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2. A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Author

Sharma, Sapna, Gray, Derek K, Read, Jordan S, O’Reilly, Catherine M, Schneider, Philipp, Qudrat, Anam, Gries, Corinna, Stefanoff, Samantha, Hampton, Stephanie E, Hook, Simon, Lenters, John D, Livingstone, David M, McIntyre, Peter B, Adrian, Rita, Allan, Mathew G, Anneville, Orlane, Arvola, Lauri, Austin, Jay, Bailey, John, Baron, Jill S, Brookes, Justin, Chen, Yuwei, Daly, Robert, Dokulil, Martin, Dong, Bo, Ewing, Kye, de Eyto, Elvira, Hamilton, David, Havens, Karl, Haydon, Shane, Hetzenauer, Harald, Heneberry, Jocelyne, Hetherington, Amy L, Higgins, Scott N, Hixson, Eric, Izmest’eva, Lyubov R, Jones, Benjamin M, Kangur, Külli, Kasprzak, Peter, Köster, Olivier, Kraemer, Benjamin M, Kumagai, Michio, Kuusisto, Esko, Leshkevich, George, May, Linda, MacIntyre, Sally, Müller-Navarra, Dörthe, Naumenko, Mikhail, Noges, Peeter, Noges, Tiina, Niederhauser, Pius, North, Ryan P, Paterson, Andrew M, Plisnier, Pierre-Denis, Rigosi, Anna, Rimmer, Alon, Rogora, Michela, Rudstam, Lars, Rusak, James A, Salmaso, Nico, Samal, Nihar R, Schindler, Daniel E, Schladow, Geoffrey, Schmidt, Silke R, Schultz, Tracey, Silow, Eugene A, Straile, Dietmar, Teubner, Katrin, Verburg, Piet, Voutilainen, Ari, Watkinson, Andrew, Weyhenmeyer, Gesa A, Williamson, Craig E, and Woo, Kara H

Abstract

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.

Published
2015

4. Long‐term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross‐system analysis

Author

Strayer, David L., Adrian, Rita, Adamovich, Boris V., Aldridge, David C., Balogh, Csilla, Burlakova, Lyubov E., Fried‐Petersen, Hannah B., G.‐Tóth, László, Hetherington, Amy L., and Jones, Thomas S. [u.v.m.]

Subjects
population performance, biological invasions, Dreissena, invasive species, long‐term studies
Abstract

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.

Published
2019
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5. Integrating fast and slow processes is essential for simulating human-freshwater interactions

Author

Ward, Nicole K., Fitchett, Leah Lynn, Hart, Julia A., Shu, Lele, Stachelek, Joseph, Weng, Weizhe, Zhang, Yu, Dugan, Hilary A., Hetherington, Amy L., Boyle, Kevin J., Carey, Cayelan C., Cobourn, Kelly M., Hanson, Paul C., Kemanian, Armen R., Sorice, Michael G., Weathers, Kathleen C., Ward, Nicole K., Fitchett, Leah Lynn, Hart, Julia A., Shu, Lele, Stachelek, Joseph, Weng, Weizhe, Zhang, Yu, Dugan, Hilary A., Hetherington, Amy L., Boyle, Kevin J., Carey, Cayelan C., Cobourn, Kelly M., Hanson, Paul C., Kemanian, Armen R., Sorice, Michael G., and Weathers, Kathleen C.

Abstract

Integrated modeling is a critical tool to evaluate the behavior of coupled human–freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human–freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human–freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change.

