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2. Tracking data highlight the importance of human-induced mortality for large migratory birds at a flyway scale

Author

Serratosa, Juan, Oppel, Steffen, Rotics, Shay, Santangeli, Andrea, Butchart, Stuart H.M., Cano-Alonso, Luis S., Tellería, Jose Luis, Kemp, Ryno, Nicholas, Aaron, Kalvāns, Aigars, Galarza, Aitor, Franco, Aldina M.A., Andreotti, Alessandro, Kirschel, Alexander N.G., Ngari, Alex, Soutullo, Alvaro, Bermejo-Bermejo, Ana, Botha, Andre J., Ferri, Andrea, Evangelidis, Angelos, Cenerini, Anna, Stamenov, Anton, Hernández-Matías, Antonio, Aradis, Arianna, Grozdanov, Atanas P., Rodríguez, Beneharo, Şekercioğlu, Çağan H., Cerecedo-Iglesias, Catuxa, Kassara, Christina, Barboutis, Christos, Bracebridge, Claire, García-Ripollés, Clara, Kendall, Corinne J., Denac, Damijan, Schabo, Dana G., Barber, David R., Popov, Dimitar V., Dobrev, Dobromir D., Mallia, Egidio, Kmetova-Biro, Elena, Álvarez, Ernesto, Buechley, Evan R., Bragin, Evgeny A., Cordischi, Fabrizio, Zengeya, Fadzai M., Monti, Flavio, Mougeot, Francois, Tate, Gareth, Stoyanov, Georgi, Dell'Omo, Giacomo, Lucia, Giuseppe, Gradev, Gradimir, Ceccolini, Guido, Friedemann, Guilad, Bauer, Hans-Günther, Kolberg, Holger, Peshev, Hristo, Catry, Inês, Øien, Ingar J., Alanís, Isidoro Carbonell, Literák, Ivan, Pokrovsky, Ivan, Ojaste, Ivar, Østnes, Jan E., de la Puente, Javier, Real, Joan, Guilherme, João L., González, José C., Fernández-García, José M., Gil, Juan Antonio, Terraube, Julien, Poprach, Karel, Aghababyan, Karen, Klein, Katharina, Bildstein, Keith L., Wolter, Kerri, Janssens, Kjell, Kittelberger, Kyle D., Thompson, Lindy J., AlJahdhami, Mansoor H., Galán, Manuel, Tobolka, Marcin, Posillico, Mario, Cipollone, Mario, Gschweng, Marion, Strazds, Māris, Boorman, Mark, Zvidzai, Mark, Acácio, Marta, Romero, Marta, Wikelski, Martin, Schmidt, Matthias, Sarà, Maurizio, McGrady, Michael J., Dagys, Mindaugas, Mackenzie, Monique L., Al Taq, Muna, Mgumba, Msafiri P., Virani, Munir Z., Kassinis, Nicolaos I., Borgianni, Nicolò, Thie, Nikki, Tsiopelas, Nikos, Anglister, Nili, Farwig, Nina, Sapir, Nir, Kleven, Oddmund, Krone, Oliver, Duriez, Olivier, Spiegel, Orr, Al Nouri, Osama, López-López, Pascual, Byholm, Patrik, Kamath, Pauline L., Mirski, Paweł, Palatitz, Peter, Serroni, Pietro, Raab, Rainer, Buij, Ralph, Žydelis, Ramūnas, Nathan, Ran, Bowie, Rauri C.K., Tsiakiris, Rigas, Hatfield, Richard Stratton, Harel, Roi, Kroglund, Rolf T., Efrat, Ron, Limiñana, Ruben, Javed, Salim, Marinković, Saša P., Rösner, Sascha, Pekarsky, Sasha, Kapila, Shiv R., Marin, Simeon A., Krejčí, Šimon, Giokas, Sinos, Tumanyan, Siranush, Turjeman, Sondra, Krüger, Sonja C., Ewing, Steven R., Stoychev, Stoycho, Nikolov, Stoyan C., Qaneer, Tareq E., Spatz, Theresa, Hadjikyriakou, Thomas G., Mueller, Thomas, Katzner, Todd E., Aarvak, Tomas, Veselovský, Tomáš, Nygård, Torgeir, Mellone, Ugo, Väli, Ülo, Sellis, Urmas, Urios, Vicente, Nemček, Vladimír, Arkumarev, Volen, Getz, Wayne M., Fiedler, Wolfgang, Van den Bossche, Willem, Lehnardt, Yael, and Jones, Victoria R.

