.T. Driscoll. 2015. Proton and Aluminum Binding Properties of Organic

412

Acids in Surface Waters of the Northeastern U.S. Environ. Sci. Technol. 49: 2939–2947.

413

García-Llorente, M., B, Martín-López, S. Díaz, and C. Montes. 2011. Can ecosystem properties

414

be fully translated into service values? an economic valuation of aquatic plant services.

415

Ecol. Appl. 21: 3083–3103.

416

Gbondo-Tugbawa, S.S., C.T. Driscoll, J.D. Aber and G.E. Likens. 2001. Evaluation of an

417

integrated biogeochemical model (PnET-BGC) at a northern hardwood forest ecosystem.

418

Water Resour. Res. 37(4):1057-1070.

419 420

Gunn, J.M. and K.H. Mills. 1998. The potential for restoration of acid-damaged lake trout lakes. Restoration Ecology. 6(4): 390-397.


Page 21 of 32


21

421 422

423

Hughes, J.M. 2015. Recreational fisheries in the USA: economics, management strategies, and ecological threats. Fisheries Science. 81(1):1-9. Jenkins, J., K. Roy, C. Driscoll, and C. Buerkett. 2005. Acid Rain and the Adirondacks: A

424

Research Summary. Adirondack Lakes Survey Corporation. Ray Brook, New York,

425

12977. 244 p.

426

Josephson, D.C., J.M. Robinson, J. Chiotti, K.J. Jirka and C.E. Kraft. 2014. Chemical and

427

biological recovery from acid deposition within the Honnedaga Lake watershed, New

428

York, USA. Environ. Monit. Assess. 186(7): 4391-4409.

429

Kahl, J.S., J.L. Stoddard, R. Haeuber, S.G. Paulsen, R. Birnbaum, F.A. Deviney, J.R. Webb,

430

D.R. Dewalle, W. Sharpe, C.T. Driscoll, A.T. Herlihy, J.H. Kellogg, P.S. Murdoch, K.M.

431

Roy, K.E. Webster, and N.S. Urquhart. 2004. Have U.S. surface waters responded to the

432

1990 Clean Air Act Amendments? Environ. Sci. Technol. 38: 484-490.

433 434

435 436

437

Knapp, R.A. 2005. Effects of nonnative fish and habitat characteristics on lentic herpetofauna in Yosemite National Park, USA. Biological Conservation. 121: 265–279. Krutilla, J.V. 1967. Conservation reconsidered. The American Economic Review. 57(4): 777786. Lachance, S., P. Bérubé, and M. Lemieux. 2000. In situ survival and growth of three brook trout

438

(Salvelinus fontinalis) strains subjected to acid conditions of anthropogenic origin at the

439

egg and fingerling stages. Canadian Journal of Fisheries and Aquatic Sciences. 57(8):

440

1562-1573.



Page 22 of 32

22

441

Lampman, G. (project manager), K. Roy, N. Houck, P. Hyde, M. Cantwell, and J. Brown. 2011.

442

The Adirondack Long–Term Monitoring Lakes: A Compendium of Site Descriptions,

443

Recent Chemistry and Selected Research Information. Final Report. No. 11-12. New

444

York Energy Research and Development Authority. 298 p.

445

Loomis, J. and L. Richardson. 2008. USER MANUAL: Benefit Transfer and Visitor Use

446

Estimating Models of Wildlife Recreation, Species, and Habitats. National Council for

447

Science and the Environment, 2006 Wildlife Habitat Policy Research Program. 24 p.

448

Lovett, G.M., T.H. Tear, D.C. Evers, S.E.G. Findlay, B.J. Cosby, J.K. Dunscomb, C.T. Driscoll

449

and K.C. Weathers. 2009. Effects of air pollution on ecosystems and biological diversity

450

in the eastern United States. Annals of the New York Academy of Sciences. 1162:99-135.

451 452

453 454

455

Menz, F.C. and C.T. Driscoll. 1983. An estimate of the costs of liming to neutralize acidic adirondack surface. Water Resour. Res. 19(5):1139-1149. Millenium Ecosystem Assessment. 2005. Ecosystems and human well-being: synthesis. Island Press, Washington, D.C. National Atmospheric Deposition Program. 2015a. National Atmospheric Deposition Program

456

2014 Annual Summary. NADP Data Report 2015-01. Illinois State Water Survey,

457

University of Illinois at Urbana-Champaign, IL.