Published
2019
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6. Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross-system analysis

Author

Biological Sciences, Strayer, David L., Adamovich, Boris, V., Adrian, Rita, Aldridge, David C., Balogh, Csilla, Burlakova, Lyubov E., FriedPetersen, Hannah B., G-Toth, Laszlo, Hetherington, Amy L., Jones, Thomas S., Karatayev, Alexander Y., Madill, Jacqueline B., Makarevich, Oleg A., Marsden, J. Ellen, Martel, Andre L., Minchin, Dan, Nalepa, Thomas F., Noordhuis, Ruurd, Robinson, Timothy J., Rudstam, Lars G., Schwalb, Astrid N., Smith, David R., Steinman, Alan D., Jeschke, Jonathan M., Biological Sciences, Strayer, David L., Adamovich, Boris, V., Adrian, Rita, Aldridge, David C., Balogh, Csilla, Burlakova, Lyubov E., FriedPetersen, Hannah B., G-Toth, Laszlo, Hetherington, Amy L., Jones, Thomas S., Karatayev, Alexander Y., Madill, Jacqueline B., Makarevich, Oleg A., Marsden, J. Ellen, Martel, Andre L., Minchin, Dan, Nalepa, Thomas F., Noordhuis, Ruurd, Robinson, Timothy J., Rudstam, Lars G., Schwalb, Astrid N., Smith, David R., Steinman, Alan D., and Jeschke, Jonathan M.

Abstract

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long-term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long-term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifi- cally, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long-term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1-2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large dedines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long-term dynamics of body size. The long-term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., pred

Published
2019

7. Environmental Modelling & Software

Author

Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, Hipsey, Matthew R., Bren School of Environmental Science and Management, University of California [Santa Barbara] (UCSB), University of California-University of California, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), CNR Water Research Institute (IRSA), Consiglio Nazionale delle Ricerche (CNR), Histoire culturelle et sociale de l'art (HiCSA), Université Paris 1 Panthéon-Sorbonne (UP1), Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques (CARRTEL), Institut National de la Recherche Agronomique (INRA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), MRC/CSO Social and Public Health Sciences Unit, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Biosystems Division [Roskilde], Risø National Laboratory for Sustainable Energy (Risø DTU), Technical University of Denmark [Lyngby] (DTU)-Technical University of Denmark [Lyngby] (DTU), Institut de Génétique Moléculaire de Montpellier (IGMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Australian Research Council (ARC) DP130104078 LP130100756, Biological Sciences, Helmholtz Centre for Environmental Research (UFZ), Université Panthéon-Sorbonne (UP1), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de la Recherche Agronomique (INRA), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Barbara] (UC Santa Barbara), University of California (UC)-University of California (UC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Danmarks Tekniske Universitet = Technical University of Denmark (DTU)-Danmarks Tekniske Universitet = Technical University of Denmark (DTU), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0106 biological sciences, Environmental Engineering, 010504 meteorology & atmospheric sciences, Network science, lake model, global observatory data, Stratification (water), Climate change, Model assessment, BAYESIAN HIERARCHICAL FRAMEWORK, 01 natural sciences, Latitude, stratification, Observatory, network science, AQUATIC BIOGEOCHEMICAL MODELS, Low correlation, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Trophic level, CLIMATE-CHANGE, REGIME SHIFTS, 010604 marine biology & hydrobiology, Ecological Modeling, SUB-ALPINE LAKE, model assessment, TEMPERATE LAKES, THERMAL STRUCTURE, ECOLOGICAL STATE, 13. Climate action, DYRESM-CAEDYM, Global observatory data, Climatology, [SDE]Environmental Sciences, CENTRAL-EUROPEAN LAKE, GLM, Lake model, Stratification, Software, 500 Naturwissenschaften und Mathematik::570 Biowissenschaften, Biologie::577 Ökologie, Thermocline
Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required. (c) 2017 Published by Elsevier Ltd. Australian Research Council (ARC)Australian Research Council [DP130104078, LP130100756] GLM development and funding support for LCB, BDB, CB and MRH was provided by the Australian Research Council (ARC) (grants DP130104078 & LP130100756). Additional contributions from individuals and organisations as well as sources of data, provided from a variety of organisations are summarised in Appendix D. This study was made possible through the sharing of ideas, data and models across the AEMON and GLEON networks as well as discussions and working groups held during AEMON workshops and GLEON meetings. Public domain – authored by a U.S. government employee

Published
2018
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8. Long‐term population dynamics of dreissenid mussels ( Dreissena polymorpha and D. rostriformis ): a cross‐system analysis