Published
2024
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7. Topic Modeling of Behavioral Modes Using Sensor Data

Author

Resheff, Yehezkel S., Rotics, Shay, Nathan, Ran, and Weinshall, Daphna

Subjects
Computer Science - Learning
Abstract

The field of Movement Ecology, like so many other fields, is experiencing a period of rapid growth in availability of data. As the volume rises, traditional methods are giving way to machine learning and data science, which are playing an increasingly large part it turning this data into science-driving insights. One rich and interesting source is the bio-logger. These small electronic wearable devices are attached to animals free to roam in their natural habitats, and report back readings from multiple sensors, including GPS and accelerometer bursts. A common use of accelerometer data is for supervised learning of behavioral modes. However, we need unsupervised analysis tools as well, in order to overcome the inherent difficulties of obtaining a labeled dataset, which in some cases is either infeasible or does not successfully encompass the full repertoire of behavioral modes of interest. Here we present a matrix factorization based topic-model method for accelerometer bursts, derived using a linear mixture property of patch features. Our method is validated via comparison to a labeled dataset, and is further compared to standard clustering algorithms., Comment: Invited Extended version of a paper \cite{resheffmatrix} presented at the international conference \textit{Data Science and Advanced Analytics}, Paris, France, 19-21 OCtober 2015

