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What acceleration data from wildlife collars and animal body mass tell us about seed dispersal

What acceleration data from wildlife collars and animal body mass tell us about seed dispersal Background The seeds of many plant species can be dispersed over long distances in animal fur (epizoochory). Quantifying epizoochory in the wild is, however, challenging, since it is difficult to measure the retention times of seeds in fur. These retention times depend on the acceleration that seeds experience and that can detach seeds from fur. Wildlife collars containing accelerometers may thus provide crucial information on epizoochorous seed dispersal. However, this is only the case if acceleration of the animal’s neck (where collars are attached) is informative of accel- eration of the animal’s main body (where most seeds are transported). Methods We used accelerometers to simultaneously measure acceleration at the neck, breast and the upper hind leg of 40 individuals of eight mammal species spanning a large range of body masses (26–867 kg). We then quantified maximum acceleration as the 95%-quantile of the resultant acceleration (of all measured values in data intervals of 5 s). Results Maximum acceleration was comparable between the neck and breast but substantially higher at the hind leg. Maximum acceleration measured by neck collars and body mass jointly explained 81% of the variance in maxi- mum acceleration of the breast and 62% of the variance in maximum acceleration of the leg. Conclusions Acceleration measured by neck collars is informative of the acceleration experienced by seeds attached to other body parts (breast and leg). When combined with animal movement data and lab measurements of how fur acceleration affects seed release and retention times, widely used collar accelerometers can thus be used to assess distances of epizoochorous seed dispersal. Keywords Body acceleration, Contact separation force, Epizoochorous seed dispersal, Wildlife collar, Mammals (notably mammals) also transport large numbers of seeds Background of many plant species via attachment to the exterior of Animals are among the most important vectors for long the body (epizoochory). A major challenge in the under- distance dispersal of plant seeds [14, 22, 30]. They dis - standing and prediction of epizoochorous seed dispersal perse seeds via endozoochory (passage through their is the quantification of seed detachment from the animal. digestive system, e.g., [16, 26]). However, many animals Consequently, we lack information on the retention time of seeds in animal fur, a crucial parameter for quantify- *Correspondence: ing seed dispersal and dispersal distances [30]. This study Carsten M. Buchmann aims at quantifying and explaining shaking movements, carsten.buchmann@uni-hohenheim.de 1 relevant for seed detachment from different parts of Institute of Landscape and Plant Ecology, University of Hohenheim, Ottilie-Zeller-Weg 2, D-70599 Stuttgart, Germany mammal bodies. In particular, it evaluates whether wild- life collars fitted with accelerometers, that are now widely © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 2 of 8 used on wild animals, can inform us on the process of which should result in higher acceleration of their body seed detachment. and hence larger forces acting on seeds in their fur (com- Two aspects of epizoochorous seed dispersal, namely, pare [7, 9, 24]). In contrast, higher inertia of the torso seed attachment to the fur and animal movement are of larger animals could possibly result in a weaker link comparatively well-studied by moving animal furs between the acceleration of the limbs and the neck. through/along vegetation [13], combing furs of wild ani- To assess the value of collar accelerometers for assess- mals (e.g., [20]) and recording animal movement with ing epizoochorous seed dispersal by wild animals, we modern tracking technology (e.g., [18, 40]). However, measured acceleration simultaneously at different body the quantification of seed detachment, which determines parts of mammals ranging in body mass from 26 to seed retention time and hence dispersal distance, is 867  kg. We then quantified (i) how acceleration at the more challenging, since epizoochorously dispersed seeds breast/torso and the leg of mammals is related to acceler- are typically small, hidden in animal fur and cannot be ation at the neck of animals, and (ii) how this relationship observed without altering animal behaviour [29]. depends on animal body mass. Since it is difficult to investigate seed detachment in the wild, previous studies have resorted to lab measure- Methods ments of the forces needed to detach seeds from fur or We measured three-dimensional acceleration on dif- the time needed to shake seeds out of the fur. They found ferent sections of the animal body for 40 individuals of that detachment is controlled by the interplay of the ani- 13 breeds of 8 mammal species kept at the Agricultural mal surface (e.g., fur properties) and seed morphology Science Faculty of the University of Hohenheim and Wil- (e.g., appendages like hooks), which determines the ‘con- helma Zoological Garden, Stuttgart (Table  1, Fig.  1). To tact separation force’ that is needed to detach the seed this end, accelerometers were attached with nylon straps from the fur [10, 11, 17, 37]. On an animal body forces (2.3  cm wide, metal buckles) to the neck, breast and to release seeds can be created via shaking of the body. hind leg (shank, between knee and heel) of the animals. According to Newton’s second law of motion, the force Deployment of sensors to the breast and leg was eas- experienced by a seed is the product of seed mass and fur ily feasible and caused minimal distress for the animals. acceleration. It has been shown that seed release can be Where necessary (e.g., for goats with short fur and thin induced by fur acceleration [35] and that the strength of legs), sensors were additionally fixed to the upper leg fur shaking determines the proportion of seeds released of the animals with adhesive elastic bandages. Animals (see Additional file 1: Figure S1). were then left to move for at least 5 min in their enclo- Accelerometers, that measure acceleration at high fre- sures (indoors and outdoors) with the aim of recording quency can quantify the force that seeds of a given mass a minimum of three time segments of at least 5 s with (i) experience in animal furs (according to Newton’s sec- walking-like movement and (ii) running movement. If ond law of motion, see above). Hence, accelerometers necessary and possible animals were tempted to move by on bodies of wild animals may provide information on leading them on a leash (camel, horse) or gently chasing seed detachment from and seed retention in fur. Thanks them (sheep, goat). This research was approved by the to rapid advances in GPS telemetry in the last decade [6, animal welfare officer of the University of Hohenheim 19] more and more studies measure animal acceleration (Nr. S 476/18 LÖ). in the wild, since nowadays many commercially avail- Sensors used were two MSR 165 (MSR Electronics able GPS tracking collars (e.g., Eobs, Vectronic aerospace, GmbH, Seuzach, Switzerland), recording continuously, Biotrack) are equipped with three-dimensional accel- and e-obs GPS and acceleration neck collars (e-obs erometers and the recording of acceleration data does GmbH, Grünwald, Germany), recording acceleration not cause much additional effort and costs (apart from in so-called “bursts” of 330 values (3.3  s) followed by a battery life and storage space). These data can be used (technically inevitable) gap of approx. 1.4  s. Positions to infer animal activity, energy budgets or even specific of the different sensors were randomly alternated. Still, behavioural patterns or syndromes [4, 15, 25, 34]. a large e-obs sensor (tag 1653) was only used with four Acceleration measurements on wild animals are mostly individuals, a smaller e-obs sensor (tag 4462) was more taken at the neck [8, 38], whereas most seeds are attached often used at the leg, since it was less disturbing for the to lower parts of the animal torso and the legs (compare animal and could be attached more easily and stable at [1, 27, 32]). However, it is largely unclear how accelera- the leg compared to the slightly heavier MSR sensors. tion of animal necks is related to acceleration of other Before use all four sensors were tested for comparability body parts. Moreover, such relationships may depend by simultaneously measuring the movement of a labo- on properties of the animals, notably their body mass. In ratory shaker. This showed negligible variation between general, smaller animals show faster (limb) movements sensors (max. 3.5% variation in maximum acceleration Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 3 of 8 Table 1 List of species and individuals used for the study including additional information on the animals and study conditions. Locations were all in Baden-Württemberg, Germany; Wilhelma Zoological Garden and research facility Hohenheim “Meiereihof “ are in Stuttgart, the research station Hohenheim “Unterer Lindenhof “ is located in Eningen unter Achalm Species Breed Individuals Individuals with Body mass Range of the Location Ground surface leg acceleration range (kg) length of hind measure-ment leg (cm) Camel (Camelus ferus) Bactrian Camel 3 3 580–800 94–103 Wilhelma Zoological Soil (outdoors) Garden Cow (Bos Taurus) Holstein–Friesian 3 3 715–867 97–100 Hohenheim (“Meierei-Concrete, plastic Cattle hof ”) (indoors) Cow (Bos taurus) Jersey Cattle 3 1 169–465 76–83 Hohenheim (“Meierei-Concrete (outdoors) hof ”) Donkey (Equus asinus) Poitou 3 3 470–530 83–90 Wilhelma Zoological Soil (outdoors) Garden Goat (Capra aegagrus) Bunte Deutsche 5 4 39–86 43–53 Hohenheim (“Meierei-Concrete with straw Edelziege hof ”) cover (indoors) Goat (Capra aegagrus) West African 2 1 26–28 30–34 Wilhelma Zoological Concrete (outdoors) Dwarf Garden Horse (Equus ferus caballus) Dülmener Horse 2 2 246–293 74–77 Wilhelma Zoological Soil (outdoors) Garden Horse (Equus ferus caballus) Shetland Pony 2 2 157–178 57–64 Wilhelma Zoological Soil (outdoors) Garden Mule (Equus mulus) – 1 1 292 72 Wilhelma Zoological Soil (outdoors) Garden Sheep (Ovis aries) Cameroon Sheep 4 4 27.5–50 38–43 Wilhelma Zoological Concrete (outdoors) Garden Sheep (Ovis aries) Merino 5 3 76 – 122 48–60 Hohenheim (“Meierei-Concrete with straw hof ”) cover (indoors), concrete and soil (outdoors) Pig (Sus scrofa domesticus) Deutsche Lan- 5 5 32–275 28–52 Hohenheim (’’Unterer Concrete (indoors) drasse x Pietrain Lindehof “) Pig (Sus scrofa domesticus) Kunekune 2 0 90–120 26–28 Wilhelma Zoological Soil (outdoors) Garden Locations were all in Baden-Württemberg, Germany; Wilhelma Zoological Garden and research facility Hohenheim “Meiereihof “ are in Stuttgart, the research station Hohenheim “Unterer Lindenhof “ is located in Eningen unter Achalm of any single sensor from the mean of all sensors). All the acceleration timeseries were cut into 5 s intervals on sensors were set to record at 100  Hz (i.e., each of the which analyses were performed. We chose an interval three axes would record at 33.3  Hz). Temporal synchro- length of 5 s, since this was short enough to cover only a nization of all collars/sensors was achieved by starting a single type of behaviour but long enough to minimize the 0.1 s resolution stop watch at the same time as manually impact of recording gaps of the e-obs sensors (see above). shaking all three sensors for approx. 15  s. This “extreme We did, however, repeat all analyses with 10  s intervals acceleration event” could later easily be recognized at the and found that this did not notably change results. beginning of the data series of all sensors and defined the From acceleration measurements in three dimensions, beginning of the specific measurement session. The time we calculated body acceleration by calculating the result- of the stop watch was used as reference for any observa- ant acceleration vector (resultant ac ce ler ation = sqrt(ac 2 2 2 tion during the animal trials that could be linked to the celerationX + accelerationY + accelerationZ ) and sub- data series (start and end of valid recording period for tracting gravitational acceleration (9.81  m/s ). We then any animal). Body mass of each individual was obtained calculated the 95%-quantile of body acceleration per 5  s from the respective zookeepers (last weighing). interval as a measure of maximum acceleration (Fig.  