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  1. AU="French, Jon R"
  2. AU="Abdelkarime, Elsayed Mohamed"
  3. AU="Owens, C E"
  4. AU="Parvardeh, Siavash"
  5. AU=Jagadish Krishnappa
  6. AU="Reina, Miguel A"
  7. AU="Lim, Huey-Yee"
  8. AU="Carla M. Carvalho"
  9. AU="Aghaei Zarch, Seyed Mohsen"
  10. AU="Che, You"
  11. AU="Er, Chen-Chen"
  12. AU="Wang, Qiao-Ming"
  13. AU="Savino, Wilson" AU="Savino, Wilson"
  14. AU="Jin Han Nam"
  15. AU="Millburn, Michael V"
  16. AU="Ciebiera, Małgorzata"
  17. AU="Granich, R"
  18. AU="Koh, Lian Chye Winston"
  19. AU="Meredith M. White"
  20. AU="Aft, Rebecca"
  21. AU="Urban, Gerald A"
  22. AU="Jeong, Jae-Hyun"
  23. AU="Patsch, Wolfgang"
  24. AU="Garwood, Sarah K"
  25. AU="Pilon, Dominic"
  26. AU="Ignacio Cerro, C"
  27. AU=Jethani Bipin AU=Jethani Bipin

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  1. Artikel ; Online: Exploratory modelling of the impacts of sea-level rise on the Sundarbans mangrove forest, West Bengal, India.

    Samanta, Sourav / Hazra, Sugata / French, Jon R / Nicholls, Robert J / Mondal, Partho P

    The Science of the total environment

    2023  Band 903, Seite(n) 166624

    Abstract: In this paper we conduct exploratory simulations of the possible evolution of the Indian Sundarbans mangroves to 2100 under a range of future sea-level rise (SLR) scenarios, considering the effects of both inundation and shoreline erosion. The Sea Level ... ...

    Abstract In this paper we conduct exploratory simulations of the possible evolution of the Indian Sundarbans mangroves to 2100 under a range of future sea-level rise (SLR) scenarios, considering the effects of both inundation and shoreline erosion. The Sea Level Affecting Marshes Model (SLAMM) is used to simulate habitat transitions due to inundation and these outputs are combined with an empirical model of SLR-driven shoreline erosion. A set of plausible climate-induced SLR scenarios are considered, together with delta subsidence and constrained vertical sediment accretion. Significant mangrove decline is found in all cases: the greater the rise in sea level the greater the losses. By the end of the century, the Indian Sundarbans mangroves could lose between 42 % and 80 % of their current area if current management is continued. Managed realignment could offset these losses but at the expense of productive land and the migration of the human population.
    Sprache Englisch
    Erscheinungsdatum 2023-08-27
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2023.166624
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: Simulating seasonal to multi-decadal variation in lake thermal response to meteorological forcing using the UCLAKE 1-dimensional model code

    Morales-Marín, Luis A / French, Jon R / Burningham, Helene / Evans, Chris / Burden, Annette

    Limnologica. 2021 May, v. 88

    2021  

    Abstract: Lake temperature responses to climate forcing are of interest on account of the important linkages between water temperature and ecosystem processes. This paper describes a new 1-dimensional (1D) numerical model code and its application to investigations ...

    Abstract Lake temperature responses to climate forcing are of interest on account of the important linkages between water temperature and ecosystem processes. This paper describes a new 1-dimensional (1D) numerical model code and its application to investigations of multi-scale linkages between the vertical temperature structure and meteorological forcing. UCLAKE is implemented as highly portable open-source software, based on computationally efficient algorithms, and able to resolve sub-daily (e.g., hourly) dynamics while retaining the efficiency to simulate multi-decadal time scales.A UCLAKE model is calibrated and validated against thermistor profile time series for a small upland lake in North Wales, UK. Some of the challenges in 1D model calibration are explored and a sensitivity analysis reveals a dependence of optimal parameter set values on water column depth and time. An exploratory 52-year hindcast simulation demonstrates the computational efficiency of UCLAKE for multi-decadal studies of trends in lake temperature that vary with depth. A supplementary application of UCLAKE to Windermere, in the English Lake District, demonstrates its performance for larger and deeper lakes.
    Schlagwörter climate ; computer software ; ecosystems ; highlands ; lakes ; mathematical models ; thermistors ; time series analysis ; water temperature
    Sprache Englisch
    Erscheinungsverlauf 2021-05
    Erscheinungsort Elsevier GmbH
    Dokumenttyp Artikel
    Anmerkung NAL-AP-2-clean
    ZDB-ID 3380-7
    ISSN 0075-9511
    ISSN 0075-9511
    DOI 10.1016/j.limno.2021.125874
    Datenquelle NAL Katalog (AGRICOLA)

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    Verfügbar in ZB MED Bonn

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  3. Artikel: Assessment and Attribution of Mangrove Forest Changes in the Indian Sundarbans from 2000 to 2020

    Samanta, Sourav / Hazra, Sugata / Mondal, Partho P. / Chanda, Abhra / Giri, Sandip / French, Jon R. / Nicholls, Robert J.

