10.5061/DRYAD.0K6DJH9X5
Pinkert, Stefan
0000-0002-8348-2337
Philipp University of Marburg
Friess, Nicolas
Philipp University of Marburg
Zeuss, Dirk
0000-0001-6457-2866
Philipp University of Marburg
Gossner, Martin
0000-0003-1516-6364
Swiss Federal Institute for Forest, Snow and Landscape Research
Brandl, Roland
Philipp University of Marburg
Brunzel, Stefan
University of Applied Sciences Erfurt
Mobility costs and energy uptake mediate the effects of morphological
traits on species’ distribution and abundance
Dryad
dataset
2020
distribution–abundance relationship
Metabolic Ecology
Population density
propensity for nectar foraging
range size
resource availability
size–abundance relationship
thermal melanism hypothesis
wingbeat frequency
2021-05-22T00:00:00Z
2021-05-22T00:00:00Z
en
353858 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Individuals of large or dark-colored ectothermic species often have a
higher reproduction and activity than small or light-colored ones.
However, investments into body size or darker colors should negatively
affect the fitness of individuals as they increase their growth and
maintenance costs. Thus, it is unlikely that morphological traits directly
affect species’ distribution and abundance. Yet, this simplification is
frequently made in trait-based ecological analyses. Here, we integrated
the energy allocation strategies of species into an ecophysiological
framework to explore the mechanisms that link species’ morphological
traits and population dynamics. We hypothesized that the effects of
morphological traits on species’ distribution and abundance are not direct
but mediated by components of the energy budget and that species can
allocate more energy towards dispersal and reproduction if they compensate
their energetic costs by reducing mobility costs or increasing energy
uptake. To classify species’ energy allocation strategies, we used easily
measured proxies for the mobility costs and energy uptake of butterflies
that can be also applied to other taxa. We demonstrated that contrasting
effects of morphological traits on distribution and abundance of butterfly
species offset each other when species’ energy allocation strategies are
not taken into account. Larger and darker butterfly species had wider
distributions and were more abundant if they compensated the investment
into body size and color darkness (i.e. melanin) by reducing their
mobility costs or increasing energy uptake. Adults of darker species were
more mobile and foraged less compared to lighter colored ones, if an
investment into melanin was indirectly compensated via a size-dependent
reduction of mobility costs or increase of energy uptake. Our results
indicate that differences in the energy allocations strategies of species
account for a considerable part of the variation in species’ distribution
and abundance that is left unexplained by morphological traits alone and
that ignoring these differences can lead to false mechanistic conclusions.
Therefore, our findings highlight the potential of integrating proxies for
species’ energy allocation strategies into trait-based models not only for
understanding the physiological mechanisms underlying variation in
species’ distribution and abundance, but also for improving predictions of
the population dynamics of species.
Proxies for mobility costs and energy uptake As a proxy for the energetic
costs of mobility, we measured the wingbeat frequency of 316 individuals
of 102 butterfly species using high-speed camera footage taken during the
years 2013 to 2017 at different sites in Central Europe (a total of
793,896 frames or 2,646 s). Wingbeat frequencies of individuals in Hz were
calculated as wingbeat counts of each scene divided by its length (in s).
Subsequently, for each species, we averaged wingbeat frequencies across
individuals (median: 3 individuals, min: 1 individual, max: 9
individuals). To integrate across the peak and normal mobility costs of a
species, we averaged wingbeat frequencies during in situ and escape flight
(i.e. normal/peak flight, DATASET:
energy_budget_butterflies-intra_specific_data.csv). When only normal or
peak wingbeat frequencies were available for a species (i.e. for 1 and 43
species, respectively), we used values that were predicted based on the
relationship between these two variables (mean_flight). Furthermore, while
filming, we also recorded the ambient temperature to evaluate whether the
wingbeat frequency of species was temperature dependent. However, the
correlation between these two variables was not significant
(temperature.C). To obtain a proxy for the energy uptake of adult
butterflies, we counted how often individuals were observed collecting
nectar on flowers based on the results of a Google Images search (accessed
on May 15, 2017). To avoid potential bias of the access point, which could
result from Google’s search algorithms, we used the international homepage
(i.e. google.com) and searched for the scientific name of a butterfly
species. Of the first 100 hits, only images of clearly identifiable and
living adult individuals were used for further analyses (DATASET:
energy_budget_butterflies-links_google_image_search.xlsx). We assigned
each image a value of 1 or 0 depending on whether the individual was
observed foraging or not (i.e. whether the proboscis was inside the flower
or not), and a value of 0.5 if it sat on a flower but the proboscis was
not visible. Hence, to avoid potential observer biases (e.g. the
preference of the photographers for taking pictures of butterflies on
flowers), butterflies that clearly only sat on flowers were not considered
as foraging. Finally, we averaged these values for each species
(nectar_foraging_google). A rarefaction analysis showed that standard
deviations calculated for an increasing number of randomly sampled images
of species remained constant at 0.04 for sample sizes above 32 images.