2). Acceleration data series were calibrated (raw meas- Intervals with maximum neck acceleration < 0.1  m/s urement values transformed to m/s ) according to were excluded from further analyses, since they represent manufacturer instructions and visually checked for syn- phases when the animals did not move. chronism between neck breast and leg. For each animal Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 4 of 8 acceleration, Fig. 4, left panel). The marginal R (variance explained by fixed effects only, i.e., neck acceleration and body mass) is 0.81. In addition, the acceleration at the hind leg is well-explained by neck acceleration and body mass (marginal R = 0.62), but here body mass increases the effect of neck acceleration on leg acceleration (Fig.  4, right panel). Coefficients of fitted models, likelihood- ratio tests and AIC values are given in the Additional file materials (Additional file  1: Tables S1, S2). Besides neck acceleration and body mass, some variability in body shaking is also explained by individuals and species (con- ditional R including fixed effects and random effect of individual nested within species was 0.89 and 0.71 for breast and leg acceleration, respectively). By back-trans- forming the fixed-effect components of the fitted (full) models, we obtain the following equations for accelera- tion A at the breast (Eq. 1) and leg (Eq. 2): 1.547 0.094 −0.107∗mass A = 0.534 ∗ A ∗ mass ∗ A breast neck neck Fig. 1 Examples of animals [top left: donkey (Equus asinus), top (1) right: camel (Camelus ferus), bottom: goat (Capra aegagrus)] carrying accelerometers (green arrows: MSR 165 and yellow arrows: e-obs 0.922 −0.170 0.044∗mass A = 4.222 ∗ A ∗ mass ∗ A leg neck neck sensor, tag 4462) around the neck, the breast and the upper hind leg. (2) Photos taken in Wilhelma Zoological Garden in Stuttgart, Germany Discussion To investigate how well maximum acceleration of other This study shows that maximum acceleration of the body parts can be explained by maximum acceleration of breast and leg of mammals can be predicted well from the neck and by an animal’s body mass we fitted linear two variables that are widely available for wild mam- mixed-effects models (packages lme4, [2] in R version mals: body mass (the most frequently used trait in ani- 4.0.2 [33]). The response variables of these models were mal ecology; [5, 7, 39] and acceleration of the neck (now maximum acceleration at the breast and the leg, respec- routinely measured by many wildlife collars). This makes tively. As fixed-effect predictor variables both models it possible to translate acceleration measurements at the included maximum acceleration at the neck and individ- neck into the forces experienced by plant seeds attached ual body mass plus the interaction of these two variables. to other body parts, a crucial step for assessing epizoo- The models also included random effects of individual chorous seed dispersal by wild mammals. The predictive nested within species on the intercept and the slope for capacity of maximum neck acceleration and body mass neck acceleration (Additional file 1: Eqs.  1, 2). These ran - was somewhat higher for maximum acceleration of the dom effects capture variation not accounted for by body breast than for maximum acceleration of the hind leg. mass (resulting from other animal traits or measure- This could be explained by the larger spatial separation ment conditions). All variables were log-transformed and of neck and hind legs. Moreover, different behaviours, scaled, to yield power-law scaling relationships. walking modes, gaits or movement speeds in the moment of measurement should more directly affect leg move - Results ment and hence, cause partial independence of leg and Maximum acceleration (the 95% quantile of body accel- neck acceleration. The fact that individual and species eration per 5  s interval) varied considerably between did not explain more variance of leg acceleration than species and individuals (Fig.  3, Additional file  1: Figure of breast acceleration (both less than 10%) supports this S2). Acceleration values and their variability (within an interpretation, namely, that such behavioural aspects play between species) were much larger at the hind leg than at an important role, especially compared to other species- the neck or breast. specific characteristics like body composition, geometry, Acceleration at the breast of animals is well-explained leg length etc. by acceleration at the neck of animals. Body mass slightly The weaker positive effect of neck acceleration on weakens the positive effect of neck acceleration on breast acceleration for larger animals is likely to result breast acceleration (negative interaction term with neck from greater torso inertia in large-bodied animals Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 5 of 8 −10 −20 −30 0306090 120 150 180 210 240 270 300 330 360 390 0306090 120 150 180 210 240 270 300 330 360 390 0306090 120 150 180 210 240 270 300 330 360 390 TIme [s] Fig. 2 Timeseries (covering 400 s) of the acceleration measured on the neck of a goat in each of the three axes (upper panel), the length of the resultant acceleration vector (middle panel) and the maximum acceleration (lower panel). Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval (compare [28]). To some extent, it may also reflect greater shaking can still be recorded with acceleration measure- neck length in large animals (notably camels) which may ments. However, numerous vascular plant species with- cause weaker translation of head movements into torso out obvious morphological adaptations to epizoochory, movement. such as hooked appendages, are transported in animal Quantification of acceleration at the body of mammals furs [13]. Particularly for these seeds body acceleration is of crucial importance for epizoochorous seed disper- while walking and running can be expected to be a very sal (compare [35]). For the removal of seeds with strongly important factor causing seed release  (compare  Addi- attaching appendages (e.g., hooks) intentional shaking, tional file 1: FigureS1). grooming behaviour or rubbing against objects [27] are To mechanistically predict distance of epizoochorous obviously very relevant. Among these at least intentional seed dispersal, acceleration measurements have to be Length of resultant Acceleration in dimensions −2 −2 −2 acceleration vector [m s ] X (red),Y (green), Z (blue) [m s ] Maximum acceleration [m s ] Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 6 of 8 Neck Breast Leg Fig. 3 Boxplots showing maximum acceleration at the neck, breast and leg of eight mammal species (ordered by increasing mean body mass). Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval. Outliers are omitted for clarity bactrian camel − 677kg 1e+02 1e+02 cow − 564kg donkey − 507kg 5e+01 5e+01 mule − 292kg horse − 218kg pig − 111kg sheep − 75kg goat − 48kg 1e+01 1e+01 100kg animal 500kg animal 5e+00 5e+00 1e+00 1e+00 5e−01 5e−01 1e−01 1e−01 5e−02 5e−02 0.1 0.5 1.0 5.0 50.0 0.10.5 1.05.0 50.0 −2 −2 Neck maximum acceleration [m s ] Neck maximum acceleration [m s ] Fig. 4 Prediction plots of linear mixed-effects models for maximum acceleration at the breast (left panel) and the hind leg (right panel). Predictions are only shown for fixed effects, namely neck acceleration and body mass; line thickness and symbol size indicate mean species body mass and individual body mass, respectively, see legend. Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval −2 Breast maximum acceleration [m s ] −2 Maximum acceleration [m s ] Goat Sheep Pig −2 Horse Leg maximum acceleration [m s ] Mule Donkey Cow Bactrian Camel Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 7 of 8 integrated with other types of data. First, estimates of runs, each with 15 seeds of any species placed on the fur). Note: some the acceleration and resulting force experienced by seeds noise is added to the x-coordinates of the symbols to improve readability. Figure S2. Boxplots showing maximum accelerationfile as well.accelera- need to be combined with either direct measures of the tion) determined for 5 s subsections of acceleration data measured at contact separation force of seeds in a particular fur [17] the neck, breast and leg of 40 individuals of 13 breeds of 8 mammal or with measurements of the distribution of seed reten- species; ordered after individual body mass. Outliers are omitted for clarity. Table S1. Summary of fitted linear mixed-effects models for breast and tion times for given fur acceleration [35]. This will yield leg acceleration. Model coefficients are for models with log-transformed distributions of retention times for a specific seed-fur and scaled variables. Likelihood-ratio tests were performed between full combination. Secondly, by combining these retention modeland additive modelfor the interaction term, and for Aneck and mass they were performed between the additive model and the model con- time distributions with measures of animal speed or spa- taining only mass and Aneck, respectively. Table S2. AIC values of the full tially explicit movement trajectories, one can obtain dis- linear mixed-effects models for breast and leg accelerationand reduced tances of epizoochorous seed dispersal (analogous to [36, simplified model versions. 40] for endozoochorous seed dispersal). Knowledge of variation in acceleration across animal Acknowledgements bodies may also be relevant for ecological fields other The authors thank many scientists and technicians that helped in data col- lection: the Biomove team at the University of Potsdam, specifically F. Jeltsch than the study of seed dispersal. Body acceleration deter- and W. Ullmann, the working groups Behavioral Physiology of Livestock and of mines the forces experienced not only by seeds but also Animal Nutrition at the University of Hohenheim and the teams at Meiereihof by animals such as grasshoppers that are dispersed in fur and Unterer Lindenhof, specifically M. Rodehutscord, V. Stefanski, B. Pfaffinger, J. Krieg, H. Trapp, W. Dunne and M. Ganser, and the team of Wilhelma Zoologi- [13]. Moreover, ecto-parasites have to spend more energy cal Garden, specifically B. Schäfer and G. Schleussner. when experiencing strong and repeated acceleration, while they crawl through the fur until they reach their Author contributions CMB and FMS conceived the idea. CMB organized and led data collection, targeted feeding location [31]. Once an ecto-parasite analysed the data and wrote the manuscript. LD and MC assisted data collec- started feeding, the acceleration it experiences should tion. FMS, LD and MC assisted analysis. All authors contributed critically to the become even more relevant, since it determines how manuscript drafts and gave final approval for publication. All authors read and approved the final manuscript. strongly attachment force has to increase as the parasite’s mass increases [23]. Such variation in energy expenditure Funding is likely to affect the fitness of ecto-parasites and their Open Access funding enabled and organized by Projekt DEAL. hosts. Availability of data and materials All data, specifically measured acceleration of all animals, are published at Outlook and conclusions figshare.com: https:// doi. org/ 10. 6084/ m9. figsh are. 20182 100. v1 Acceleration measurements at animal necks contain val- uable information on epizoochorous seed dispersal by Declarations wild mammals. Since such measurements are now widely Ethics approval and consent to participate available, there is considerable potential for ‘recycling’ This research was approved by the animal welfare officer of the University of them [21] to assess the dispersal services provided by Hohenheim (Nr. S 476/18 LÖ). wild animals [12]. Consent for publication Not applicable. Abbreviations Competing interests Aneck Maximum acceleration at animals’ necks (m/s ) Quantified as the The authors declare that they have no competing interests. 95%-quantile of resultant acceleration Abreast M aximum acceleration at animals’ breasts (m/s ) Quantified as the 95%-quantile of resultant acceleration Received: 8 November 2022 Accepted: 20 April 2023 Aleg Maximum acceleration at animals’ hind legs (m/s ) Quantified as the 95%-quantile of resultant acceleration mass Individual body mass (kg) References Supplementary Information 1. Albert A, Mårell A, Picard M, Baltzinger C. 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What acceleration data from wildlife collars and animal body mass tell us about seed dispersal

