Damage to crops is a major cause of human-elephant conflict (HEC) in
elephant range states. Elephant crop raiding drives farmers'
resentment against elephants and reduces local community support for
wildlife conservation. While elephant crop raiding ecology is well
studied, further investigations on HEC mitigation strategies are still
needed. Thus, there is a need to focus on less investigated areas, such as
the physiological drivers of elephant crop-raiding behavior, using
multidisciplinary sciences. Two physiological proxies, gastrointestinal
parasite infestations (GPI) and fecal glucocorticoid metabolite (fGCM)
concentrations, common in animal ecophysiology, were used to help
understand differences or motivations in the preferences of crops by
elephant raiders. The results show, for the first time, that forest
elephants may increase the frequency of crop raiding according to GPI,
indicating a self-medication behavior. Increases in parasitism prevalence
(PP) and parasitism intensity (PI) in sampled boluses led to 28% and 0.16%
more intakes of all crops, respectively. Parasitism prevalence (PP)
increases in elephant boluses also led to 16% and 25% more bananas and
papaya intakes, respectively, while PI increases in boluses led to 0.1%
more intakes of both bananas and papaya plants. No such predictions were
found for other crops (cassava and palm plant), nor for natural food
species. Furthermore, fGCM concentrations were not related to elephant
crop raiding. Results highlight a trade-off between the benefit of
elephants raiding crops and the danger of encountering farmers by adopting
nocturnal crop-raiding behaviours. # Data from: Are crop fields pharmacies for megaherbivores? From
ecophysiological studies of elephant (*Loxodonta cycotis*) crop raiders in
Gabon Dataset DOI: [10.5061/dryad.7wm37pw1p](10.5061/dryad.7wm37pw1p) ##
Description of the data and file structure Forest elephant crop raiding
according to FGCM and GIP ### Dataset Overview This data includes
frequencies of forest elephant crop raiding events as well as fecal
glucocorticoid metabolite concentrations and gastrointestinal parasitism
presence. The data is composed by 90 rows corresponding to individual
elephants sampled. Columns represents variables with Fecal Glucocorticoid
concentration, parasite prevalence (PP), and parasitism intensity (PI)
being the response variables and the others being the explanatory
variables. ### Funding These data were collected through a research work
funded by COLAS-Gabon with the collaboration of IRAF-CENAREST (Gabon),
Nature+ asbl NGO (Belgium), and Gembloux ABT, University of Liège
(Belgium). COLAS-Gabon, IRAF-CENAREST, and Nature+ provided logistic and
financial support for the field work to SN. Gembloux Agro-Bio Tech,
University of Liège (Belgium), and RESSAC (CIFOR-ICRAF) provided financial
support for data analyses, manuscript writing, and publishing. ### Ethics
Approval The National Center for Scientific Research and Technology
(Centre National de la Recherche Scientifique et Technologique, CENAREST)
and the National Agency of National Parks (Agence National des Parcs
Nationaux ANPN) in Gabon provided permissions to conduct this research.
### Files and variables #### File:
Forest_elephant_crop_raiding_according_to_FGCM_and_GIP.csv
**Description:** fecal glucocorticoid metabolite concentrations (fGCM), as
well as parasite prevalence (PP) and parasite intensity (PI), are the
response variables. The others parameters are explanatory variables. #####
Variables * Seasons: Our observational experimental blocks were seasons
with five modalities (S1=Long dry season; S2 = short wet season; S3 =
short dry season; S4 = long wet season; S5= second long dry season) *
S5: second long dry season * S4: long wet season * S3:short dry season *
S2:short wet season * S1: Long dry season * Elephant.Groups: * Crop:
represents the presence (1) and absence (0) of farmed plants eaten by
elephants. * Crops: represent all farmed plants eaten by elephants. *
Food.sp: represents all plant species eaten by elephants * Nat.food: is a
numerical form of non-croped plants eaten by elephantsNat.food.: is the
numerical form of non-croped plants eaten by elephants *
Natural.food: represents all non-crop plants eaten by elephants * Banana:
is a crop species eaten by elephants * Banana.: is the numerical form of
the banana crop species eaten by elephants * Cassava: is a crop species
eaten by elephants * Cassava.: is the numerical form of the cassava crop
species eaten by elephants * Papaya: is a crop species eaten by elephants
* Papaya.: is the numerical form of the papaya crop species eaten by
elephants * Palm: is a crop species eaten by elephants * Palm.: is the
numerical form of the palm crop species eaten by elephants * Costus: is a
natural species eaten by elephants * Cost.: is a natural species eaten by
elephants (numeric) * Bamboo: is a natural species eaten by elephants *
Bamboo.: is a natural species eaten by elephants (numeric) * Fern: is a
natural species eaten by elephants * Fern.: is a natural species eaten by
elephants (numeric) * Ficus: is a natural species eaten by elephants *
Ficus.: is a natural species eaten by elephants (numeric) * Parasitism:
indicates the presence (1) or absence (0) of parasite eggs in elephant
dung * PP: is parasitism prevalence * FGM.conc: fecal glucocorticoid
metabolite concentrations * FGMcx10: fecal glucocorticoid metabolite
concentrations times 10 for graphical depictions * FGM.conc/SEM: fecal
glucocorticoid metabolite concentrations for graphical depiction *
EPGD.c: egg per gram of boluses * PI:Parasitism intensity * EPGDx100: egg
per gram of boluses times 100 (for graphical representations) *
EPG.cat: egg per gram of boluses (categorised) * OPG.cat.num: egg per
gram of boluses (numeric) * PP.ord: Parasitism prevalence (ordinal for
analyses) * OPG.cat.L.H.num: egg per gram of boluses (categorised for
analyses) ## Code/software We performed descriptive and inferential
statistical calculations using Excel software and R version 4.0.4 (R
Development Core Team 2025). We performed descriptive statistics,
including percentage calculations, charts’ design, and principal component
analyses (PCA) showing correlations between variables. In inferential
statistics, the *Shapiro* test was used to assess the normality of
response variables, while the *X^2^* dependency test was used to assess
whether variables were dependent. As most of our data were counts, we used
nonparametric ANOVA tests (Kruskal and Wilcoxon) to calculate PP, PI, and
fGCM differences according to plant intakes. We also used the *lme4*
package to perform generalized linear mixed models (GLMMs) analyses to
predict the effects of PP, PI, and fGCM on elephant plant species intakes
over time.