Published
2015

8. Tracking data highlight the importance of human-induced mortality for large migratory birds at a flyway scale

Author

Universidad de Alicante. Departamento de Ciencias Ambientales y Recursos Naturales, Universidad de Alicante. Departamento de Didáctica General y Didácticas Específicas, Universidad de Alicante. Instituto Universitario de Física Aplicada a las Ciencias y las Tecnologías, Serratosa, Juan, Oppel, Steffen, Rotics, Shay, Santangeli, Andrea, Butchart, Stuart H.M., Cano-Alonso, Luis S., Tellería Jorge, José Luis, Kemp, Ryno, Nicholas, Aaron, Kalvāns, Aigars, Galarza, Aitor, Franco, Aldina M.A., Andreotti, Alessandro, Kirschel, Alexander N.G., Ngari, Alex, Soutullo, Alvaro, Bermejo, Ana, Botha, Andre J., Ferri, Andrea, Evangelidis, Angelos, Cenerini, Anna, Stamenov, Anton, Hernández-Matías, Antonio, Aradis, Arianna, Grozdanov, Atanas P., Rodríguez, Beneharo, Sekercioğlu, Cağan H., Cerecedo-Iglesias, Catuxa, Kassara, Christina, Barboutis, Christos, Bracebridge, Claire, García Ripollés, Clara, Kendall, Corinne J., Denac, Damijan, Schabo, Dana G., Barber, David R., Popov, Dimitar V., Dobrev, Dobromir D., Mallia, Egidio, Kmetova-Biro, Elena, Álvarez, Ernesto, Buechley, Evan R., Bragin, Evgeny A., Cordischi, Fabrizio, Zengeya, Fadzai M., Monti, Flavio, Mougeot, François, Tate, Gareth, Stoyanov, Georgi, Dell’Omo, Giacomo, Lucia, Giuseppe, Gradev, Gradimir, Ceccolini, Guido, Friedemann, Guilad, Bauer, Hans-Günther, Kolberg, Holger, Peshev, Hristo, Catry, Inês, Øien, Ingar J., Carbonell Alanís, Isidoro, Literák, Ivan, Pokrovsky, Ivan, Ojaste, Ivar, Østnes, Jan E., Puente, Javier de la, Real, Joan, Guilherme, João L., González, José C., Fernández-García, José M., Gil, Juan Antonio, Terraube, Julien, Poprach, Karel, Aghababyan, Karen, Klein, Katharina, Bildstein, Keith L., Wolter, Kerri, Janssens, Kjell, Kittelberger, Kyle D., Thompson, Lindy J., AlJahdhami, Mansoor H., Galán, Manuel, Tobolka, Marcin, Posillico, Mario, Cipollone, Mario, Gschweng, Marion, Strazds, Māris, Boorman, Mark, Zvidzai, Mark, Acácio, Marta, Romero, Marta, Wikelski, Martin, Schmidt, Matthias, Sarà, Maurizio, McGrady, Michael J., Dagys, Mindaugas, Mackenzie, Monique L., Al Taq, Muna, Mgumba, Msafiri P., Virani, Munir Z., Kassinis, Nicolaos I., Borgianni, Nicolò, Thie, Nikki, Tsiopelas, Nikos, Anglister, Nili, Farwig, Nina, Sapir, Nir, Kleven, Oddmund, Krone, Oliver, Duriez, Olivier, Spiegel, Orr, Al Nouri, Osama, López-López, Pascual, Byholm, Patrik, Kamath, Pauline L., Mirski, Paweł, Palatitz, Peter, Serroni, Pietro, Raab, Rainer, Buij, Ralph, Žydelis, Ramūnas, Nathan, Ran, Bowie, Rauri C.K., Tsiakiris, Rigas, Hatfield, Richard Stratton, Harel, Roi, Kroglund, Rolf T., Efrat, Ron, Limiñana, Rubén, Javed, Salim, Marinković, Saša P., Rösner, Sascha, Pekarsky, Sasha, Kapila, Shiv R., Marin, Simeon, Krejčí, Šimon, Giokas, Sinos, Tumanyan, Siranush, Turjeman, Sondra, Krüger, Sonja C., Ewing, Steven R., Stoychev, Stoycho, Nikolov, Stoyan C., Qaneer, Tareq E., Spatz, Theresa, Hadjikyriakou, Thomas G., Mueller, Thomas, Katzner, Todd E., Aarvak, Tomas, Veselovský, Tomáš, Nygård, Torgeir, Mellone, Ugo, Väli, Ülo, Sellis, Urmas, Urios, Vicente, Nemček, Vladimír, Arkumarev, Volen, Getz, Wayne M., Fiedler, Wolfgang, Van den Bossche, Willem, Lehnardt, Yael, Jones, Victoria R., Universidad de Alicante. Departamento de Ciencias Ambientales y Recursos Naturales, Universidad de Alicante. Departamento de Didáctica General y Didácticas Específicas, Universidad de Alicante. Instituto Universitario de Física Aplicada a las Ciencias y las Tecnologías, Serratosa, Juan, Oppel, Steffen, Rotics, Shay, Santangeli, Andrea, Butchart, Stuart H.M., Cano-Alonso, Luis S., Tellería Jorge, José Luis, Kemp, Ryno, Nicholas, Aaron, Kalvāns, Aigars, Galarza, Aitor, Franco, Aldina M.A., Andreotti, Alessandro, Kirschel, Alexander N.G., Ngari, Alex, Soutullo, Alvaro, Bermejo, Ana, Botha, Andre J., Ferri, Andrea, Evangelidis, Angelos, Cenerini, Anna, Stamenov, Anton, Hernández-Matías, Antonio, Aradis, Arianna, Grozdanov, Atanas P., Rodríguez, Beneharo, Sekercioğlu, Cağan H., Cerecedo-Iglesias, Catuxa, Kassara, Christina, Barboutis, Christos, Bracebridge, Claire, García Ripollés, Clara, Kendall, Corinne J., Denac, Damijan, Schabo, Dana G., Barber, David R., Popov, Dimitar V., Dobrev, Dobromir D., Mallia, Egidio, Kmetova-Biro, Elena, Álvarez, Ernesto, Buechley, Evan R., Bragin, Evgeny A., Cordischi, Fabrizio, Zengeya, Fadzai M., Monti, Flavio, Mougeot, François, Tate, Gareth, Stoyanov, Georgi, Dell’Omo, Giacomo, Lucia, Giuseppe, Gradev, Gradimir, Ceccolini, Guido, Friedemann, Guilad, Bauer, Hans-Günther, Kolberg, Holger, Peshev, Hristo, Catry, Inês, Øien, Ingar J., Carbonell Alanís, Isidoro, Literák, Ivan, Pokrovsky, Ivan, Ojaste, Ivar, Østnes, Jan E., Puente, Javier de la, Real, Joan, Guilherme, João L., González, José C., Fernández-García, José M., Gil, Juan Antonio, Terraube, Julien, Poprach, Karel, Aghababyan, Karen, Klein, Katharina, Bildstein, Keith L., Wolter, Kerri, Janssens, Kjell, Kittelberger, Kyle D., Thompson, Lindy J., AlJahdhami, Mansoor H., Galán, Manuel, Tobolka, Marcin, Posillico, Mario, Cipollone, Mario, Gschweng, Marion, Strazds, Māris, Boorman, Mark, Zvidzai, Mark, Acácio, Marta, Romero, Marta, Wikelski, Martin, Schmidt, Matthias, Sarà, Maurizio, McGrady, Michael J., Dagys, Mindaugas, Mackenzie, Monique L., Al Taq, Muna, Mgumba, Msafiri P., Virani, Munir Z., Kassinis, Nicolaos I., Borgianni, Nicolò, Thie, Nikki, Tsiopelas, Nikos, Anglister, Nili, Farwig, Nina, Sapir, Nir, Kleven, Oddmund, Krone, Oliver, Duriez, Olivier, Spiegel, Orr, Al Nouri, Osama, López-López, Pascual, Byholm, Patrik, Kamath, Pauline L., Mirski, Paweł, Palatitz, Peter, Serroni, Pietro, Raab, Rainer, Buij, Ralph, Žydelis, Ramūnas, Nathan, Ran, Bowie, Rauri C.K., Tsiakiris, Rigas, Hatfield, Richard Stratton, Harel, Roi, Kroglund, Rolf T., Efrat, Ron, Limiñana, Rubén, Javed, Salim, Marinković, Saša P., Rösner, Sascha, Pekarsky, Sasha, Kapila, Shiv R., Marin, Simeon, Krejčí, Šimon, Giokas, Sinos, Tumanyan, Siranush, Turjeman, Sondra, Krüger, Sonja C., Ewing, Steven R., Stoychev, Stoycho, Nikolov, Stoyan C., Qaneer, Tareq E., Spatz, Theresa, Hadjikyriakou, Thomas G., Mueller, Thomas, Katzner, Todd E., Aarvak, Tomas, Veselovský, Tomáš, Nygård, Torgeir, Mellone, Ugo, Väli, Ülo, Sellis, Urmas, Urios, Vicente, Nemček, Vladimír, Arkumarev, Volen, Getz, Wayne M., Fiedler, Wolfgang, Van den Bossche, Willem, Lehnardt, Yael, and Jones, Victoria R.

