Browsing by Author "Richardson, David C."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
- Analysis of high-frequency and long-term data in undergraduate ecology classes improves quantitative literacyKlug, Jennifer L.; Carey, Cayelan C.; Richardson, David C.; Gougis, Rebekka Darner (Ecological Society of America, 2017-03)Ecologists are increasingly analyzing long-term and high-frequency sensor datasets as part of their research. As ecology becomes a more data-rich scientific discipline, the next generation of ecologists needs to develop the quantitative literacy required to effectively analyze,visualize, and interpret large datasets. We developed and assessed three modules to teach undergraduate freshwater ecology students both scientific concepts and quantitative skills needed to work with large datasets. These modules covered key ecological topics of phenology, physical mixing, and the balance between primary production and respiration, using lakes as model systems with high-frequency or long-term data. Our assessment demonstrated that participating in these modules significantly increased student comfort using spreadsheet software and their self-reported competence in performing a variety of quantitative tasks. Interestingly, students with the lowest pre-module comfort and skills achieved the biggest gains. Furthermore, students reported that participating in the modules helped them better understand the concepts presented and that they appreciated practicing quantitative skills. Our approach demonstrates that working with large datasets in ecology classrooms helps undergraduate students develop the skills and knowledge needed to help solve complex ecological problems and be more prepared for a data-intensive future.
- Dynamics of the stream-lake transitional zone affect littoral lake metabolismWard, Nicole K.; Brentrup, Jennifer A.; Richardson, David C.; Weathers, Kathleen C.; Hanson, Paul C.; Hewett, Russell J.; Carey, Cayelan C. (Springer, 2022-07)Lake ecosystems, as integrators of watershed and climate stressors, are sentinels of change. However, there is an inherent time-lag between stressors and whole-lake response. Aquatic metabolism, including gross primary production (GPP) and respiration (R), of stream-lake transitional zones may bridge the time-lag of lake response to allochthonous inputs. In this study, we used high-frequency dissolved oxygen data and inverse modeling to estimate daily rates of summer epilimnetic GPP and R in a nutrient-limited oligotrophic lake at two littoral sites located near different major inflows and at a pelagic site. We examined the relative importance of stream variables in comparison to meteorological and in-lake predictors of GPP and R. One of the inflow streams was substantially warmer than the other and primarily entered the lake's epilimnion, whereas the colder stream primarily mixed into the metalimnion or hypolimnion. Maximum GPP and R rates were 0.2-2.5 mg O-2 L-1 day(-1) (9-670%) higher at littoral sites than the pelagic site. Ensemble machine learning analyses revealed that > 30% of variability in daily littoral zone GPP and R was attributable to stream depth and stream-lake transitional zone mixing metrics. The warm-stream inflow likely stimulated littoral GPP and R, while the cold-stream inflow only stimulated littoral zone GPP and R when mixing with the epilimnion. The higher GPP and R observed near inflows in our study may provide a sentinel-of-the-sentinel signal, bridging the time-lag between stream inputs and in-lake processing, enabling an earlier indication of whole-lake response to upstream stressors.
- Intra- and inter-annual variability in metabolism in an oligotrophic lakeRichardson, David C.; Carey, Cayelan C.; Bruesewitz, Denise A.; Weathers, Kathleen C. (2017-04)Lakes are sentinels of change in the landscapes in which they are located. Changes in lake function are reflected in whole-system metabolism, which integrates ecosystem processes across spatial and temporal scales. Recent improvements in high-frequency open-water metabolism modeling techniques have enabled estimation of rates of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) at high temporal resolution. However, few studies have examined metabolic rates over daily to multi-year temporal scales, especially in oligotrophic ecosystems. Here, we modified a metabolism modeling technique to reveal substantial intra- and inter-annual variability in metabolic rates in Lake Sunapee, a temperate, oligotrophic lake in New Hampshire, USA. Annual GPP and R increased each summer, paralleling increases in littoral, but not pelagic, total phosphorus concentrations. Storms temporarily decoupled GPP and R, resulting in greater decreases in GPP than R. Daily rates of GPP and R were positively correlated on warm days that had stable water columns, and metabolism model fits were best on warm, sunny days, indicating the importance of lake physics when evaluating metabolic rates. These metabolism data span a range of temporal scales and together suggest that Lake Sunapee may be moving toward mesotrophy. We suggest that functional, integrative metrics, such as metabolic rates, are useful indicators and sentinels of ecosystem change. We also highlight the challenges and opportunities of using high-frequency measurements to elucidate the drivers and consequences of intra- and inter-annual variability in metabolic rates, especially in oligotrophic lakes.
- Transparency, Geomorphology and Mixing Regime Explain Variability in Trends in Lake Temperature and Stratification across Northeastern North America (1975–2014)Richardson, David C.; Melles, Stephanie J.; Pilla, Rachel M.; Hetherington, Amy L.; Knoll, Lesley B.; Williamson, Craig E.; Kraemer, Benjamin M.; Jackson, James R.; Long, Elizabeth C.; Moore, Karen; Rudstam, Lars G.; Rusak, James A.; Saros, Jasmine E.; Sharma, Sapna; Strock, Kristin E.; Weathers, Kathleen C.; Wigdahl-Perry, Courtney R. (MDPI, 2017-06-20)Lake surface water temperatures are warming worldwide, raising concerns about the future integrity of valuable lake ecosystem services. In contrast to surface water temperatures, we know far less about what is happening to water temperature beneath the surface, where most organisms live. Moreover, we know little about which characteristics make lakes more or less sensitive to climate change and other environmental stressors. We examined changes in lake thermal structure for 231 lakes across northeastern North America (NENA), a region with an exceptionally high density of lakes. We determined how lake thermal structure has changed in recent decades (1975–2012) and assessed which lake characteristics are related to changes in lake thermal structure. In general, NENA lakes had increasing near-surface temperatures and thermal stratification strength. On average, changes in deepwater temperatures for the 231 lakes were not significantly different than zero, but individually, half of the lakes experienced warming and half cooling deepwater temperature through time. More transparent lakes (Secchi transparency >5 m) tended to have higher near-surface warming and greater increases in strength of thermal stratification than less transparent lakes. Whole-lake warming was greatest in polymictic lakes, where frequent summer mixing distributed heat throughout the water column. Lakes often function as important sentinels of climate change, but lake characteristics within and across regions modify the magnitude of the signal with important implications for lake biology, ecology and chemistry.