DOI: 10.5061/dryad.ffbg79d3t
title: Predation risk in a migratory butterfly increases southward along a latitudinal gradient

description: Migratory insects provide a valuable ecosystem service by transporting
 large amounts of organic matter across regions where they become
 temporarily abundant prey. In species performing multigenerational
 migration, such as the painted lady butterfly Vanessa cardui, successive
 generations face a wide variety of predator communities and may be subject
 to different predation risks. Here, we analyze the pattern of wing damage
 of over 2,000 butterflies to investigate, for the first time, the risk of
 predation of adult painted ladies across a latitudinal range of ca. 3,500
 km extending from the northern Mediterranean through the Maghreb to
 sub-Saharan West Africa. Large number of butterflies showed substantial
 wing damage attributable to failed attacks, with birds, mantids and
 lizards being the most likely predators. The risk of attack increased
 towards the equator, even after controlling for wing wear. In addition,
 there was a strong effect of butterfly size on predation risk, with larger
 butterflies facing a higher risk compared to their smaller counterparts,
 and clear evidence that females suffered more attacks than males. Although
 size is a major factor, latitude was a stronger predictor of predation
 risk across the migratory system, as evidenced by greater wing damage in
 butterflies at lower latitudes, even though their size notably decreased.
 These results raise an interesting evolutionary conflict, with a trade-off
 between size and predation risk, as larger butterflies are likely to be
 more fecund and efficient in migratory flight but, at the same time, more
 vulnerable to predation.
description: <strong>Butterfly collection and sampling
 regions</strong> Between 2015 and 2023, a total
 of 2,276 painted ladies were collected in three regions (Fig. 1,
 Supporting information). Sampling was designed to obtain representative
 collections of the study regions, while avoiding spatial and temporal
 biases: (1) northern Mediterranean, 891 butterflies from 102 sites in
 northeast Spain (38-43ºN, 0-4ºE); (2) Maghreb, 1,247 butterflies from 141
 sites in Morocco (28-35ºN, 2-11ºW); and (3) sub-Saharan West Africa, 138
 butterflies from 22 sites in Senegal (11-15ºN, 11-17ºW). In the northern
 Mediterranean, butterflies were collected each month from March to
 October; in Morocco, they were collected in autumn (October-November),
 spring (April), and winter (January-February); and in Senegal, in
 October. Butterflies were sexed, and their wings were
 removed and stored in glassine envelopes for further measurements. To
 account for the potential influence of age on wing damage, wing wear
 (i.e., a surrogate of age) was assessed on a scale from 1 to 5, as
 described in Stefanescu et al. (2016). Wing size was measured with a
 calliper (to the nearest tenth of millimeter), from the apex to the
 insertion on the thorax for either forewing.
 <strong>Wing damage measurements and predation
 ris</strong>k Wing damage was measured for each
 of the four wings and quantified as the percentage of wing-area loss using
 digital images and the open-source platform for biological-image analysis
 Fiji (Schindelin et al. 2012; Supporting information).
 As wing damage can result from both wear and tear associated to
 routine behavioral activities, or be the consequence of unsuccessful
 predator attacks (Korkmaz et al. 2022), we examined the distribution of
 wing area loss through histograms (Supporting information). Taking an
 average of area loss across the four wings, more than half (60.1±10.3%) of
 the sample showed no loss or a loss of less than 1% on their wings, while
 the remaining butterflies showed a gradual decrease from 1-2% wing area
 loss (10.4 ± 1% of individuals) to 40-50% loss in rare and extreme cases
 (2.2 ± 2.1% of individuals). This pattern suggests that wing damage in the
 first interval is simply explained by wear and tear from normal activities
 as the butterfly ages, whereas values below 99% of the wing area may often
 be related to unsuccessful predator attacks. Therefore, predation risk was
 treated as a binary variable, with individuals classified as non-attacked
 (i.e., 0-1% wing area loss, calculated as the average of the four wings)
 or attacked (&gt;1% wing area loss). Although this method is likely to
 overestimate the frequency of attacks, the error is distributed
 homogeneously across the entire sample and does not affect the hypotheses
 being tested. It is important to recognize that the
 actual predation rate cannot be directly inferred from wing loss data
 alone (e.g., Bengtson 1981, Burger and Gochfeld 2001). Despite this, when
 accounting for the degree of wing wear, the incidence of wing loss is
 likely correlated with the frequency of predator attacks, thereby serving
 as a proxy for assessing predation risk.
description: # Predation risk in a migratory butterfly increases southward along a
 latitudinal gradient
 [https://doi.org/10.5061/dryad.ffbg79d3t](https://doi.org/10.5061/dryad.ffbg79d3t) ## Description of the data and file structure ### Files and variables #### File: cardui\_predation\_dryad.csv **Description:**  ##### Variables * code: Unique identifier of the sample. * region: Geographic region. Levels: Catalonia (Spain); Mallorca (Spain); Menorca (Spain); Morocco; Senegal. * region2: Spanish locations are grouped. Levels: Mediterranean; Morocco; Senegal. * date: Calendar date when the sample was collected. * year: Year when the sample was collected. * month: Month when the sample was collected. * period: Season of sampling. Levels: spring; autumn; winter. * longitude: Longitude coordinates in decimals format. * latitude: Latitude coordinates in decimals format. * sex: levels: m (male); f (female). * wing wear: a surrogate of age which was assessed on a scale from 1 to 5, as described in Stefanescu et al. (2016). * wing size: Body size, which was measured with a calliper (to the nearest tenth of millimeter), from the apex to the insertion on the thorax for either forewing. * upwr: Percentage (%) of wing remaining for upper right wing. * hnwr: Percentage (%) of wing remaining for hind right wing. * upwl: Percentage (%) of wing remaining for upper left wing. * hnwl: Percentage (%) of wing remaining for hind left wing. * predation: Mean percentage of wing loss in per unit terms. * pred_binom: Predation treated as a binary variable, with individuals classified as non-attacked (i.e., 0-1% wing area loss, calculated as the average of the four wings) or attacked (&gt;1% wing area loss) * pred_up: Mean percentage of wing loss for upper wings in per unit terms. * pred_hn: Mean percentage of wing loss for hind wings in per unit terms. * pred_upwr: Percentage of wing loss for upper right wing. * pred_hnwr: Percentage of wing loss for hind right wing. * pred_upwl: Percentage of wing loss for upper left wing. * pred_hnwl: Percentage of wing loss for hind left wing. **Additional information** Cells with the value "NA" indicate missing data. The variables with missing values and their respective percentages are as follows: * **sex**: 0.09% * **wing wear**: 0.79% * **wing size**: 2.89% * **upwr**: 0.83% * **hnwr**: 2.10% * **upwl**: 16.02% * **hnwl**: 16.73% * **pred_upwr**: 0.83% * **pred_hnwr**: 2.10% * **pred_upwl**: 16.02% * **pred_hnwl**: 16.73%