Ian M. McCullough

Salting our freshwater lakes

Significance In lakes, chloride is a relatively benign ion at low concentrations but begins to have ecological impacts as concentrations rise into the 100s and 1,000s of mg L−1. In this study, we investigate long-term chloride trends in 371 freshwater lakes in North America. We find that in Midwest and Northeast North America, most urban lakes and rural lakes that are surrounded by >1% impervious land cover show increasing chloride trends. Expanding on this finding, thousands of lakes in these regions are at risk of long-term salinization. Keeping lakes “fresh” is critically important for protecting the ecosystem services freshwater lakes provide, such as drinking water, fisheries, recreation, irrigation, and aquatic habitat. The highest densities of lakes on Earth are in north temperate ecosystems, where increasing urbanization and associated chloride runoff can salinize freshwaters and threaten lake water quality and the many ecosystem services lakes provide. However, the extent to which lake salinity may be changing at broad spatial scales remains unknown, leading us to first identify spatial patterns and then investigate the drivers of these patterns. Significant decadal trends in lake salinization were identified using a dataset of long-term chloride concentrations from 371 North American lakes. Landscape and climate metrics calculated for each site demonstrated that impervious land cover was a strong predictor of chloride trends in Northeast and Midwest North American lakes. As little as 1% impervious land cover surrounding a lake increased the likelihood of long-term salinization. Considering that 27% of large lakes in the United States have >1% impervious land cover around their perimeters, the potential for steady and long-term salinization of these aquatic systems is high. This study predicts that many lakes will exceed the aquatic life threshold criterion for chronic chloride exposure (230 mg L−1), stipulated by the US Environmental Protection Agency (EPA), in the next 50 y if current trends continue.

Citizen science as an approach for overcoming insufficient monitoring and inadequate stakeholder buy-in in adaptive management: criteria and evidence

Adaptive management is broadly recognized as critical for managing natural resources, yet in practice it often fails to achieve intended results for two main reasons: insufficient monitoring and inadequate stakeholder buy-in. Citizen science is gaining momentum as an approach that can inform natural resource management and has some promise for solving the problems faced by adaptive management. Based on adaptive management literature, we developed a set of criteria for successfully addressing monitoring and stakeholder related failures in adaptive management and then used these criteria to evaluate 83 citizen science case studies from peer-reviewed literature. The results suggest that citizen science can be a cost-effective method to collect essential monitoring information and can also produce the high levels of citizen engagement that are vital to the adaptive management learning process. The analysis also provides a set of recommendations for citizen science program design that addresses spatial and temporal scale, data quality, costs, and effective incentives to facilitate participation and integration of findings into adaptive management.

Cross-scale modeling of surface temperature and tree seedling establishment in mountain landscapes

IntroductionEstimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized.MethodsUsing a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.ResultsThe surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.ConclusionPredicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Landsat imagery reveals declining clarity of Maine's lakes during 1995–2010

Abstract.  Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll a, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes >8 ha based on Landsat satellite data recorded during 1995–2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38 m during 1995–2010. Water clarity ranged from 4 to 6 m during 1995–2010, but it decreased consistently during 2005–2010. Clarity in both the northeastern and western lake regions has decreased from 5.22 m in 1995 to 4.36 and 4.21 m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50 m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.

High and dry: high elevations disproportionately exposed to regional climate change in Mediterranean-climate landscapes

ContextPredicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change.ObjectivesWe demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099).MethodsWe produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows.ResultsClimate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change.ConclusionsIn moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.

Place and process in conservation planning for climate change: a reply to Keppel and Wardell-Johnson

Conservation in the face of climate change is hindered by a preoccupation with place. ‘Refugial capacity’ [1] adds useful descriptive power to the terminology of place, while ‘stepping stones’ and ‘holdouts’ are terms that usefully describe the dynamics of place [2]. Ultimately, no matter what happens in the lexicon, conservation needs to be implemented with a shift in focus from place to process. It will not be easy.

A lake classification concept for a more accurate global estimate of the dissolved inorganic carbon export from terrestrial ecosystems to inland waters

The magnitude of lateral dissolved inorganic carbon (DIC) export from terrestrial ecosystems to inland waters strongly influences the estimate of the global terrestrial carbon dioxide (CO2) sink. At present, no reliable number of this export is available, and the few studies estimating the lateral DIC export assume that all lakes on Earth function similarly. However, lakes can function along a continuum from passive carbon transporters (passive open channels) to highly active carbon transformers with efficient in-lake CO2 production and loss. We developed and applied a conceptual model to demonstrate how the assumed function of lakes in carbon cycling can affect calculations of the global lateral DIC export from terrestrial ecosystems to inland waters. Using global data on in-lake CO2 production by mineralization as well as CO2 loss by emission, primary production, and carbonate precipitation in lakes, we estimated that the global lateral DIC export can lie within the range of 0.70−0.31+0.27

Fine-grain modeling of species’ response to climate change: holdouts, stepping-stones, and microrefugia

{0.70}_{-0.31}^{+0.27}