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Fish habitats, fish diets, and bathymetry for 18 terminal lakes

Cite this dataset

Bess, Zachary et al. (2023). Fish habitats, fish diets, and bathymetry for 18 terminal lakes [Dataset]. Dryad. https://doi.org/10.5061/dryad.f7m0cfz0x

Abstract

Terminal lakes are lakes with no hydrologic surface outflows and with losses of water occurring only through surface evaporation and groundwater discharge. We quantified the extent of the littoral zones (areas where 1% or more of surface irradiation reaches the lake bottom) and open water zones (areas where less than 1% of surface irradiation reaches the lake bottom) in 18 terminal lakes. Additionally, we quantified habitat usage and diets of the fish species inhabiting these lakes. This dataset contains includes seven lakes from North America (Atitlan, Crater, Eagle, Mann, Pyramid, Summit, Walker), one from South America (Titicaca), five from Eurasia (Caspian, Issyk-Kul, Neusiedl, Qinghai, Van), and five from Africa (Abijatta, Manyara, Nakuru, Shala, Turkana).

README: Fish Habitats and Diets and Interpolated Bathymetry for 18 Terminal Lakes


Terminal lakes are lakes with no hydrologic surface outflows and with losses of water occurring only through surface evaporation and groundwater discharge. We quantified the extent of the littoral zones (areas where 1% or more of surface irradiation reaches the lake bottom) and open water zones (areas where less than 1% of surface irradiation reaches the lake bottom) in 18 terminal lakes. Additionally, we quantified habitat usage and diets of the fish species inhabiting these lakes. This dataset contains includes seven lakes in North America (Atitlan, Crater, Eagle, Mann, Pyramid, Summit, Walker), one in South America (Titicaca), five in Eurasia (Caspian, Issyk-Kul, Neusiedl, Qinghai, Van), and five in Africa (Abijatta, Manyara, Nakuru, Shala, Turkana).

Description of the data and file structure

All of the data pertaining to fish habitat and diet is contained in All_Lakes_Fish_Data.csv. This dataset contains a unique record for each fish species in each lake. This file contains fields for a) the continent on which the lake is located; b) the species' scientific name; c) the taxonomic family to which the species belongs; d) the taxonomic order to which the species belongs; e) the species' habitat; f) the species' diet; g) the status of the species in the lake as either an endemic taxa, a native taxa, or a non-native taxa; h) the surface area of the lake (in square kilometers); i) the depth of the lake (in meters); j) the 1% PAR depth (in meters); k) the percent of the lake's surface area overlying littoral habitat; l) the surface area of the lake's littoral zone (in square kilometers); m) the references consulted in quantifying the taxa's habitat use; and n) the references consulted in quantifying the taxa's diet.

There are GIS files for each lake's shoreline, open water zone, littoral zone, and interpolated bathymetry. The interpolated bathymetry is in raster format, while the open water zones, littoral zones, and shorelines are in shapefile formats. These are stored in compressed folders named in accordance with the following formula: Lakename_year_Datatype.zip

Examples:

  1. The shapefile for Pyramid Lake's 1970 shoreline is named Pyramid_1970_Shoreline.zip
  2. The raster file for Crater Lake's 2020 bathymetry is named Crater_2020_Bathymetry.zip
  3. The shapefile for Mann Lake's 2020 open water zone is named Mann_2020_Open_water_zone.zip
  4. The shapefile for Mann Lake's 2020 littoral zone is named Mann_2020_Littoral_zone.zip

The following offers specific details for each lake's GIS files:

Abijatta:

The 1% PAR depth is 1.62 meters (Belay & Wood 1984). The bathymetry was generated by digitizing the contours published in Legesse et al. 2004 and then interpolating into a raster using the Natural Neighbor function. Changes in size from 1980 to 1995 were calculated from water depth reported by Legesse 2004.

Atitlan:

Bathymetric contours provided by Domingo Francisco Ujpan. 1% PAR depth is 27.5 meters. This is calculated by 2.5 x Secchi depth. Secchi depth is 11 meters in the center of the lake (Rejmankova et al. 2011).

Caspian:

A 1% light level of 11.5 meters (calculated from a Secchi disk depth of 4.6 meters reported in Bagheri et al. 2012) was used to delineate the boundary between the open water and littoral zones. A Bathymetry DEM published by GEBCO was used to generate the bathymetry of the Caspian Sea.