Abstract

Human-induced direct mortality affects huge numbers of birds each year, threatening hundreds of species worldwide. Tracking technologies can be an important tool to investigate temporal and spatial patterns of bird mortality as well as their drivers. We compiled 1704 mortality records from tracking studies across the African-Eurasian flyway for 45 species, including raptors, storks, and cranes, covering the period from 2003 to 2021. Our results show a higher frequency of human-induced causes of mortality than natural causes across taxonomic groups, geographical areas, and age classes. Moreover, we found that the frequency of human-induced mortality remained stable over the study period. From the human-induced mortality events with a known cause (n = 637), three main causes were identified: electrocution (40.5 %), illegal killing (21.7 %), and poisoning (16.3 %). Additionally, combined energy infrastructure-related mortality (i.e., electrocution, power line collision, and wind-farm collision) represented 49 % of all human-induced mortality events. Using a random forest model, the main predictors of human-induced mortality were found to be taxonomic group, geographic location (latitude and longitude), and human footprint index value at the location of mortality. Despite conservation efforts, human drivers of bird mortality in the African-Eurasian flyway do not appear to have declined over the last 15 years for the studied group of species. Results suggest that stronger conservation actions to address these threats across the flyway can reduce their impacts on species. In particular, projected future development of energy infrastructure is a representative example where application of planning, operation, and mitigation measures can enhance bird conservation.