Author

Strayer, David L., primary, Adamovich, Boris V., additional, Adrian, Rita, additional, Aldridge, David C., additional, Balogh, Csilla, additional, Burlakova, Lyubov E., additional, Fried‐Petersen, Hannah B., additional, G.‐Tóth, László, additional, Hetherington, Amy L., additional, Jones, Thomas S., additional, Karatayev, Alexander Y., additional, Madill, Jacqueline B., additional, Makarevich, Oleg A., additional, Marsden, J. Ellen, additional, Martel, André L., additional, Minchin, Dan, additional, Nalepa, Thomas F., additional, Noordhuis, Ruurd, additional, Robinson, Timothy J., additional, Rudstam, Lars G., additional, Schwalb, Astrid N., additional, Smith, David R., additional, Steinman, Alan D., additional, and Jeschke, Jonathan M., additional

Published
2019
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9. A multi-lake comparative analysis of the General Lake Model (GLM) : Stress-testing across a global observatory network

Author

Bruce, Louise C, Frassl, Marieke A, Arhonditsis, George B, Gal, Gideon, Hamilton, David P, Hanson, Paul C, Hetherington, Amy L, Melack, John M, Read, Jordan S, Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I, Bocaniov, Serghei A, Boehrer, Bertram, Boon, Casper, Brookes, Justin D, Bueche, Thomas, Busch, Brendan D, Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D, MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G, Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J, Rusak, James A, Samal, Nihar R, Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R Iestyn, Yao, Huaxia, Hipsey, Matthew R, Bruce, Louise C, Frassl, Marieke A, Arhonditsis, George B, Gal, Gideon, Hamilton, David P, Hanson, Paul C, Hetherington, Amy L, Melack, John M, Read, Jordan S, Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I, Bocaniov, Serghei A, Boehrer, Bertram, Boon, Casper, Brookes, Justin D, Bueche, Thomas, Busch, Brendan D, Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D, MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G, Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J, Rusak, James A, Samal, Nihar R, Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R Iestyn, Yao, Huaxia, and Hipsey, Matthew R

Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.

Published
2018
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10. From concept to practice to policy: modeling coupled natural and human systems in lake catchments

Author

Cobourn, Kelly M., Carey, Cayelan C., Boyle, Kevin J., Duffy, Christopher J., Dugan, Hilary A., Farrell, Kaitlin J., Fitchett, Leah Lynn, Hanson, Paul C., Hart, Julia A., Henson, Virginia Reilly, Hetherington, Amy L., Kemanian, Armen R., Rudstam, Lars G., Shu, Lele, Soranno, Patricia A., Sorice, Michael G., Stachelek, Joseph, Ward, Nicole K., Weathers, Kathleen C., Weng, Weizhe, Zhang, Yu, Cobourn, Kelly M., Carey, Cayelan C., Boyle, Kevin J., Duffy, Christopher J., Dugan, Hilary A., Farrell, Kaitlin J., Fitchett, Leah Lynn, Hanson, Paul C., Hart, Julia A., Henson, Virginia Reilly, Hetherington, Amy L., Kemanian, Armen R., Rudstam, Lars G., Shu, Lele, Soranno, Patricia A., Sorice, Michael G., Stachelek, Joseph, Ward, Nicole K., Weathers, Kathleen C., Weng, Weizhe, and Zhang, Yu

Abstract

Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well‐developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual–empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi‐disciplinary tool that captures diverse processes that operate at multiple scales, including land‐management decision‐making, hydrologic‐solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross‐disciplinary dialogue to move CNHS lake‐catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision‐making and policy.

Published
2018
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11. A multi-lake comparative analysis of the General Lake Model (GLM): stress-testing across a global observatory network

Author

Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, Hipsey, Matthew R., Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, and Hipsey, Matthew R.

Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.

Published
2018

12. A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network

Author

Biological Sciences, Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke A., Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortes, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Oezkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frederic, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vincon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, Hipsey, Matthew R., Biological Sciences, Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke A., Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortes, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Oezkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frederic, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vincon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, and Hipsey, Matthew R.

Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required. (c) 2017 Published by Elsevier Ltd.