This suggests that our results are not affected by differences among
locations and conditions of these observations and, although we used all
images sampled for further analyses, it indicates that a relatively small
number of images is already sufficient to provide a robust estimate for
the propensity of nectar foraging of a species. The reliability of our
approach was further confirmed by a positive relationship between
image-based estimates and expert classifications of the nectar-foraging
propensity of species (P < 0.001, rho = 0.31, n = 436; DATASET:
energy_budget_butterflies-expert_nectar_foraging_classification.csv).
Morphological traits Estimates of the color darkness, body size and wing
size of a species were calculated based on scanned dorsal drawings of
European butterfly species. In our study, we considered only data for
females. Specifically, we used the inverted average RGB (i.e. color
lightness) of pixels of the basal third of the wings and the body as an
estimate of the color darkness of a species (color_lightness_8bit,
DATASET: energy_budget_butterflies-species_level_data.csv). We considered
only the basal third of the wings because their distal part is less
relevant for thermoregulation in butterflies. As an estimate of the body
size of a species, we used the sum of volumes of each pixel row of images
of the body surface [π × (½ length of pixel row)2 × pixel edge length in
mm; body_volume.mm3]. In addition, we calculated the wing size of images
as the number of pixels of the four wings × pixel area in
cm2(wing_area.cm2). Distribution and abundance of species Regional
distributions (i.e. occupancy; OccuEU) were estimated based on gridded
distribution data of species across Europe [in a grid of cells with a size
of 50 km × 50 km, CGRS]. For each species, regional distributions were
calculated by dividing the number of grid cells in which it was present by
the total number of grid cells (1,720 grid cells). To calculate the local
distribution and abundance of species (i.e. local occupancy and population
density; OccuCH, AbundCH), we used survey data for butterfly species
assessed as part of the Biodiversity Monitoring Switzerland during the
years 2003–2016 (www.biodiversitymonitoring.ch, accessed on October 4,
2017). The monitoring scheme involved the counting of butterflies at 520
regularly placed sites (in a grid of cells with a size of 5 km × 5 km)
along transects of 2.5 km length. Transects were visited four to seven
times each year during comparable weather conditions. Species abundances
were calculated as the average number of individuals per occupied transect
and year. Note that this abundance measure is not correlated with the
number of generations per year (nbr_generations). Habitat availability
To account for the potential effect of habitat availability on the
distribution and abundance of species, we used gridded distribution
information on all 473 larval host plants of butterflies in Switzerland
for the years 2003–2016 from the Info Flora Database (accessed on October
18, 2017; a grid of cells with a size of 5 km × 5 km). We considered only
larval host plants of the butterfly species because adult butterflies are
mainly generalist nectarivores. Based on these data, we then calculated
the habitat availability for each butterfly species as the number of grid
cells occupied by host plants divided by the total number of grid cells
across Switzerland (i.e. occupancy of host plants;
OccuCH_hostplants_logit). Data transformation To normalize the data,
nectar-foraging propensity, habitat availability, local distribution and
regional distribution were logit transformed, and wingbeat frequencies,
body volume, color darkness, wing area, egg number and local abundance
were loge transformed.
For a more detailed description, including references and data sources,
please see the referenced article (Pinkert et al. 2020, ECY19-1196).