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Abstract

Background The seeds of many plant species can be dispersed over long distances in animal fur (epizoochory). Quantifying epizoochory in the wild is, however, challenging, since it is difficult to measure the retention times of seeds in fur. These retention times depend on the acceleration that seeds experience and that can detach seeds from fur. Wildlife collars containing accelerometers may thus provide crucial information on epizoochorous seed dispersal. However, this is only the case if acceleration of the animal’s neck (where collars are attached) is informative of accel- eration of the animal’s main body (where most seeds are transported). Methods We used accelerometers to simultaneously measure acceleration at the neck, breast and the upper hind leg of 40 individuals of eight mammal species spanning a large range of body masses (26–867 kg). We then quantified maximum acceleration as the 95%-quantile of the resultant acceleration (of all measured values in data intervals of 5 s). Results Maximum acceleration was comparable between the neck and breast but substantially higher at the hind leg. Maximum acceleration measured by neck collars and body mass jointly explained 81% of the variance in maxi- mum acceleration of the breast and 62% of the variance in maximum acceleration of the leg. Conclusions Acceleration measured by neck collars is informative of the acceleration experienced by seeds attached to other body parts (breast and leg). When combined with animal movement data and lab measurements of how fur acceleration affects seed release and retention times, widely used collar accelerometers can thus be used to assess distances of epizoochorous seed dispersal. Keywords Body acceleration, Contact separation force, Epizoochorous seed dispersal, Wildlife collar, Mammals (notably mammals) also transport large numbers of seeds Background of many plant species via attachment to the exterior of Animals are among the most important vectors for long the body (epizoochory). A major challenge in the under- distance dispersal of plant seeds [14, 22, 30]. They dis - standing and prediction of epizoochorous seed dispersal perse seeds via endozoochory (passage through their is the quantification of seed detachment from the animal. digestive system, e.g., [16, 26]). However, many animals Consequently, we lack information on the retention time of seeds in animal fur, a crucial parameter for quantify- *Correspondence: ing seed dispersal and dispersal distances [30]. This study Carsten M. Buchmann aims at quantifying and explaining shaking movements, carsten.buchmann@uni-hohenheim.de 1 relevant for seed detachment from different parts of Institute of Landscape and Plant Ecology, University of Hohenheim, Ottilie-Zeller-Weg 2, D-70599 Stuttgart, Germany mammal bodies. In particular, it evaluates whether wild- life collars fitted with accelerometers, that are now widely © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 2 of 8 used on wild animals, can inform us on the process of which should result in higher acceleration of their body seed detachment. and hence larger forces acting on seeds in their fur (com- Two aspects of epizoochorous seed dispersal, namely, pare [7, 9, 24]). In contrast, higher inertia of the torso seed attachment to the fur and animal movement are of larger animals could possibly result in a weaker link comparatively well-studied by moving animal furs between the acceleration of the limbs and the neck. through/along vegetation [13], combing furs of wild ani- To assess the value of collar accelerometers for assess- mals (e.g., [20]) and recording animal movement with ing epizoochorous seed dispersal by wild animals, we modern tracking technology (e.g., [18, 40]). However, measured acceleration simultaneously at different body the quantification of seed detachment, which determines parts of mammals ranging in body mass from 26 to seed retention time and hence dispersal distance, is 867  kg. We then quantified (i) how acceleration at the more challenging, since epizoochorously dispersed seeds breast/torso and the leg of mammals is related to acceler- are typically small, hidden in animal fur and cannot be ation at the neck of animals, and (ii) how this relationship observed without altering animal behaviour [29]. depends on animal body mass. Since it is difficult to investigate seed detachment in the wild, previous studies have resorted to lab measure- Methods ments of the forces needed to detach seeds from fur or We measured three-dimensional acceleration on dif- the time needed to shake seeds out of the fur. They found ferent sections of the animal body for 40 individuals of that detachment is controlled by the interplay of the ani- 13 breeds of 8 mammal species kept at the Agricultural mal surface (e.g., fur properties) and seed morphology Science Faculty of the University of Hohenheim and Wil- (e.g., appendages like hooks), which determines the ‘con- helma Zoological Garden, Stuttgart (Table  1, Fig.  1). To tact separation force’ that is needed to detach the seed this end, accelerometers were attached with nylon straps from the fur [10, 11, 17, 37]. On an animal body forces (2.3  cm wide, metal buckles) to the neck, breast and to release seeds can be created via shaking of the body. hind leg (shank, between knee and heel) of the animals. According to Newton’s second law of motion, the force Deployment of sensors to the breast and leg was eas- experienced by a seed is the product of seed mass and fur ily feasible and caused minimal distress for the animals. acceleration. It has been shown that seed release can be Where necessary (e.g., for goats with short fur and thin induced by fur acceleration [35] and that the strength of legs), sensors were additionally fixed to the upper leg fur shaking determines the proportion of seeds released of the animals with adhesive elastic bandages. Animals (see Additional file 1: Figure S1). were then left to move for at least 5 min in their enclo- Accelerometers, that measure acceleration at high fre- sures (indoors and outdoors) with the aim of recording quency can quantify the force that seeds of a given mass a minimum of three time segments of at least 5 s with (i) experience in animal furs (according to