Published
2024

13. Pregnancy reduces concurrent pup care behaviour in meerkats, generating differences between dominant and subordinate females

Author

Rotics, Shay; https://orcid.org/0000-0002-3858-1811, Groenewoud, Frank; https://orcid.org/0000-0002-5490-086X, Manser, Marta, Clutton‐Brock, Tim, Rotics, Shay; https://orcid.org/0000-0002-3858-1811, Groenewoud, Frank; https://orcid.org/0000-0002-5490-086X, Manser, Marta, and Clutton‐Brock, Tim

Abstract

In some mammals, and particularly in cooperative breeding ones, successive bouts of reproduction can overlap so that a female is often pregnant while still nurturing dependent young from her previous litter. Such an overlap requires females to divide their energetic budget between two reproductive activities, and pregnancy costs would consequently be expected to reduce investment in concurrent offspring care. However, explicit evidence for such reductions is scarce, and the potential effects they may have on work division in cooperative breeders have not been explored. Using 25 years of data on reproduction and cooperative behaviour in wild Kalahari meerkats, supplemented with field experiments, we investigated whether pregnancy reduces contributions to cooperative pup care behaviours, including babysitting, provisioning and raised guarding. We also explored whether pregnancy, which is more frequent in dominants than subordinates, could account for the reduced contributions of dominants to the cooperative pup care behaviours. We found that pregnancy, particularly at late stages of gestation, reduces contributions to cooperative pup care; that these reductions are eliminated when the food available to pregnant females is experimentally supplemented; and that pregnancy effects accounted for differences between dominants and subordinates in two of the three cooperative behaviours examined (pup provisioning and raised guarding but not babysitting). By linking pregnancy costs with reductions in concurrent pup care, our findings illuminate a trade‐off between investment in successive, overlapping bouts of reproduction. They also suggest that some of the differences in cooperative behaviour between dominant and subordinate females in cooperative breeding mammals can be a direct consequence of differences in their breeding frequency.

Published
2023

15. Correcting a bias in the computation of behavioural time budgets that are based on supervised learning

Author

Resheff, Yehezkel S, Bensch, Hanna M, Zöttl, Markus, Rotics, Shay, Resheff, Yehezkel S [0000-0001-7863-7632], Bensch, Hanna M [0000-0002-8449-9843], Rotics, Shay [0000-0002-3858-1811], Apollo - University of Cambridge Repository, and Apollo-University Of Cambridge Repository

Subjects
Behavioural ecology, body acceleration, Ecological Modeling, biotelemetry, animal behaviour, RESEARCH ARTICLES, Movement ecology, RESEARCH ARTICLE, 3109 Zoology, machine learning, biologging, FOS: Biological sciences, behavioural time budget, Zoology, Ecology, Evolution, Behavior and Systematics, 31 Biological Sciences
Abstract

This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Wiley., 1. Supervised learning of behavioral modes from body-acceleration data has become a widely used research tool in Behavioral Ecology over the past decade. One of the primary usages of this tool is to estimate behavioral time budgets from the distribution of behaviors as predicted by the model. These serve as the key parameters to test predictions about the variation in animal behavior. In this paper we show that the widespread computation of behavioral time budgets is biased, due to ignoring the classification model confusion probabilities. 2. Next, we introduce the confusion matrix correction for time budgets - a simple correction method for adjusting the computed time budgets based on the model's confusion matrix. 3. Finally, we show that the proposed correction is able to eliminate the bias, both theoretically and empirically in a series of data simulations on body acceleration data of a fossorial rodent species (Damaraland mole-rat, Fukomys damarensis). 4. Our paper provides a simple implementation of the confusion matrix correction for time budgets, and we encourage researchers to use it to improve accuracy of behavioral time budget calculations.

Published
2022

18. Correcting a bias in the computation of behavioural time budgets that are based on supervised learning

Author

Resheff, Yehezkel S., Bensch, Hanna, Zöttl, Markus, Rotics, Shay, Resheff, Yehezkel S., Bensch, Hanna, Zöttl, Markus, and Rotics, Shay

Abstract

Supervised learning of behavioural modes from body acceleration data has become a widely used research tool in Behavioural Ecology over the past decade. One of the primary usages of this tool is to estimate behavioural time budgets from the distribution of behaviours as predicted by the model. These serve as the key parameters to test predictions about the variation in animal behaviour. In this paper we show that the widespread computation of behavioural time budgets is biased, due to ignoring the classification model confusion probabilities. Next, we introduce the confusion matrix correction for time budgets-a simple correction method for adjusting the computed time budgets based on the model's confusion matrix. Finally, we show that the proposed correction is able to eliminate the bias, both theoretically and empirically in a series of data simulations on body acceleration data of a fossorial rodent species (Damaraland mole-rat Fukomys damarensis). Our paper provides a simple implementation of the confusion matrix correction for time budgets, and we encourage researchers to use it to improve accuracy of behavioural time budget calculations.