Crater:

Bathymetry of Crater Lake available at: http://oe.oregonexplorer.info/craterlake/bathymetry.html#download
The 1% light depth is 86 meters, courtesy of data provided by Scott Girdner.

Eagle:

Secchi depth measurements were provided by Ryan McKim that were recorded in the southern basin in the 2000s. The average of these Secchi depths was 17.3 feet. Therefore, the 1% PAR depth was approximated as 17.3 feet x 2.5 = 43 feet = 13.1 meters. The bathymetry raster was generated by digitizing contours from Vail et al. 1974 and then interpolating a raster using the natural neighbor method.

Issyk-Kul:

Light attenuation is reported by Abakumov 2019: 0.045/meter. Bathymetry was provided in raster format by Damien Delvaux. The raster file integrates the bathymetry of the lake with the surrounding topography. Raster calculator was used to remove all elevations greater than the surface elevation (1607 meters).

Mann:

Bathymetry from 1959 (Atlas of Oregon Lakes) was used to generate contours of the lakes depth. Then, a raster was interpolated from the contours. This raster was then clipped to a polygon drawn of the 2020 shoreline from Landsat imagery. The 1% light depth is the 2007 Secchi depth (0.48m) x 2.5 = 1.2 meters (Atlas of Oregon Lakes).

Manyara:

A 1% PAR depth was calculated from the minimum and maximum Secchi values reported in Kiwhele et al. 2015. A minimum value of 2.5 cm was recorded in March, and a maximum value of 19.5 cm was recorded in May. Therefore, 1% PAR depth was 0.275 meters. The bathymetry raster was generated from interpolation of contours digitized from Deus et al. 2013.

Nakuru:

1% PAR depth is 0.91 meters (Vareschi 1982). Bathymetry was generated by digitizing contours shown in Vareschi 1982.

Neusiedl:

Somogyi et al. 2010 reports a Secchi depth maximum of 30 cm. Therefore, 1% PAR depth is 0.3 x 2.5 = 0.75 meters. The extent of the reed zone was digitized from georeferenced images from Krachler et al. 2009. The reed zone was considered inherently littoral. A bathymetry raster was generated from sonar measurements provided by Tamas Kramer.

Pyramid:

The 1% PAR depth used to distinguish littoral and open water zones is 11 meters according to unpublished data from 1976 & 1977 collected by the Pyramid Lake Paiute Tribe. Contours were digitized from Harris 1970.

Qinghai:

Bathymetric contours from 2004 were provided as a shapefile by Quangyin Hu. A raster DEM was generated from these contours. The boundary between pelagic and open water zones were determined from Secchi disk readings reported in Ao et al. 2014:
June Secchi = 3.2 meters
August Secchi = 2.94
Mean = 3.07 meters
3.07 X 2.5 = 7.7 1% light depth

Shala:

Bathymetry raster was generated by digitizing the contours presented in Baumann et al. 1975. The 1% PAR depth is 4.93 meters (Belay & Wood 1984).

Summit:

A Secchi depth of 2.4 meters is reported in Barnes et al. 2015. This was used to calculate a 1% PAR depth of 2.4*2.5 = 6 meters. Bathymetric contours reported in Barnes et al. 2015 were digitized and interpolation was used to generate a bathymetric raster.

Titicaca:

In the northern basin, the Secchi depths are 11.8, 11.9, 13.2, 12.4, and 13.9 meters. The average of this multiplied by 2.5 is 32 meters which is an approximation of the 1% PAR depth for the northern basin. In the southern basin, the Secchi depths are 4.7, 4.5, 5.6, 5.4, and 3.2 meters. The mean of this multiplied by 2.5 is 12 meters which is an approximation of the 1% PAR depth for the southern basin (Iltis et al. 1992). The bathymetry was provided as a raster by Sheri Briggs from University of Nebraska, Lincoln.

Turkana:

A mean 1% PAR depth of 6 meters was used to delineate littoral and open water zones (Kallqvist et al. 1988). Bathymetry raster was generated by contours reported in Kallqvist et al. 1988.

Van:

A 1% PAR depth was calculated from Secchi depth values reported in Ozguven & Yetis 2020 which reported a dry season Secchi of 2.54 meters and a wet season Secchi of 3.21 meters. Therefore, the mean Secchi depth is 2.875, and 1% PAR depth is 7.18 meters. Contours were digitized from Huguet et al. 2012. These contours were then interpolated to create a raster.