Published
2018

13. From concept to practice to policy: modeling coupled natural and human systems in lake catchments

Author

Agricultural and Applied Economics, Biological Sciences, Forest Resources and Environmental Conservation, Cobourn, Kelly M., Carey, Cayelan C., Boyle, Kevin J., Duffy, Christopher J., Dugan, Hilary A., Farrell, Kaitlin J., Fitchett, Leah Lynn, Hanson, Paul C., Hart, Julia A., Henson, Virginia Reilly, Hetherington, Amy L., Kemanian, Armen R., Rudstam, Lars G., Shu, Lele, Soranno, Patricia A., Sorice, Michael G., Stachelek, Joseph, Ward, Nicole K., Weathers, Kathleen C., Weng, Weizhe, Zhang, Yu, Agricultural and Applied Economics, Biological Sciences, Forest Resources and Environmental Conservation, Cobourn, Kelly M., Carey, Cayelan C., Boyle, Kevin J., Duffy, Christopher J., Dugan, Hilary A., Farrell, Kaitlin J., Fitchett, Leah Lynn, Hanson, Paul C., Hart, Julia A., Henson, Virginia Reilly, Hetherington, Amy L., Kemanian, Armen R., Rudstam, Lars G., Shu, Lele, Soranno, Patricia A., Sorice, Michael G., Stachelek, Joseph, Ward, Nicole K., Weathers, Kathleen C., Weng, Weizhe, and Zhang, Yu

Abstract

Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well‐developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual–empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi‐disciplinary tool that captures diverse processes that operate at multiple scales, including land‐management decision‐making, hydrologic‐solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross‐disciplinary dialogue to move CNHS lake‐catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision‐making and policy.

Published
2018

14. From concept to practice to policy: modeling coupled natural and human systems in lake catchments

Author

Cobourn, Kelly M., primary, Carey, Cayelan C., additional, Boyle, Kevin J., additional, Duffy, Christopher, additional, Dugan, Hilary A., additional, Farrell, Kaitlin J., additional, Fitchett, Leah, additional, Hanson, Paul C., additional, Hart, Julia A., additional, Henson, Virginia Reilly, additional, Hetherington, Amy L., additional, Kemanian, Armen R., additional, Rudstam, Lars G., additional, Shu, Lele, additional, Soranno, Patricia A., additional, Sorice, Michael G., additional, Stachelek, Jemma, additional, Ward, Nicole K., additional, Weathers, Kathleen C., additional, Weng, Weizhe, additional, and Zhang, Yu, additional

Published
2018
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15. A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network

Author

Bruce, Louise C., primary, Frassl, Marieke A., additional, Arhonditsis, George B., additional, Gal, Gideon, additional, Hamilton, David P., additional, Hanson, Paul C., additional, Hetherington, Amy L., additional, Melack, John M., additional, Read, Jordan S., additional, Rinke, Karsten, additional, Rigosi, Anna, additional, Trolle, Dennis, additional, Winslow, Luke, additional, Adrian, Rita, additional, Ayala, Ana I., additional, Bocaniov, Serghei A., additional, Boehrer, Bertram, additional, Boon, Casper, additional, Brookes, Justin D., additional, Bueche, Thomas, additional, Busch, Brendan D., additional, Copetti, Diego, additional, Cortés, Alicia, additional, de Eyto, Elvira, additional, Elliott, J. Alex, additional, Gallina, Nicole, additional, Gilboa, Yael, additional, Guyennon, Nicolas, additional, Huang, Lei, additional, Kerimoglu, Onur, additional, Lenters, John D., additional, MacIntyre, Sally, additional, Makler-Pick, Vardit, additional, McBride, Chris G., additional, Moreira, Santiago, additional, Özkundakci, Deniz, additional, Pilotti, Marco, additional, Rueda, Francisco J., additional, Rusak, James A., additional, Samal, Nihar R., additional, Schmid, Martin, additional, Shatwell, Tom, additional, Snorthheim, Craig, additional, Soulignac, Frédéric, additional, Valerio, Giulia, additional, van der Linden, Leon, additional, Vetter, Mark, additional, Vinçon-Leite, Brigitte, additional, Wang, Junbo, additional, Weber, Michael, additional, Wickramaratne, Chaturangi, additional, Woolway, R. Iestyn, additional, Yao, Huaxia, additional, and Hipsey, Matthew R., additional

Published
2018
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16. Transparency, Geomorphology and Mixing Regime Explain Variability in Trends in Lake Temperature and Stratification across Northeastern North America (1975–2014)

Author

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., 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., and Wigdahl-Perry, Courtney R.