    Remote Sensing. 2021 Dec. 07, v. 13, no. 24

    2021  

    Abstract: The Indian Sundarbans, together with Bangladesh, comprise the largest mangrove forest in the world. Reclamation of the mangroves in this region ceased in the 1930s. However, they are still subject to adverse environmental influences, such as sediment ... ...

    Abstract The Indian Sundarbans, together with Bangladesh, comprise the largest mangrove forest in the world. Reclamation of the mangroves in this region ceased in the 1930s. However, they are still subject to adverse environmental influences, such as sediment starvation due to migration of the main river channels in the Ganges–Brahmaputra delta over the last few centuries, cyclone landfall, wave action from the Bay of Bengal—changing hydrology due to upstream water diversion—and the pervasive effects of relative sea-level rise. This study builds on earlier work to assess changes from 2000 to 2020 in mangrove extent, genus composition, and mangrove ‘health’ indicators, using various vegetation indices derived from Landsat and MODIS satellite imagery by performing maximum likelihood supervised classification. We show that about 110 km² of mangroves disappeared within the reserve forest due to erosion, and 81 km² were gained within the inhabited part of Sundarbans Biosphere Reserve (SBR) through plantation and regeneration. The gains are all outside the contiguous mangroves. However, they partially compensate for the losses of the contiguous mangroves in terms of carbon. Genus composition, analyzed by amalgamating data from published literature and ground-truthing surveys, shows change towards more salt-tolerant genus accompanied by a reduction in the prevalence of freshwater-loving Heiritiera, Nypa, and Sonneratia assemblages. Health indicators, such as the enhanced vegetation index (EVI) and normalized differential vegetation index (NDVI), show a monotonic trend of deterioration over the last two decades, which is more pronounced in the sea-facing parts of the mangrove forests. An increase in salinity, a temperature rise, and rainfall reduction in the pre-monsoon and the post-monsoon periods appear to have led to such degradation. Collectively, these results show a decline in mangrove area and health, which poses an existential threat to the Indian Sundarbans in the long term, especially under scenarios of climate change and sea-level rise. Given its unique values, the policy process should acknowledge and address these threats.
    Schlagwörter Landsat ; Nypa ; Sonneratia ; carbon ; climate change ; conservation areas ; issues and policy ; mangrove forests ; rain ; remote sensing ; river deltas ; rivers ; salinity ; salt tolerance ; sea level ; sediments ; starvation ; statistical analysis ; temperature ; Bangladesh
    Sprache Englisch
    Erscheinungsverlauf 2021-1207
    Erscheinungsort Multidisciplinary Digital Publishing Institute
    Dokumenttyp Artikel
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs13244957
    Datenquelle NAL Katalog (AGRICOLA)

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  4. Artikel ; Online: Diel Surface Temperature Range Scales with Lake Size.

    Woolway, R Iestyn / Jones, Ian D / Maberly, Stephen C / French, Jon R / Livingstone, David M / Monteith, Donald T / Simpson, Gavin L / Thackeray, Stephen J / Andersen, Mikkel R / Battarbee, Richard W / DeGasperi, Curtis L / Evans, Christopher D / de Eyto, Elvira / Feuchtmayr, Heidrun / Hamilton, David P / Kernan, Martin / Krokowski, Jan / Rimmer, Alon / Rose, Kevin C /
    Rusak, James A / Ryves, David B / Scott, Daniel R / Shilland, Ewan M / Smyth, Robyn L / Staehr, Peter A / Thomas, Rhian / Waldron, Susan / Weyhenmeyer, Gesa A

    PloS one

    2016  Band 11, Heft 3, Seite(n) e0152466

    Abstract: Ecological and biogeochemical processes in lakes are strongly dependent upon water temperature. Long-term surface warming of many lakes is unequivocal, but little is known about the comparative magnitude of temperature variation at diel timescales, due ... ...

    Abstract Ecological and biogeochemical processes in lakes are strongly dependent upon water temperature. Long-term surface warming of many lakes is unequivocal, but little is known about the comparative magnitude of temperature variation at diel timescales, due to a lack of appropriately resolved data. Here we quantify the pattern and magnitude of diel temperature variability of surface waters using high-frequency data from 100 lakes. We show that the near-surface diel temperature range can be substantial in summer relative to long-term change and, for lakes smaller than 3 km2, increases sharply and predictably with decreasing lake area. Most small lakes included in this study experience average summer diel ranges in their near-surface temperatures of between 4 and 7°C. Large diel temperature fluctuations in the majority of lakes undoubtedly influence their structure, function and role in biogeochemical cycles, but the full implications remain largely unexplored.
    Mesh-Begriff(e) Lakes/chemistry ; Models, Statistical ; Models, Theoretical ; Temperature ; Time Factors ; Water/chemistry
    Chemische Substanzen Water (059QF0KO0R)
    Sprache Englisch
    Erscheinungsdatum 2016
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0152466
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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