Newton’s sec- walking-like movement and (ii) running movement. If ond law of motion, see above). Hence, accelerometers necessary and possible animals were tempted to move by on bodies of wild animals may provide information on leading them on a leash (camel, horse) or gently chasing seed detachment from and seed retention in fur. Thanks them (sheep, goat). This research was approved by the to rapid advances in GPS telemetry in the last decade [6, animal welfare officer of the University of Hohenheim 19] more and more studies measure animal acceleration (Nr. S 476/18 LÖ). in the wild, since nowadays many commercially avail- Sensors used were two MSR 165 (MSR Electronics able GPS tracking collars (e.g., Eobs, Vectronic aerospace, GmbH, Seuzach, Switzerland), recording continuously, Biotrack) are equipped with three-dimensional accel- and e-obs GPS and acceleration neck collars (e-obs erometers and the recording of acceleration data does GmbH, Grünwald, Germany), recording acceleration not cause much additional effort and costs (apart from in so-called “bursts” of 330 values (3.3  s) followed by a battery life and storage space). These data can be used (technically inevitable) gap of approx. 1.4  s. Positions to infer animal activity, energy budgets or even specific of the different sensors were randomly alternated. Still, behavioural patterns or syndromes [4, 15, 25, 34]. a large e-obs sensor (tag 1653) was only used with four Acceleration measurements on wild animals are mostly individuals, a smaller e-obs sensor (tag 4462) was more taken at the neck [8, 38], whereas most seeds are attached often used at the leg, since it was less disturbing for the to lower parts of the animal torso and the legs (compare animal and could be attached more easily and stable at [1, 27, 32]). However, it is largely unclear how accelera- the leg compared to the slightly heavier MSR sensors. tion of animal necks is related to acceleration of other Before use all four sensors were tested for comparability body parts. Moreover, such relationships may depend by simultaneously measuring the movement of a labo- on properties of the animals, notably their body mass. In ratory shaker. This showed negligible variation between general, smaller animals show faster (limb) movements sensors (max. 3.5% variation in maximum acceleration Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 3 of 8 Table 1 List of species and individuals used for the study including additional information on the animals and study conditions. Locations were all in Baden-Württemberg, Germany; Wilhelma Zoological Garden and research facility Hohenheim “Meiereihof “ are in Stuttgart, the research station Hohenheim “Unterer Lindenhof “ is located in Eningen unter Achalm Species Breed Individuals Individuals with Body mass Range of the Location Ground surface leg acceleration range (kg) length of hind measure-ment leg (cm) Camel (Camelus ferus) Bactrian Camel 3 3 580–800 94–103 Wilhelma Zoological Soil (outdoors) Garden Cow (Bos Taurus) Holstein–Friesian 3 3 715–867 97–100 Hohenheim (“Meierei-Concrete, plastic Cattle hof ”) (indoors) Cow (Bos taurus) Jersey Cattle 3 1 169–465 76–83 Hohenheim (“Meierei-Concrete (outdoors) hof ”) Donkey (Equus asinus) Poitou 3 3 470–530 83–90 Wilhelma Zoological Soil (outdoors) Garden Goat (Capra aegagrus) Bunte Deutsche 5 4 39–86 43–53 Hohenheim (“Meierei-Concrete with straw Edelziege hof ”) cover (indoors) Goat (Capra aegagrus) West African 2 1 26–28 30–34 Wilhelma Zoological Concrete (outdoors) Dwarf Garden Horse (Equus ferus caballus) Dülmener Horse 2 2 246–293 74–77 Wilhelma Zoological Soil (outdoors) Garden Horse (Equus ferus caballus) Shetland Pony 2 2 157–178 57–64 Wilhelma Zoological Soil (outdoors) Garden Mule (Equus mulus) – 1 1 292 72 Wilhelma Zoological Soil (outdoors) Garden Sheep (Ovis aries) Cameroon Sheep 4 4 27.5–50 38–43 Wilhelma Zoological Concrete (outdoors) Garden Sheep (Ovis aries) Merino 5 3 76 – 122 48–60 Hohenheim (“Meierei-Concrete with straw hof ”) cover (indoors), concrete and soil (outdoors) Pig (Sus scrofa domesticus) Deutsche Lan- 5 5 32–275 28–52 Hohenheim (’’Unterer Concrete (indoors) drasse x Pietrain Lindehof “) Pig (Sus scrofa domesticus) Kunekune 2 0 90–120 26–28 Wilhelma Zoological Soil (outdoors) Garden Locations were all in Baden-Württemberg, Germany; Wilhelma Zoological Garden and research facility Hohenheim “Meiereihof “ are in Stuttgart, the research station Hohenheim “Unterer Lindenhof “ is located in Eningen unter Achalm of any single sensor from the mean of all sensors). All the acceleration timeseries were cut into 5 s intervals on sensors were set to record at 100  Hz (i.e., each of the which analyses were performed. We chose an interval three axes would record at 33.3  Hz). Temporal synchro- length of 5 s, since this was short enough to cover only a nization of all collars/sensors was achieved by starting a single type of behaviour but long enough to minimize the 0.1 s resolution stop watch at the same time as manually impact of recording gaps of the e-obs sensors (see above). shaking all three sensors for approx. 15  s. This “extreme We did, however, repeat all analyses with 10  s intervals acceleration event” could later easily be recognized at the and found that this did not notably change results. beginning of the data series of all sensors and defined the From acceleration measurements in three dimensions, beginning of the specific measurement session. The time we calculated body acceleration by calculating the result- of the stop watch was used as reference for any observa- ant acceleration vector (resultant ac ce ler ation = sqrt(ac 2 2 2 tion during the animal trials that could be linked to the celerationX + accelerationY + accelerationZ ) and sub- data series (start and end of valid recording period for tracting gravitational acceleration (9.81  m/s ). We then any animal). Body mass of each individual was obtained calculated the 95%-quantile of body acceleration per 5  s from the respective zookeepers (last weighing). interval as a measure of maximum acceleration (Fig.  2). Acceleration data series were calibrated (raw meas- Intervals with maximum neck acceleration < 0.1  m/s urement values transformed to m/s ) according to were excluded from further analyses, since