458

National Atmospheric Deposition Program. 2015b. Critical Loads of Atmospheric Deposition

459

Science Committee; 2015 Summary of Critical Load Maps. NADP Data Report 2015-02.

460

Illinois State Water Survey, University of Illinois at Urbana-Champaign, IL.


Page 23 of 32


23

461 462

463

Plummer, M.L. 2009. Assessing benefit transfer for the valuation of ecosystem services. Frontiers in Ecology and the Environment. 7: 38–45. Pourmokhtarian, A., C. T. Driscoll, J. L. Campbell, and K. Hayhoe. 2012. Modeling potential

464

hydrochemical responses to climate change and rising CO2 at the Hubbard Brook

465

Experimental Forest using a dynamic biogeochemical model (PnET-BGC). Water

466

Resources Research. 48: W07514.

467 468

469 470

471 472

473

R Core Team. 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. Schofield, C.L. and C.T. Driscoll. 1987. Fish species distribution in relation to water quality gradients in the North Branch of the Moose River Basin. Biogeochemistry. 3(1-3):63-85. Snucins, E. and J.M. Gunn. 2003. Use of rehabilitation experiments to understand the recovery dynamics of acid-stressed fish populations. Ambio. 32(3): 240-243. Strock, K.E., S.J. Nelson, J.S. Kahl, J.E. Saros, and W.H. McDowell. 2014. Decadal trends

474

reveal recent acceleration in the rate of recovery from acidification in the northeastern

475

U.S. Environ. Sci. Technol. 48: 4681-4689.

476

Sutherland, J.W., F.W. Acker, J.A. Bloomfield, C.W. Boylen, D.F. Charles, R.A. Daniels, L.W.

477

Eichler, J.L. Farrell, R.S. Feranec, M.P. Hare, S.L. Kanfoush, R.J. Preall, S.O. Quinn,

478

H.C. Rowell, W.F. Schoch, W.H. Shaw, C.A. Siegfried, T.J. Sullivan, D.A. Winkler and

479

S.A. Nierzwicki-Bauer. 2015. Brooktrout Lake case study: Biotic recovery from acid

480

deposition 20 years after the 1990 clean air act amendments. Environ. Sci. Technol.

481

49(5): 2665-2674.



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24

482

Tammi, J., M. Appelberg, U. Beier, T. Hesthagen, A. Lappalainen, and M. Rask. 2003. Fish

483

status survey of Nordic lakes: effects of acidification, eutrophication, and stocking acidity

484

on present fish species composition. Ambio. 32(2): 98-105.

485

U.S. Department of Labor, Bureau of Labor Statistics. 2015. Consumer Price Index (CPI)

486

Inflation Calculator. http://www.bls.gov/data/inflation_calculator.htm. Accessed 19

487

August 2015.

488 489

490

U.S. Environmental Protection Agency. 2013. 2012 Progress Report: SO2 and NOX Emissions, Compliance, and Market Analysis. Van Houtven, G., C. Mansfield, D.J. Phaneuf, R. von Haefen, B. Milstead, M.A. Kenney and

491

K.H. Reckhow. 2014. Combining expert elicitation and stated preference methods to

492

value ecosystem services from improved lake water quality. Ecol. Econ. 99:40-52.

493

Van Offelen, C.C. Krueger, and C.L. Schofield. 1993. Survival, growth, movement, and

494

distribution of two brook trout strains stocked into small Adirondack streams. North

495

American Journal of Fisheries Management. 13(1): 86-95.

496

Whittier, T.R., and T.M. Kincaid. 1999. Introduced fish in Northeastern USA lakes: regional

497

extent, dominance, and effect on native species richness. Transactions of the American

498

Fisheries Society. 128: 769–783.

499

Zhou, Q., C.T. Driscoll and T.J. Sullivan. 2015. Responses of 20 lake-watersheds in the

500

Adirondack region of New York to historical and potential future acidic deposition. Sci.

501

Total Environ. 511:186-194.