Walker:

LANDSAT 5 images from 1984 and 2014 were used to generate polygons of the shorelines in 1984 and 2014. A bathymetry DEM was used from Smith & Lopes 2007. The DEM from Smith & Lopes 2007 was clipped to the polygons generated of the lake shoreline for 1984 and 2014. A 1% PAR depth of 17 meters was calculated from the mean of the 1% PAR values reported in Figure A.4.8 in Collopy & Thomas 2010.

Literature Cited:

  1. Abakumov AI, Pak SY, Morozov MA, & Tynybekov AB. 2019. Model estimation of the phytoplankton biomass of Lake Issyk-Kul using remote sensing data. Inland Water Biology 12: S111S118.
  2. Ao H, Wu C, Xiong X, Jing L, Huang X, Zhang K, & Liu J. 2014. Water and sediment quality in Qinghai Lake, China: a revisit after half a century. Environmental Monitoring & Assessment 186: 21212133. DOI:10.1007/s10661-013-3522-7
  3. Atlas of Oregon Lakes. https://oregonlakesatlas.org/map
  4. Bagheri S, Mansor M, Turkoglu M, Makaremi M, Omar WMW, Negarestan H. 2012. Phytoplankton Species Composition and Abundance in the Southwestern Caspian Sea. Ekoloji 21(83): 32-43. DOI: 10.5053/ekoloji.2012.834
  5. Barnes J, Chandra S, & Atwell L. 2015. Summit Lake food web energetics with a comparison of Lahontan cutthroat trout characteristics across lake ecosystems. Submitted to Natural Resources Department, Summit Lake Paiute Tribe. 66 pgs.
  6. Baumann A, Forstner U, & Rodhe R. 1975. Lake Shala: Water chemistry, mineralogy and geochemistry of sediments in an Ethiopian Rift lake. Geologische Rundschau 64: 593-609. DOI: 10.1007/BF01820685
  7. Belay A & Wood RB. 1984. Primary productivity of five Ethiopian Rift Valley lakes. Internationale Vereinigung fr theoretische und angewandte Limnologie: Verhandlungen 22(2): 1187-1192. DOI: 10.1080/03680770.1983.11897464
  8. Collopy ME & Thomas JM. 2010. Restoration of a desert lake in an agriculturally dominated watershed: The Walker Lake Basin. Bureau of Reclamation Report. 1273 pgs.
  9. Deus D, Gloaguen R, & Krause. 2013. Water balance modeling in a semi-arid environment with limited in situ data using remote sensing in Lake Manyara, East African Rift, Tanzania. Remote Sensing 5: 1651-1680. DOI: 10.3390/rs5041651
  10. General Bathymetric Chart of the Oceans (GEBCO): The GEBCO_08 Grid. https://www.gebco.net/data_and_products/gridded_bathymetry_data/version_20100927/
  11. Harris EE. 1970. Reconnaissance bathymetry of Pyramid Lake, Washoe County, Nevada. USGS Hydrologic Atlas 379.
  12. Huguet C, Fietz S, Moraleda N, Litt T, Heumann G, Stockhecke M, Anselmetti FS, Sturm M.
  13. A seasonal cycle of terrestrial inputs in Lake Van, Turkey. Environmental Science & Pollution Research 19: 3628-3625.
  14. Iltis A, Carmouze J, & Lemoalle J. 1992. Physico-chemical properties of the water. In Lake Titicaca: A Synthesis of Limnological Knowledge. Eds: Dejoux C & Iltis A. Kluwer Academic Publishers. 573 pgs.
  15. Kallqvist T, Lien L, & Liti D. 1988. Lake Turkana: Limnological Study 1985-1988. Norwegian Institute for Water Research. 98 pgs.
  16. Kihwele ES, Lugomela C, Howell KM, Nonga HE. 2015. Spatial and temporal variations in the abundance and diversity of phytoplankton in Lake Manyara, Tanzania. International Journal of Innovative Studies in Aquatic Biology and Fisheries 1(1): 1-14.
  17. Krachler RF, Krachler R, Stojanovic A, Wielander B, & Herzig A. 2009. Effects of pH on aquatic biodegradation processes. Biogeosciences Discuss 6: 491514.
  18. Legesse D, Vallet-Coulomb C, & Gasse F. 2004. Analysis of the hydrological response of a tropical terminal lake, Lake Abiyata (Main Ethiopian Rift Valley) to changes in climate and human activities. Hydrological Processes 18: 487-504.
  19. Lopes TJ & Smith JL. 2007. Bathymetry of Walker Lake, West-Central Nevada. U.S. Geological Survey Scientific Investigations Report 2007-5012. 26 pgs.
  20. Ozguven A & Yetis AD. 2020. Assessment of spatiotemporal water quality variations, impact analysis and trophic status of Big Soda Lake Van, Turkey. Water, Air, & Soil Pollution 231: 260.
  21. Raymon Vail and Associates. 1974. Eagle Lake Basin Planning Study. Volume 5: Eagle Lake Limnological Analyses. 45 pgs.
  22. Rejmankova E, Komarek J, Dix M, Komarkova J, & Giron N. 2014. Cyanobacterial blooms in Lake Atitlan, Guatemala. Limnologica 41(4): 296-302.
  23. Somogyi B, Felfoldi T, Dinka M, & Voros L. 2010. Periodic picophytoplankton predominance in a large, shallow alkaline lake (Lake Ferto, Neusiedlersee). International Journal of Limnology 46: 9-19.
  24. Vareschi E. 1982. The ecology of Lake Nakuru (Kenya): III. Abiotic factors and primary production. Oecologia 55(1): 81-101. DOI: 10.1007/BF00386722.