Published
2022
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21. Time series enable the characterization of small-scale vegetation dynamics that influence fine-scale animal behavior : an example from white storks' foraging behavior

Author

Standfuß, Ines, Geiß, Christian, Nathan, Ran, Rotics, Shay, Scacco, Martina, Kerr, Grégoire Henry Gérard, and Taubenböck, Hannes

Subjects
vegetation phenology, Agricultural practices, NDVI, ddc:570, GPS-telemetry, white stork, habitat selection, habitat use, time series, Agricultural practices, GPS-telemetry, habitat selection, habitat use, NDVI, time series, vegetation phenology, white stork
Abstract

Agricultural activities and vegetation growth cause rapid small-scale vegetation changes which dynamically alter habitat suitability. Time series enable to track down such variations of vegetation structure and are promising to examine their impact on animals' life. Nevertheless, their potential to characterize vegetation dynamics in ways pertinent to animals' fine-scale habitat use has not been adequately explored and ecologically meaningful proxies are lacking. To address this gap, we exemplary investigated foraging activities of breeding white storks in an agricultural landscape. Reflecting on the understanding that storks require short vegetation to access prey, we examined if good foraging conditions – early growth and post-harvest/mowing periods – are detectable using the points between local minima/maxima in NDVI profiles (half-maximum). We processed 1 year of Landsat imagery to identify half-maximum periods (HM: good prey access) and non-half-maximum periods (non-HM: poor prey access) on field-scale in croplands and grasslands. Additionally, we mapped used/unused fields and retrieved foraging duration/daily visitation rates from GPS tracks of the storks. We then explored habitat use, compared habitat use with habitat availability and tested temporal predictors distinguishing between HM/non-HM in habitat selection models. Examining habitat use, storks revisited croplands and grasslands significantly more often during HM than during non-HM, while foraging duration was only prolonged in croplands during HM. However, comparing habitat use with habitat availability, we observed that storks used croplands and grasslands in significantly higher proportions during HM than during non-HM. Additionally, we found that temporal information affected storks' habitat selection and improved model performance. Our findings emphasize that the half-maximum proxy enables to coarsely distinguish temporal resource variations in storks' foraging habitats, highlighting the potential of time series for characterizing behaviorally-relevant vegetation dynamics. Such information helps to create more species-centered landscape scenarios in habitat models, allowing to unravel effects of small-scale environmental changes on wildlife to ultimately guide conservation and management. published

Published
2022

26. Estimating nest‐switching in free‐ranging wild birds: an assessment of the most common methodologies, illustrated in the White Stork ( Ciconia ciconia )

Author

Turjeman, Sondra, primary, Eggers, Ute, additional, Rotics, Shay, additional, Fiedler, Wolfgang, additional, Centeno‐Cuadros, Alejandro, additional, Kaatz, Michael, additional, Zurell, Damaris, additional, Jeltsch, Florian, additional, Wikelski, Martin, additional, and Nathan, Ran, additional

Published
2021
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29. SM1: Seasonal niche overlap; SM2: Seasonal niche tracking; SM3: Variability estimation for seasonal niche overlap and niche tracking from Seasonal niche tracking of climate emerges at the population level in a migratory bird

Author

Fandos, Guillermo, Rotics, Shay, Sapir, Nir, Fiedler, Wolfgang, Kaatz, Michael, Wikelski, Martin, Nathan, Ran, and Zurell, Damaris

Abstract

Summary statistics for the seasonal niche overlap values with all environmental variables.;Figure and summary statistics for the seasonal niche tracking values with all environmental variables.;Tabel describing the posterior distribution estimates (mean and 95% confidence intervals) for the variability estimation result from the mixed models.

Published
2020
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31. Home Range Size and Resource Use of Breeding and Non-breeding White Storks Along a Land Use Gradient

Author

Zurell, Damaris, von Wehrden, Henrik, Rotics, Shay, Kaatz, Michael, Groß, Helge, Schlag, Lena, Schäfer, Merlin, Sapir, Nir, Turjeman, Sondra, Wikelski, Martin, Nathan, Ran, and Jeltsch, Florian

Subjects
Ecology, Ciconia ciconia, biotelemetry, Didactics of sciences education, resource selection, 900 Geschichte und Geografie, home range selection, 3D-acceleration sensor, Biology, Institut für Biochemie und Biologie, Ecology, Evolution, Behavior and Systematics, ddc:900, Transdisciplinary studies
Abstract

Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013–2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.