Abstract

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.

Published
2017
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17. Transparency, Geomorphology and Mixing Regime Explain Variability in Trends in Lake Temperature and Stratification across Northeastern North America (1975–2014)

Author

Biological Sciences, 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., Biological Sciences, 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., and Wigdahl-Perry, Courtney R.

Abstract

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.

Published
2017

18. Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

Author

Dugan, Hilary A., Woolway, R. Iestyn, Santoso, Arianto B., Corman, Jessica R., Jaimes, Aline, Nodine, Emily R., Patil, Vijay P., Zwart, Jacob A., Brentrup, Jennifer A., Hetherington, Amy L., Oliver, Samantha K., Read, Jordan S., Winters, Kirsten M., Hanson, Paul C., Read, Emily K., Winslow, Luke A., Weathers, Kathleen C., Dugan, Hilary A., Woolway, R. Iestyn, Santoso, Arianto B., Corman, Jessica R., Jaimes, Aline, Nodine, Emily R., Patil, Vijay P., Zwart, Jacob A., Brentrup, Jennifer A., Hetherington, Amy L., Oliver, Samantha K., Read, Jordan S., Winters, Kirsten M., Hanson, Paul C., Read, Emily K., Winslow, Luke A., and Weathers, Kathleen C.

Abstract

Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient (k) to model gas exchange with the atmosphere. Theoretical and empirically based models of k range in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of k influenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.

Published
2016

20. High-frequency lake data benefit society through broader engagement with stakeholders: a synthesis of GLEON data use survey and membe rexperiences

Author

Smyth, Robyn L., primary, Caruso, Alicia, additional, Borre, Lisa, additional, Zhu, Guangwei, additional, Zhu, Mengyuan, additional, Hetherington, Amy L., additional, Jennings, Eleanor, additional, Klug, Jennifer L., additional, Piccolo, Maria Cintia, additional, Rusak, James A., additional, Weathers, Kathleen C., additional, and Wigdahl-Perry, Courtney, additional

Published
2016
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21. Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

Author

Dugan, Hilary A., primary, Woolway, R. Iestyn, additional, Santoso, Arianto B., additional, Corman, Jessica R., additional, Jaimes, Aline, additional, Nodine, Emily R., additional, Patil, Vijay P., additional, Zwart, Jacob A., additional, Brentrup, Jennifer A., additional, Hetherington, Amy L., additional, Oliver, Samantha K., additional, Read, Jordan S., additional, Winters, Kirsten M., additional, Hanson, Paul C., additional, Read, Emily K., additional, Winslow, Luke A., additional, and Weathers, Kathleen C., additional

Published
2016
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22. Rapid and highly variable warming of lake surface waters around the globe