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502

Table 1. Trout and other game fish found within 52 lakes in the Adirondack region, NY, USA. Trouts*

Other game fish

Salmo trutta

Ameiurus nebulosus

Salvelinus fontinalis

Lepomis gibbosus

Salvelinus namaycush

Lepomis auritus

Salvelinus namaycush X Salvelinus fontinalis

Esox lucius Esox niger Micropterus salmoides Micropterus dolomieu Salmo salar Perca flavescens Ambloplites rupestris Semotilus corporalis Osmerus mordax Coregonus clupeaformis

503

*

the term ‘trouts’ includes brown trout (Salmo trutta) in addition to the chars (Salvelinus spp.)



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504

Table 2. Results from logistic regression models predicting presence of trout and other game fish

505

in 52 lakes of the Adirondacks, NY, USA, based on lake pH and whether or not lakes had been

506

previously stocked with trout (1 = unstocked, 0 = stocked). Trouts*,** Estimate

Std. Error

Z value

P(>|Z)

β0

-8.63

3.19

-2.71

0.007

β1 (pH)

1.87

0.60

3.11

0.002

β2 (unstocked)

-2.23

0.79

-2.83

0.005

Other game fishǂ Estimate

Std. Error

Z value

P(>|Z)

β0

-6.80

2.47

-2.75

0.006

β1 (pH)

1.22

0.44

2.76

0.006

507

*

508

**

509

ǂ

the term ‘trouts’ includes brown trout (Salmo trutta) in addition to the chars (Salvelinus spp.) residual deviance: 46.710 on 49 degrees of freedom (P=0.434)

residual deviance: 62.981 on 50 degrees of freedom (P=0.897)


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27

510

Figure 1. Probability of finding trout and other game fish in 52 lakes of the Adirondacks, NY,

511

USA, based on pH and stocking status of trout.

512

Figure 2. Expected value of recreational fisheries in 52 lakes of the Adirondacks, NY, USA,

513

based on pH and stocking status of trout.

514

Figure 3. Simulated change in expected value of recreational fisheries in 21 lakes in the

515

Adirondacks, NY, USA across three pollution reduction scenarios and two trout stocking

516

scenarios. Acid pollution reduction refers to the reduction of nitrogen and sulfur emissions

517

relative to current levels. Trout stocking scenarios include one in which it is assumed that lakes

518

have been stocked with trout (all stocking) and one in which the actual historical stocking status

519

of each lake was maintained (current stocking). Plotted lines are smoothed approximations

520

(GAM smoother); confidence envelopes show 95% confidence intervals.

521

Figure 4. Expected value (simulated) of recreational fisheries in 21 lakes in the year 2200 in the

522

Adirondacks, NY, USA across three pollution reduction scenarios and two trout stocking

523

scenarios. Acid pollution reduction refers to the reduction of nitrogen and sulfur emissions

524

relative to current levels. Trout stocking scenarios include one in which it is assumed that lakes

525

have been stocked with trout (all stocking) and one in which the actual historical stocking status

526

of each lake was maintained (current stocking).



ABSTRACT 70x47mm (300 x 300 DPI)


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Figure 1. Probability of finding trout and other game fish in 52 lakes of the Adirondacks, NY, USA, based on pH and stocking status of trout. Figure 1 177x177mm (300 x 300 DPI)



Figure 2. Expected value of recreational fisheries in 52 lakes of the Adirondacks, NY, USA, based on pH and stocking status of trout. Figure 2 177x177mm (300 x 300 DPI)


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Figure 3. Simulated change in expected value of recreational fisheries in 21 lakes in the Adirondacks, NY, USA across three pollution reduction scenarios and two trout stocking scenarios. Acid pollution reduction refers to the reduction of nitrogen and sulfur emissions relative to current levels. Trout stocking scenarios include one in which it is assumed that lakes have been stocked with trout (all stocking) and one in which the actual historical stocking status of each lake was maintained (current stocking). Plotted lines are smoothed approximations (GAM smoother); confidence envelopes show 95% confidence intervals. Figure 3 177x177mm (300 x 300 DPI)



Figure 4. Expected value (simulated) of recreational fisheries in 21 lakes in the year 2200 in the Adirondacks, NY, USA across three pollution reduction scenarios and two trout stocking scenarios. Acid pollution reduction refers to the reduction of nitrogen and sulfur emissions relative to current levels. Trout stocking scenarios include one in which it is assumed that lakes have been stocked with trout (all stocking) and one in which the actual historical stocking status of each lake was maintained (current stocking). Figure 4 177x177mm (300 x 300 DPI)


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Impacts of Acidification and Potential Recovery on the Expected Value

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