Published
2018
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34. Extra-pair paternity in the socially monogamous white stork (Ciconia ciconia) is fairly common and independent of local density

Author

Feldman Turjeman, Sondra, Centeno-Cuadros, A., Eggers, Ute, Rotics, Shay, Blas, Julio, Fiedler, Wolfgang, Kaatz, Michael, Jeltsch, Florian, Wikelski, Martin, Nathan, Ran, Feldman Turjeman, Sondra, Centeno-Cuadros, A., Eggers, Ute, Rotics, Shay, Blas, Julio, Fiedler, Wolfgang, Kaatz, Michael, Jeltsch, Florian, Wikelski, Martin, and Nathan, Ran

Abstract

Although many birds are socially monogamous, most (>75%) studied species are not strictly genetically monogamous, especially under high breeding density. We used molecular tools to reevaluate the reproductive strategy of the socially monogamous white stork (Ciconia ciconia) and examined local density effects. DNA samples of nestlings (Germany, Spain) were genotyped and assigned relationships using a two-program maximum likelihood classification. Relationships were successfully classified in 79.2% of German (n = 120) and 84.8% of Spanish (n = 59) nests. For each population respectively, 76.8% (n = 73) and 66.0% (n = 33) of nests contained only full-siblings, 10.5% (n = 10) and 18.0% (n = 9) had half-siblings (at least one nestling with a different parent), 3.2% (n = 3) and 10.0% (n = 5) had unrelated nestlings (at least two nestlings, each with different parents), and 9.5% (n = 9) and 6.0% (n = 3) had “not full-siblings” (could not differentiate between latter two cases). These deviations from strict monogamy place the white stork in the 59th percentile for extra-pair paternity among studied bird species. Although high breeding density generally increases extra-pair paternity, we found no significant association with this species’ mating strategies. Thus although genetic monogamy is indeed prominent in the white stork, extra-pair paternity is fairly common compared to other bird species and cannot be explained by breeding density

Published
2016

36. Costs of migratory decisions: A comparison across eight white stork populations

Author

Flack, Andrea, primary, Fiedler, Wolfgang, additional, Blas, Julio, additional, Pokrovsky, Ivan, additional, Kaatz, Michael, additional, Mitropolsky, Maxim, additional, Aghababyan, Karen, additional, Fakriadis, Ioannis, additional, Makrigianni, Eleni, additional, Jerzak, Leszek, additional, Azafzaf, Hichem, additional, Feltrup-Azafzaf, Claudia, additional, Rotics, Shay, additional, Mokotjomela, Thabiso M., additional, Nathan, Ran, additional, and Wikelski, Martin, additional

Published
2016
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42. Light Masking in the Field: An Experiment with Nocturnal and Diurnal Spiny Mice Under Semi-natural Field Conditions.

Author

Rotics, Shay, Dayan, Tamar, Levy, Ofir, and Kronfeld-Schor, Noga

Subjects
*PHYSIOLOGICAL effects of light, *BODY temperature, *BIOLOGICAL adaptation, *ACOMYS, *RADIO transmitters & transmission, *LABORATORY mice
Abstract

Light masking has been studied almost exclusively in the laboratory. The authors populated four field enclosures with locally coexisting nocturnal Acomys cahirinus and diurnal A. russatus, and monitored their body temperatures (Tb) using implanted temperature-sensitive radio transmitters. A 3-h light pulse was initiated at the beginning of two consecutive nights; preceding nights were controls. A. cahirinus Tb and calculated activity levels decreased significantly during the light pulse, demonstrating a negative light masking response (light effect on Tb: −0.32°C ± 0.15°C; average calculated activity records during the light pulse: 7 ± 1.53, control: 9.8 ± 1.62). Diurnal A. russatus did not respond to the light pulse. We conclude that light masking is not an artifact of laboratory conditions but represents a natural adaptive response in free-living populations. (Author correspondence: Shayroti@post.tau.ac.il) [ABSTRACT FROM AUTHOR]

Published
2011
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