Methods

Measurements of the surface areas of the littoral and open water zones were performed using ArcGIS Pro Version 2.9. First, we generated year-specific digital elevation models (DEMs) of the lake’s bathymetry by a) using existing bathymetry raster data or b) by digitizing published depth contours of the lake’s bathymetry and interpolating a bathymetry raster using a natural neighbor interpolation. For several lakes that showed significant changes in lake level and where data regarding lake level change were available, we were able to produce a second year closer to the present by using the Raster Calculator function in ArcGIS Pro and then clipping the bathymetry raster to the lower lake level. This was possible for 5 of the 18 lakes (Mann Lake, Eagle Lake, Lake Abijatta, Walker Lake, and Lake Turkana), allowing us to map changes in the littoral zone size between the two years. For the lakes containing two years of data, we used only the most recent year in all subsequent analyses. We defined the portions of the littoral zone of the lake as the portions where the intensity of photosynthetically active radiation (PAR) reaching the lake bottom is 1% or greater relative to the intensity at the surface. For lakes where 1% PAR depth was not published, we calculated 1% PAR depth from published light profiles using the Lambert-Beer Law: 0.01 = e-u*z where µ is the light attenuation coefficient (meters-1) and z is 1% PAR depth (meters). For lakes where neither 1% PAR depth nor light profiles were published, we approximated the 1% PAR depth by multiplying the Secchi depth of the lake by a coefficient of 2.5. We sought the most recently collected Secchi depth to make these calculations. We then used the Raster Calculator function in ArcGIS PRO 2.9 to determine the portions of the lake where depth was less than or greater than the 1% PAR depth to map the open water and littoral zones, respectively.

Fish species inventories and information regarding each species’ habitat and diet was compiled from 1) published peer-reviewed primary literature, 2) non-peer-reviewed literature (books, reports by government agencies or private firms), 3) online databases (i.e., FishBase (https://www.fishbase.de/home.htm), California Fish Website (www.calfish.ucdavis.edu)), and/or 4) experts studying the ecology of the species or lake ecosystem. We employed a conservative view regarding species taxonomy (i.e., ‘lumping’ rather than ‘splitting’). We classified species’ habitats with respect to three categories: 1) littoral zone (occurring in parts of the lake where 1% or more of the surface radiation reaches the lake bottom), 2) open water zone (occurring in parts of the lake where less than 1% of the surface radiation reaches the lake bottom), and 3) littoral & open water zone (occurring in both lake zones). These habitat classifications were based on adult habitat use only, and habitat use during larval and juvenile stages was not considered. We classified diets with respect to seven categories: 1) plankton only, 2) periphyton only, 3) periphyton and macroinvertebrates, 4) periphyton, macroinvertebrates, and plankton, 5) periphyton, macroinvertebrates, and fish, 6) fish OR fish and plankton, and 7) fish, plankton, periphyton, and macroinvertebrates.

Usage notes

The fish habitat and diet data (All_Lakes_Fish_Data.csv) can be opened with any program capable of reading .csv files (e.g. Microsoft Excel). The GIS files can opened with any software capable of opening GIS files (e.g. ArcGIS Pro, QGIS, Google Earth).

Funding