Author

O’Reilly, Catherine M., Sharma, Sapna, Gray, Derek K., Hampton, Stephanie E., Read, Jordan S., Rowley, Rex J., Schneider, Philipp, Lenters, John D., McIntyre, Peter B., Kraemer, Benjamin M., Weyhenmeyer, Gesa A., Straile, Dietmar, Dong, Bo, Adrian, Rita, Allan, Mathew G., Anneville, Orlane, Arvola, Lauri, Austin, Jay, Bailey, John L., Baron, Jill S., Brookes, Justin D., de Eyto, Elvira, Dokulil, Martin T., Hamilton, David P., Havens, Karl, Hetherington, Amy L., Higgins, Scott N., Hook, Simon, Izmest’eva, Lyubov R., Joehnk, Klaus D., Kangur, Kulli, Kasprzak, Peter, Kumagai, Michio, Kuusisto, Esko, Leshkevich, George, Livingstone, David M., MacIntyre, Sally, May, Linda, Melack, John M., Mueller-Navarra, Doerthe C., Naumenko, Mikhail, Noges, Peeter, Noges, Tiina, North, Ryan P., Plisnier, Pierre-Denis, Rigosi, Anna, Rimmer, Alon, Rogora, Michela, Rudstam, Lars G., Rusak, James A., Salmaso, Nico, Samal, Nihar R., Schindler, Daniel E., Schladow, S. Geoffrey, Schmid, Martin, Schmidt, Silke R., Silow, Eugene, Soylu, M. Evren, Teubner, Katrin, Verburg, Piet, Voutilainen, Ari, Watkinson, Andrew, Williamson, Craig E., Zhang, Guoqing, O’Reilly, Catherine M., Sharma, Sapna, Gray, Derek K., Hampton, Stephanie E., Read, Jordan S., Rowley, Rex J., Schneider, Philipp, Lenters, John D., McIntyre, Peter B., Kraemer, Benjamin M., Weyhenmeyer, Gesa A., Straile, Dietmar, Dong, Bo, Adrian, Rita, Allan, Mathew G., Anneville, Orlane, Arvola, Lauri, Austin, Jay, Bailey, John L., Baron, Jill S., Brookes, Justin D., de Eyto, Elvira, Dokulil, Martin T., Hamilton, David P., Havens, Karl, Hetherington, Amy L., Higgins, Scott N., Hook, Simon, Izmest’eva, Lyubov R., Joehnk, Klaus D., Kangur, Kulli, Kasprzak, Peter, Kumagai, Michio, Kuusisto, Esko, Leshkevich, George, Livingstone, David M., MacIntyre, Sally, May, Linda, Melack, John M., Mueller-Navarra, Doerthe C., Naumenko, Mikhail, Noges, Peeter, Noges, Tiina, North, Ryan P., Plisnier, Pierre-Denis, Rigosi, Anna, Rimmer, Alon, Rogora, Michela, Rudstam, Lars G., Rusak, James A., Salmaso, Nico, Samal, Nihar R., Schindler, Daniel E., Schladow, S. Geoffrey, Schmid, Martin, Schmidt, Silke R., Silow, Eugene, Soylu, M. Evren, Teubner, Katrin, Verburg, Piet, Voutilainen, Ari, Watkinson, Andrew, Williamson, Craig E., and Zhang, Guoqing

Abstract

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.

Published
2015
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23. Rapid and highly variable warming of lake surface waters around the globe

