Derived variables in Env-DATA
Movebank and the Env-DATA system calculate several variables relevant to understanding animal movement, particularly aerial movements, that can be linked to your animal tracking data using the Track Annotation Service. These are derived using combinations of variables from existing environmental datasets and, in some cases, information from the track itself.
The Env-DATA System calculates attributes describing terrain using elevation estimates from digital elevation models (DEMs):
- slope: the change in height divided by the change in distance,
- rugosity: a measure of the "roughness" of the land surface, typically calculated as the actual area of the surface divided by the aerial (planimetric) area.
These are used to calculate the uplift variables below. Estimates of slope and rugosity provided by Env-DATA are calculated using the ETOPO1 Ice Surface Global Relief Model, the SRTM 90-m Digital Elevation Model, and the ASTER ASTGTM3 Global 30-m Digital Elevation Model. Rugosity is provided as the standard deviation of the height (in meters) over a given number of pixels of the original elevation model. Details about how the actual surface area is calculated are in Jenness 2004.
Wind conditions can greatly affect the movements of species that fly. For example, many bird species use use upward air movements as an efficient way to travel by soaring and gliding. In addition, it can be useful to know the speed and direction of wind in relation to a flying animal's movement. While regional- and global-scale weather reanalyses provide lots of information about wind conditions, these particular parameters are not included. Therefore Movebank has implemented existing methods and datasets for calculating these variables globally.
Keep in mind that the estimates provided by Env-DATA represent average conditions at the resolution of the original datasets. These estimates will therefore provide an indication of general conditions but are not intended to replicate the effects of small-scale wind turbulence and changes in topography, which can of course be very important to understanding animal movements. Despite this limitation, lower-resolution estimates like those Env-DATA provides have been successful in showing expected correlations between animal movements and wind conditions—see the references below for examples.
Orographic uplift happens when rising terrain forces air to move upwards to higher elevations. This is most famously the cause of the "rain shadows" found in mountaineous regions around the world. In addition, this uplift is a consistent source of upward-moving air that migrating birds such as raptors can use to travel long distances along mountain ridges.
The estimates of orographic uplift velocity provided by the Env-DATA System are calculated using estimates of the slope and aspect of the terrain (which can be calculated using digital elevation models as described below), and estimates of surface wind speed and direction (from global weather reanalyses). For details of the equations used, see Bohrer et al. (2012).
Movebank calculates orographic uplift using four different combinations of source data:
- the ASTER ASTGTM2 Global 30-m Digital Elevation Model and the ECMWF Global Atmospheric Reanalysis
- the ASTER ASTGTM2 Global 30-m Digital Elevation Model and the NCEP North American Regional Reanalysis
- the SRTM 90-m Digital Elevation Model and the ECMWF Global Atmospheric Reanalysis
- the SRTM 90-m Digital Elevation Model and the NCEP North American Regional Reanalysis
Which version to use will depend in part on the location of your dataset. The NCEP North American Regional Reanalysis (NARR) dataset provides higher-resolution weather data but covers only North America (from about 50–150°W and 12–60°N).
Thermals, or buoyant eddies of air, are formed by heating of the air by the sun near the earth's surface. Soaring birds that are slowly circling upward are using this thermal uplift (not to be confused with the use of this term in plate tectonics!) to travel.
The estimates of thermal uplift velocity provided by the Env-DATA System are calculated using estimates of temperature, relative humidity, surface pressure, boundary layer height, and instantaneous moisture and surface heat fluxes from the ECMWF Global Atmospheric Reanalysis. For details of the equations used, see Bohrer and others (2012).
Calculate other wind conditions
Some additional helpful conditions can be calculated yourself using annotated wind data from Env-DATA. Begin by annotating U and V wind (wind speed in the E-W and N-S directions, respectively) from the NARR or ECMWF weather models.
Wind speed and direction can be calculated from U and V wind as nicely illustrated in course exercises from San Francisco State University and George Mason University.
Wind support and cross wind are measures of the wind conditions in relation to the direction in which an animal is moving. Because they are dependent on the animal's direction of movement, and on how the researcher thinks it best to calculate direction of movement given the available data and question being addressed (for example, using the direction based on migration heading, heading calculated between consecutive locations, or instantaneous GPS heading) Env-DATA can't annotate it directly. See Figure 1 of Safi et al. (2013) for the equations, as well as some sample R script and a tutorial.
Bohrer G, Brandes D, Mandel JT, Bildstein KL, Miller TA, Lanzone M, Katzner T, Maisonneuve C, Tremblay JA. 2012. Estimating updraft velocity components over large spatial scales—contrasting migration strategies of golden eagles and turkey vultures. Ecol Letters. 15:96–103. https://doi.org/10.1111/j.1461-0248.2011.01713.x
Jenness JS. 2004. Calculating landscape surface area from digital elevation models. Wildlife Soc Bull. 32(3):829–839. https://www.fs.usda.gov/treesearch/pubs/20437
Katzner TE, Brandes D, Miller T, Lanzone M, Maisonneuve C, Tremblay JA, Mulvihill R, Merovich GT. 2012. Topography drives migratory flight altitude of golden eagles—implications for on-shore wind energy development. J Appl Ecol. 49:1178–1186. https://doi.org/10.1111/j.1365-2664.2012.02185.x
Mandel JT, Bildstein KL, Bohrer G, Winkler DW. 2008. The movement ecology of migration in turkey vultures. P Natl Acad Sci USA. 105(49):19102–19107. https://doi.org/10.1073/pnas.0801789105
Nourani E, Bohrer G, Bierregaard RO, Duriez O, Figuerola J, Gangoso L, Giokas S, Higuchi H, et al. 2021. The interplay of wind and uplift facilitates over-water flight in facultative soaring birds. Proc Roy Soc B. 288(1958):20211603. https://doi.org/10.1098/rspb.2021.1603
Safi K, Kranstauber B, Weinzierl R, Griffin L, Rees EC, Cabot D, Cruz S, Proaño C, Takekawa JY, Newman SH, et al. 2013. Flying with the wind: scale dependency of speed and direction measurements in modelling wind support in avian flight. Movement Ecol. 1:4. https://doi.org/10.1186/2051-3933-1-4
Shamoun-Baranes J, Leshem Y, Yom-Tov Y, Liechti O. 2003. Differential use of thermal convection by soaring birds over central Israel. Condor. 105(2):208–218. https://doi.org/10.1093/condor/105.2.20810.1093/condor/105.2.208
These derived variables may be used freely for research, conservation, and education purposes. In any publications or presentations that use the data, we ask that you cite Movebank and Env-DATA (citation below) as well as the original source of the data used to calculate the variable. We also request that you contact us at email@example.com to let us how you are using the data.
Dodge S, Bohrer G, Weinzierl R, Davidson SC, Kays R, Douglas D, Cruz S, Han J, Brandes D, Wilkelski M. 2013. The Environmental-Data Automated Track Annotation (Env-DATA) System: linking animal tracks with environmental data. Movement Ecol. 1:3. https://doi.org/10.1186/2051-3933-1-3