they represent manufacturer instructions and visually checked for syn- phases when the animals did not move. chronism between neck breast and leg. For each animal Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 4 of 8 acceleration, Fig. 4, left panel). The marginal R (variance explained by fixed effects only, i.e., neck acceleration and body mass) is 0.81. In addition, the acceleration at the hind leg is well-explained by neck acceleration and body mass (marginal R = 0.62), but here body mass increases the effect of neck acceleration on leg acceleration (Fig.  4, right panel). Coefficients of fitted models, likelihood- ratio tests and AIC values are given in the Additional file materials (Additional file  1: Tables S1, S2). Besides neck acceleration and body mass, some variability in body shaking is also explained by individuals and species (con- ditional R including fixed effects and random effect of individual nested within species was 0.89 and 0.71 for breast and leg acceleration, respectively). By back-trans- forming the fixed-effect components of the fitted (full) models, we obtain the following equations for accelera- tion A at the breast (Eq. 1) and leg (Eq. 2): 1.547 0.094 −0.107∗mass A = 0.534 ∗ A ∗ mass ∗ A breast neck neck Fig. 1 Examples of animals [top left: donkey (Equus asinus), top (1) right: camel (Camelus ferus), bottom: goat (Capra aegagrus)] carrying accelerometers (green arrows: MSR 165 and yellow arrows: e-obs 0.922 −0.170 0.044∗mass A = 4.222 ∗ A ∗ mass ∗ A leg neck neck sensor, tag 4462) around the neck, the breast and the upper hind leg. (2) Photos taken in Wilhelma Zoological Garden in Stuttgart, Germany Discussion To investigate how well maximum acceleration of other This study shows that maximum acceleration of the body parts can be explained by maximum acceleration of breast and leg of mammals can be predicted well from the neck and by an animal’s body mass we fitted linear two variables that are widely available for wild mam- mixed-effects models (packages lme4, [2] in R version mals: body mass (the most frequently used trait in ani- 4.0.2 [33]). The response variables of these models were mal ecology; [5, 7, 39] and acceleration of the neck (now maximum acceleration at the breast and the leg, respec- routinely measured by many wildlife collars). This makes tively. As fixed-effect predictor variables both models it possible to translate acceleration measurements at the included maximum acceleration at the neck and individ- neck into the forces experienced by plant seeds attached ual body mass plus the interaction of these two variables. to other body parts, a crucial step for assessing epizoo- The models also included random effects of individual chorous seed dispersal by wild mammals. The predictive nested within species on the intercept and the slope for capacity of maximum neck acceleration and body mass neck acceleration (Additional file 1: Eqs.  1, 2). These ran - was somewhat higher for maximum acceleration of the dom effects capture variation not accounted for by body breast than for maximum acceleration of the hind leg. mass (resulting from other animal traits or measure- This could be explained by the larger spatial separation ment conditions). All variables were log-transformed and of neck and hind legs. Moreover, different behaviours, scaled, to yield power-law scaling relationships. walking modes, gaits or movement speeds in the moment of measurement should more directly affect leg move - Results ment and hence, cause partial independence of leg and Maximum acceleration (the 95% quantile of body accel- neck acceleration. The fact that individual and species eration per 5  s interval) varied considerably between did not explain more variance of leg acceleration than species and individuals (Fig.  3, Additional file  1: Figure of breast acceleration (both less than 10%) supports this S2). Acceleration values and their variability (within an interpretation, namely, that such behavioural aspects play between species) were much larger at the hind leg than at an important role, especially compared to other species- the neck or breast. specific characteristics like body composition, geometry, Acceleration at the breast of animals is well-explained leg length etc. by acceleration at the neck of animals. Body mass slightly The weaker positive effect of neck acceleration on weakens the positive effect of neck acceleration on breast acceleration for larger animals is likely to result breast acceleration (negative interaction term with neck from greater torso inertia in large-bodied animals Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 5 of 8 −10 −20 −30 0306090 120 150 180 210 240 270 300 330 360 390 0306090 120 150 180 210 240 270 300 330 360 390 0306090 120 150 180 210 240 270 300 330 360 390 TIme [s] Fig. 2 Timeseries (covering 400 s) of the acceleration measured on the neck of a goat in each of the three axes (upper panel), the length of the resultant acceleration vector (middle panel) and the maximum acceleration (lower panel). Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval (compare [28]). To some extent, it may also reflect greater shaking can still be recorded with acceleration measure- neck length in large animals (notably camels) which may ments. However, numerous vascular plant species with- cause weaker translation of head movements into torso out obvious morphological adaptations to epizoochory, movement. such as hooked appendages, are transported in animal Quantification of acceleration at the body of mammals furs [13]. Particularly for these seeds body acceleration is of crucial importance for epizoochorous seed disper- while walking and running can be expected to be a very sal (compare [35]). For the removal of seeds with strongly important factor causing seed release  (compare  Addi- attaching appendages (e.g., hooks) intentional shaking, tional file 1: FigureS1). grooming behaviour or rubbing against objects [27] are To mechanistically predict distance of epizoochorous obviously very relevant. Among these at least intentional seed dispersal, acceleration measurements have to be Length of resultant Acceleration in dimensions −2 −2 −2 acceleration vector [m s ] X (red),Y (green), Z (blue) [m s ] Maximum acceleration [m s ] Buchmann et al. Animal Biotelemetry (2023) 11:22 Page 6 of 8 Neck Breast Leg Fig. 3 Boxplots showing maximum acceleration at the neck, breast and leg of eight mammal species (ordered by increasing mean body mass). Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval. Outliers are omitted for clarity bactrian camel − 677kg 1e+02 1e+02 cow − 564kg donkey − 507kg 5e+01 5e+01 mule − 292kg horse − 218kg pig − 111kg sheep − 75kg goat − 48kg 1e+01 1e+01 100kg animal 500kg animal 5e+00 5e+00 1e+00 1e+00 5e−01 5e−01 1e−01 1e−01 5e−02 5e−02 0.1 0.5 1.0 5.0 50.0 0.10.5 1.05.0 50.0 −2 −2 Neck maximum acceleration [m s ] Neck maximum acceleration [m s ] Fig. 4 Prediction plots of linear mixed-effects models for maximum acceleration at the breast (left panel) and the hind leg (right panel). Predictions are only shown for fixed effects, namely neck acceleration and body mass; line thickness and symbol size indicate mean species body mass and individual body mass, respectively, see legend. Maximum acceleration is calculated as the 95% quantile of resultant acceleration minus gravitational acceleration per 5 s interval −2 Breast maximum acceleration [m s ] −2 Maximum acceleration [m s ] Goat Sheep Pig −2 Horse Leg maximum acceleration [m s ] Mule Donkey Cow Bactrian Camel Buchmann  et al. Animal Biotelemetry (2023) 11:22 Page 7 of 8 integrated with other types of data. First, estimates of runs, each with 15 seeds of any species placed on the fur). Note: some the acceleration and resulting force experienced by seeds noise is added to the x-coordinates of the symbols to improve readability. Figure S2. Boxplots showing maximum accelerationfile as well.accelera- need to be combined with either direct measures of the tion) determined for 5 s subsections of acceleration data measured at contact separation force of seeds in a particular fur [17] the neck, breast and leg of 40 individuals of 13 breeds of 8 mammal or with measurements of the distribution of seed reten- species; ordered after individual body mass. Outliers are omitted for clarity. Table S1. Summary of fitted linear mixed-effects models for breast and tion times for given fur acceleration [35]. This will yield leg acceleration. Model coefficients are for models with log-transformed distributions of retention times for a specific seed-fur and scaled variables. Likelihood-ratio tests were performed between full combination. Secondly, by combining these retention modeland additive modelfor the interaction term, and for Aneck and mass they were performed between the additive model and the model con- time distributions with measures of animal speed or spa- taining only mass and Aneck, respectively. Table S2. AIC values of the full tially explicit movement trajectories, one can obtain dis- linear mixed-effects models for breast and leg accelerationand reduced tances of epizoochorous seed dispersal (analogous to [36, simplified model versions. 40] for endozoochorous seed dispersal). Knowledge of variation in acceleration across animal Acknowledgements bodies may also be relevant for ecological fields other The authors thank many scientists and technicians that helped in data col- lection: the Biomove team at the University of Potsdam, specifically F. Jeltsch than the study of seed dispersal. Body acceleration deter- and W. Ullmann, the working groups Behavioral Physiology of Livestock and of mines the forces experienced not only by seeds but also Animal Nutrition at the University of Hohenheim and the teams at Meiereihof by animals such as grasshoppers that are dispersed in fur and Unterer Lindenhof, specifically M. Rodehutscord, V. Stefanski, B. Pfaffinger, J. Krieg, H. Trapp, W. Dunne and M. Ganser, and the team of Wilhelma Zoologi- [13]. Moreover, ecto-parasites have to spend more energy cal Garden, specifically B. Schäfer and G. Schleussner. when experiencing strong and repeated acceleration, while they crawl through the fur until they reach their Author contributions CMB and FMS conceived the idea. CMB organized and led data collection, targeted feeding location [31]. Once an ecto-parasite analysed the data and wrote the manuscript. LD and MC assisted data collec- started feeding, the acceleration it experiences should tion. FMS, LD and MC assisted analysis. All authors contributed critically to the become even more relevant, since it determines how manuscript drafts and gave final approval for publication. All authors read and approved the final manuscript. strongly attachment force has to increase as the parasite’s mass increases [23]. Such variation in energy expenditure Funding is likely to affect the fitness of ecto-parasites and their Open Access funding enabled and organized by Projekt DEAL. hosts. Availability of data and materials All data, specifically measured acceleration of all animals, are published at Outlook and conclusions figshare.com: https:// doi. org/ 10. 6084/ m9. figsh are. 20182 100. v1 Acceleration measurements at animal necks contain val- uable information on epizoochorous seed dispersal by Declarations wild mammals. Since such measurements are now widely Ethics approval and consent to participate available, there is considerable potential for ‘recycling’ This research was approved by the animal welfare officer of the University of them [21] to assess the dispersal services provided by Hohenheim (Nr. S 476/18 LÖ). wild animals [12]. Consent for publication Not applicable. Abbreviations Competing interests Aneck Maximum acceleration at animals’ necks (m/s ) Quantified as the The authors declare that they have no competing interests. 95%-quantile of resultant acceleration Abreast M aximum acceleration at animals’ breasts (m/s ) Quantified as the 95%-quantile of resultant acceleration Received: 8 November 2022 Accepted: 20 April 2023 Aleg Maximum acceleration at animals’ hind legs (m/s ) Quantified as the 95%-quantile of resultant acceleration mass Individual body mass (kg) References Supplementary Information 1. Albert A, Mårell A, Picard M, Baltzinger C. 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Journal

Animal Biotelemetry – Springer Journals

Published: May 18, 2023

Keywords: Body acceleration; Contact separation force; Epizoochorous seed dispersal; Wildlife collar; Mammals

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