Luo et al
Global warming impacts bat prey detection
Global warming alters sound transmission: differential impacts on the prey
detection ability of echolocating bats
Jinhong Luo, Klemen Koselj, Sándor Zsebők, Björn M. Siemers and Holger R. Goerlitz
Supporting Methods
Data-distribution-model and average-data-model: We obtained more than 100,000
single weather data points describing the distribution of weather conditions in temperate
and tropical climate zones. Because prey detection volume changes in a non-linear
fashion with changing weather conditions, it can only be accurately computed from their
entire distribution and not from mean values. These detailed data, however, will not
always be available and require computationally more costly models than when using
average weather data. We therefore compared our model, which used the full distribution
of weather data, to a model which only used the mean temperature and mean relative
humidity of our temperate and tropical data set. The difference between the outputs of
both models is small to negligible (Fig. S2). This is due to the comparatively small shifts
in temperature (+2 and +4°C) that do not lead to extensive non-linear changes in
atmospheric attenuation. In the tropical biome, this is additionally due to the little
variation of temperature around the mean value. Therefore, the average-weather model is,
despite the non-linear relationship between temperature and atmospheric attenuation, an
easy model to predict the influence of global warming on echolocating animals in the
absence of detailed weather data with sufficient accuracy.
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Luo et al
Global warming impacts bat prey detection
Supporting Figures
Figure S1. Molar concentration of water vapour as a function of ambient
temperature and humidity.
The estimated atmospheric attenuation coefficient α has an accuracy of ±10% for molar
concentrations of water vapour in the range between 0.05% and 5% [46]. This accuracy is
achieved for almost the entire range of climatic conditions modelled in our study. Values
outside this range, indicated by the white lines, occur only for very high temperatures and
relative humidities (top right corner) and very low relative humidities (bottom area).
Please also note that the error in α is affecting the absolute prey detection volume.
However, we studied the relative change in prey detection volume, based on estimated
prey detection volumes before and after global warming of +2 and +4°C. Due to the small
change in temperature, the error in the estimated prey detection volumes will be similar.
Therefore, the error of the change in prey detection volume will be much smaller because
the similar errors of the prey detection volume almost cancel each other out.
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Luo et al
Global warming impacts bat prey detection
Figure S2. Comparison between data-distribution-model and average-weather
model.
Shown is the mean change of detection volume caused by global warming of +2 °C (red)
and +4 °C (blue), for two different MTLs and temperate (a, b) and tropical (b, d) climate
zones and for perch-hunting bats (a, b) and aerial-hawking bats (c, d).
We used the data-distribution-model (darker colours) to compute the results of the study.
It included all temperature and humidity measurements obtained for each climate zone.
The output of this model is the average change in detection volume after increasing every
temperature measurement by +2 or +4°C.
The average-weather model (lighter colours), which can be used if detailed data are
unavailable, uses only the average temperature and relative humidity of a biome and
outputs the change in detection volume after increasing the average temperature by +2
and +4°C.
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Luo et al
Global warming impacts bat prey detection
Figure S3. Average change of detection volume for different temperatures (columns)
and relative humidities (rows).
Calculated for a perching bat, a temperature increase of +2 (blue) and +4°C (red) and
MTL = -60 dB.
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Luo et al
Global warming impacts bat prey detection
Figure S4. Effect of global warming on bat communities in different climatic zones.
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Luo et al
Global warming impacts bat prey detection
a, b) Crossover frequency f0 (kHz; see inset) as a function of ambient temperature and
relative humidity. Global warming will increase detection volume for call frequencies <f0
and decrease detection volume for call frequencies >f0. Note that f0 is independent of
MTL. In the grey area next to the axes origin, no f0 exists between 10-150 kHz and
detection volume will decrease for all these sound frequencies; in the red area, a second f0
exists between 10-14 kHz (cf. Fig. S3).
c, d) Magnitude of detection volume change (percentage points) between the most
benefiting and the most disadvantaged bat species for call frequencies from 10 to
150 kHz (see inset).
e, f) Absolute value of the most extreme slope (percentage points per 10 kHz) within the
range of 10-150 kHz call frequency (see inset).
g, h) Mean of the absolute slopes (percentage points per 10 kHz) across the full range of
10-150 kHz call frequency (see inset).
All values calculated for +2 (left) and +4 °C (right) temperature rise and for a perching
bat and MTL = -60 dB. The present day weather distributions of temperate (GER),
tropical (MAL) and an arid desert biome (NEG: Negev, Israel; May-Sept.), are shown as
grey scaling enclosing 80, 60, 40 and 20% of all weather measurements, respectively.
References
46.
International Organization for Standardization. 1993 Acoustics - Attenuation of
sound during propagation outdoors, ISO 9613. Genève, International Organizsation for
Standardization
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