Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake’s watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near‐stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near‐stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake‐specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.
Using a dataset of more than 51,000 US lakes, we estimated the relationship between summertime lake visits, lake water clarity, landscape features, and other amenities, where visits were estimated with counts of geo‐located photographs. Given the size and complexity of our dataset, we used a combination of machine learning techniques, imputation techniques, and a Poisson count model to estimate these relationships. We found that every additional meter of average summertime Secchi depth was associated with at least 7% more summertime lake visits, all else equal. Second, we found that lake amenities, such as beaches, boat launches, and public toilets, were more powerful predictors of visits than water clarity. Third, we found that visits to a lake were strongly influenced by the lake's accessibility and its distance to nearby lakes and the amenities the nearby lakes offered. Our research highlights the need for (1) a better understanding of how representative social media data are of actual recreational behavior, (2) the development of best practices to account for nonrandom patterns in missing natural feature data, and (3) a better understanding of the potential endogeneity in the lake visit–water quality relationships.
more » « less- NSF-PAR ID:
- 10405600
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 14
- Issue:
- 4
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll
a concentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophylla in high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world. -
The phenology of critical biological events in aquatic ecosystems are rapidly shifting due to climate change. Growing variability in phenological cues can increase the likelihood of trophic mismatches, causing recruitment failures in commercially, culturally, and recreationally important fisheries. We tested for changes in spawning phenology of regionally important walleye (Sander vitreus) populations in 194 Midwest US lakes in Minnesota, Michigan, and Wisconsin spanning 1939-2019 to investigate factors influencing walleye phenological responses to climate change and associated climate variability, including ice-off timing, lake physical characteristics, and population stocking history. Data from Wisconsin and Michigan lakes (185 and 5 out of 194 total lakes, respectively) were collected by the Wisconsin Department of Natural Resources (WDNR) and the Great Lakes Indian Fish and Wildlife Commission (GLIFWC) through standardized spring walleye mark-recapture surveys and spring tribal harvest season records. Standardized spring mark-recapture population estimates are performed shortly after ice-off, where following a marking event, a subsequent recapture sampling event is conducted using nighttime electrofishing (typically AC – WDNR, pulsed-DC – GLIFWC) of the entire shoreline including islands for small lakes and index stations for large lakes (Hansen et al. 2015) that is timed to coincide with peak walleye spawning activity (G. Hatzenbeler, WDNR, personal communication; M. Luehring, GLIFWC, personal communication; Beard et al. 1997). Data for four additional Minnesota lakes were collected by the Minnesota Department of Natural Resources (MNDNR) beginning in 1939 during annual collections of walleye eggs and broodstock (Schneider et al. 2010), where date of peak egg take was used to index peak spawning activity. For lakes where spawning location did not match the lake for which the ice-off data was collected, the spawning location either flowed into (Pike River) or was within 50 km of a lake where ice-off data were available (Pine River) and these ice-off data were used. Following the affirmation of off-reservation Ojibwe tribal fishing rights in the Ceded Territories of Wisconsin and the Upper Peninsula of Michigan in 1987, tribal spearfishers have targeted walleye during spring spawning (Mrnak et al. 2018). Nightly harvests are recorded as part of a compulsory creel survey (US Department of the Interior 1991). Using these records, we calculated the date of peak spawning activity in a given lake-year as the day of maximum tribal harvest. Although we were unable to account for varying effort in these data, a preliminary analysis comparing spawning dates estimated using tribal harvest to those determined from standardized agency surveys in the same lake and year showed that they were highly correlated (Pearson’s correlation: r = 0.91, P < 0.001). For lakes that had walleye spawning data from both agency surveys and tribal harvest, we used the data source with the greatest number of observation years. Ice-off phenology data was collected from two sources – either observed from the Global Lake and River Ice Phenology database (Benson et al. 2000)t, or modeled from a USGS region-wide machine-learning model which used North American Land Data Assimilation System (NLDAS) meteorological inputs combined with lake characteristics (lake position, clarity, size, depth, hypsography, etc.) to predict daily water column temperatures from 1979 - 2022, from which ice-off dates could be derived (https://www.sciencebase.gov/catalog/item/6206d3c2d34ec05caca53071; see Corson-Dosch et al. 2023 for details). Modeled data for our study lakes (see (Read et al. 2021) for modeling details), which performed well in reflecting ice phenology when compared to observed data (i.e., highly significant correlation between observed and modeled ice-off dates when both were available; r = 0.71, p < 0.001). Lake surface area (ha), latitude, and maximum depth (m) were acquired from agency databases and lake reports. Lake class was based on a WDNR lakes classification system (Rypel et al. 2019) that categorized lakes based on temperature, water clarity, depth, and fish community. Walleye stocking history was defined using the walleye stocking classification system developed by the Wisconsin Technical Working Group (see also Sass et al. 2021), which categorized lakes based on relative contributions of naturally-produced and stocked fish to adult recruitment by relying heavily on historic records of age-0 and age-1 catch rates and stocking histories. Wisconsin lakes were divided into three groups: natural recruitment (NR), a combination of stocking and natural recruitment (C-ST), and stocked only (ST). Walleye natural recruitment was indexed as age-0 walleye CPE (number of age-0 walleye captured per km of shoreline electrofished) from WDNR and GLIFWC fall electrofishing surveys (see Hansen et al. 2015 for details). 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Abstract Mountain glaciers are retreating rapidly due to climate change, leading to the formation of downstream lakes. However, little is known about the physical and biogeochemical conditions in these lakes across a range of glacial influence. We surveyed alpine lakes fed by both glacial and snowpack meltwaters and those fed by snowpack alone to compare nutrient concentrations, stoichiometry, water clarity, chlorophyll, and zooplankton communities. Total phosphorus (TP) and soluble reactive phosphorus were two times higher in glacial lakes than in non‐glacial lakes, while nitrate concentrations were three times higher. However, organic carbon concentrations in glacial lakes were two times lower than in non‐glacial lakes. The carbon‐to‐phosphorus ratio and the nitrogen‐to‐phosphorus ratio of lake seston increased with water clarity in glacial lakes, suggesting that turbidity from glacial flour increases light limitation and increases stoichiometric food quality for zooplankton in newly formed lakes. However, chlorophyll
a concentrations did not differ between lake types. Through structural equation modeling, we found that glaciers exhibit a bidirectional association with nitrate and TP concentrations, perhaps mediated through landscape vegetation and lake clarity. Zooplankton communities in high‐turbidity glacial lakes were largely composed of cyclopoid copepods and rotifers (i.e., non‐filter feeders), while non‐glacial lakes tended to be dominated by calanoid copepods and cladocerans (i.e., filter feeders). Our results show that glacier‐influenced lakes have biogeochemical and ecological characteristics distinct from snow‐fed mountain lakes. Sustained studies are needed to assess the dynamics of these unique features as the influence of the alpine cryosphere fades under ongoing climate change. -
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Abstract The concentration of dissolved oxygen (DO) is an important attribute of aquatic ecosystems, influencing habitat, drinking water quality, biodiversity, nutrient biogeochemistry, and greenhouse gas emissions. While average summer DO concentrations are declining in lakes across the temperate zone, much remains unknown about seasonal factors contributing to deepwater DO losses. It is unclear whether declines are related to increasing rates of seasonal DO depletion or changes in seasonal stratification that limit re‐oxygenation of deep waters. Furthermore, despite the presence of important biological and ecological DO thresholds, there has been no large‐scale assessment of changes in the amount of habitat crossing these thresholds, limiting the ability to understand the consequences of observed DO losses. We used a dataset from >400 widely distributed lakes to identify the drivers of DO losses and quantify the frequency and volume of lake water crossing biologically and ecologically important threshold concentrations ranging from 5 to 0.5 mg/L. Our results show that while there were no consistent changes over time in seasonal DO depletion rates, over three‐quarters of lakes exhibited an increase in the duration of stratification, providing more time for seasonal deepwater DO depletion to occur. As a result, most lakes have experienced summertime increases in the amount of water below all examined thresholds in deepwater DO concentration, with increases in the proportion of the water column below thresholds ranging between 0.9% and 1.7% per decade. In the 30‐day period preceding the end of stratification, increases were greater at >2.2% per decade and >70% of analyzed lakes experienced increases in the amount of oxygen‐depleted water. These results indicate ongoing climate‐induced increases in the duration of stratification have already contributed to reduction of habitat for many species, likely increased internal nutrient loading, and otherwise altered lake chemistry. Future warming is likely to exacerbate these trends.