Author

O'Reilly, Catherine M., Sharma, Sapna, Gray, Derek K., Hampton, Stephanie E., Read, Jordan S., Rowley, Rex J., Schneider, Philipp, Lenters, John D., McIntyre, Peter B., Kraemer, Benjamin M., Weyhenmeyer, Gesa A., Straile, Dietmar, Dong, Bo, Adrian, Rita, Allan, Mathew G., Anneville, Orlane, Arvola, Lauri, Austin, Jay, Bailey, John L., Baron, Jill S., Brookes, Justin D., de Eyto, Elvira, Dokulil, Martin T., Hamilton, David P., Havens, Karl, Hetherington, Amy L., Higgins, Scott N., Hook, Simon, Izmest'eva, Lyubov R., Joehnk, Klaus D., Kangur, Kulli, Kasprzak, Peter, Kumagai, Michio, Kuusisto, Esko, Leshkevich, George, Livingstone, David M., MacIntyre, Sally, May, Linda, Melack, John M., Mueller-Navarra, Doerthe C., Naumenko, Mikhail, Noges, Peeter, Noges, Tiina, North, Ryan P., Plisnier, Pierre-Denis, Rigosi, Anna, Rimmer, Alon, Rogora, Michela, Rudstam, Lars G., Rusak, James A., Salmaso, Nico, Samal, Nihar R., Schindler, Daniel E., Schladow, S. Geoffrey, Schmid, Martin, Schmidt, Silke R., Silow, Eugene, Soylu, M. Evren, Teubner, Katrin, Verburg, Piet, Voutilainen, Ari, Watkinson, Andrew, Williamson, Craig E., Zhang, Guoqing, O'Reilly, Catherine M., Sharma, Sapna, Gray, Derek K., Hampton, Stephanie E., Read, Jordan S., Rowley, Rex J., Schneider, Philipp, Lenters, John D., McIntyre, Peter B., Kraemer, Benjamin M., Weyhenmeyer, Gesa A., Straile, Dietmar, Dong, Bo, Adrian, Rita, Allan, Mathew G., Anneville, Orlane, Arvola, Lauri, Austin, Jay, Bailey, John L., Baron, Jill S., Brookes, Justin D., de Eyto, Elvira, Dokulil, Martin T., Hamilton, David P., Havens, Karl, Hetherington, Amy L., Higgins, Scott N., Hook, Simon, Izmest'eva, Lyubov R., Joehnk, Klaus D., Kangur, Kulli, Kasprzak, Peter, Kumagai, Michio, Kuusisto, Esko, Leshkevich, George, Livingstone, David M., MacIntyre, Sally, May, Linda, Melack, John M., Mueller-Navarra, Doerthe C., Naumenko, Mikhail, Noges, Peeter, Noges, Tiina, North, Ryan P., Plisnier, Pierre-Denis, Rigosi, Anna, Rimmer, Alon, Rogora, Michela, Rudstam, Lars G., Rusak, James A., Salmaso, Nico, Samal, Nihar R., Schindler, Daniel E., Schladow, S. Geoffrey, Schmid, Martin, Schmidt, Silke R., Silow, Eugene, Soylu, M. Evren, Teubner, Katrin, Verburg, Piet, Voutilainen, Ari, Watkinson, Andrew, Williamson, Craig E., and Zhang, Guoqing

Abstract

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.

Published
2015

24. Rapid and highly variable warming of lake surface waters around the globe

Author

O'Reilly, Catherine M., primary, Sharma, Sapna, additional, Gray, Derek K., additional, Hampton, Stephanie E., additional, Read, Jordan S., additional, Rowley, Rex J., additional, Schneider, Philipp, additional, Lenters, John D., additional, McIntyre, Peter B., additional, Kraemer, Benjamin M., additional, Weyhenmeyer, Gesa A., additional, Straile, Dietmar, additional, Dong, Bo, additional, Adrian, Rita, additional, Allan, Mathew G., additional, Anneville, Orlane, additional, Arvola, Lauri, additional, Austin, Jay, additional, Bailey, John L., additional, Baron, Jill S., additional, Brookes, Justin D., additional, de Eyto, Elvira, additional, Dokulil, Martin T., additional, Hamilton, David P., additional, Havens, Karl, additional, Hetherington, Amy L., additional, Higgins, Scott N., additional, Hook, Simon, additional, Izmest'eva, Lyubov R., additional, Joehnk, Klaus D., additional, Kangur, Kulli, additional, Kasprzak, Peter, additional, Kumagai, Michio, additional, Kuusisto, Esko, additional, Leshkevich, George, additional, Livingstone, David M., additional, MacIntyre, Sally, additional, May, Linda, additional, Melack, John M., additional, Mueller‐Navarra, Doerthe C., additional, Naumenko, Mikhail, additional, Noges, Peeter, additional, Noges, Tiina, additional, North, Ryan P., additional, Plisnier, Pierre‐Denis, additional, Rigosi, Anna, additional, Rimmer, Alon, additional, Rogora, Michela, additional, Rudstam, Lars G., additional, Rusak, James A., additional, Salmaso, Nico, additional, Samal, Nihar R., additional, Schindler, Daniel E., additional, Schladow, S. Geoffrey, additional, Schmid, Martin, additional, Schmidt, Silke R., additional, Silow, Eugene, additional, Soylu, M. Evren, additional, Teubner, Katrin, additional, Verburg, Piet, additional, Voutilainen, Ari, additional, Watkinson, Andrew, additional, Williamson, Craig E., additional, and Zhang, Guoqing, additional

Published
2015
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