@article{DeAngelisTatischeffGrenieretal.2018,
  author    = {De Angelis, A. and Tatischeff, V. and Grenier, I. A. and McEnery, J. and Mallamaci, Manuela and Tavani, M. and Oberlack, U. and Hanlon, L. and Walter, R. and Argan, A. and Von Ballmoos, P. and Bulgarelli, A. and Bykov, A. and Hernanz, M. and Kanbach, G. and Kuvvetli, I. and Pearce, M. and Zdziarski, A. and Conrad, J. and Ghisellini, G. and Harding, A. and Isern, J. and Leising, M. and Longo, F. and Madejski, G. and Martinez, M. and Mazziotta, Mario Nicola and Paredes, J. M. and Pohl, Martin and Rando, R. and Razzano, M. and Aboudan, A. and Ackermann, M. and Addazi, A. and Ajello, M. and Albertus, C. and Alvarez, J. M. and Ambrosi, G. and Anton, S. and Antonelli, L. A. and Babic, A. and Baibussinov, B. and Balbom, M. and Baldini, L. and Balman, S. and Bambi, C. and Barres de Almeida, U. and Barrio, J. A. and Bartels, R. and Bastieri, D. and Bednarek, W. and Bernard, D. and Bernardini, E. and Bernasconi, T. and Bertucci, B. and Biland, A. and Bissaldi, E. and Boettcher, M. and Bonvicini, V. and Bosch-Ramon, V. and Bottacini, E. and Bozhilov, V. and Bretz, T. and Branchesi, M. and Brdar, V. and Bringmann, T. and Brogna, A. and Jorgensen, C. Budtz and Busetto, G. and Buson, S. and Busso, M. and Caccianiga, A. and Camera, S. and Campana, R. and Caraveo, P. and Cardillo, M. and Carlson, P. and Celestin, S. and Cermeno, M. and Chen, A. and Cheung, C. C. and Churazov, E. and Ciprini, S. and Coc, A. and Colafrancesco, S. and Coleiro, A. and Collmar, W. and Coppi, P. and Curado da Silva, R. and Cutini, S. and De Lotto, B. and de Martino, D. and De Rosa, A. and Del Santo, M. and Delgado, L. and Diehl, R. and Dietrich, S. and Dolgov, A. D. and Dominguez, A. and Prester, D. Dominis and Donnarumma, I. and Dorner, D. and Doro, M. and Dutra, M. and Elsaesser, D. and Fabrizio, M. and Fernandez-Barral, A. and Fioretti, V. and Foffano, L. and Formato, V. and Fornengo, N. and Foschini, L. and Franceschini, A. and Franckowiak, A. and Funk, S. and Fuschino, F. and Gaggero, D. and Galanti, G. and Gargano, F. and Gasparrini, D. and Gehrz, R. and Giammaria, P. and Giglietto, N. and Giommi, P. and Giordano, F. and Giroletti, M. and Ghirlanda, G. and Godinovic, N. and Gouiffes, C. and Grove, J. E. and Hamadache, C. and Hartmann, D. H. and Hayashida, M. and Hryczuk, A. and Jean, P. and Johnson, T. and Jose, J. and Kaufmann, S. and Khelifi, B. and Kiener, J. and Knodlseder, J. and Kolem, M. and Kopp, J. and Kozhuharov, V. and Labanti, C. and Lalkovski, S. and Laurent, P. and Limousin, O. and Linares, M. and Lindfors, E. and Lindner, M. and Liu, J. and Lombardi, S. and Loparco, F. and Lopez-Coto, R. and Lopez Moya, M. and Lott, B. and Lubrano, P. and Malyshev, D. and Mankuzhiyil, N. and Mannheim, K. and Marcha, M. J. and Marciano, A. and Marcote, B. and Mariotti, M. and Marisaldi, M. and McBreen, S. and Mereghetti, S. and Merle, A. and Mignani, R. and Minervini, G. and Moiseev, A. and Morselli, A. and Moura, F. and Nakazawa, K. and Nava, L. and Nieto, D. and Orienti, M. and Orio, M. and Orlando, E. and Orleanski, P. and Paiano, S. and Paoletti, R. and Papitto, A. and Pasquato, M. and Patricelli, B. and Perez-Garcia, M. A. and Persic, M. and Piano, G. and Pichel, A. and Pimenta, M. and Pittori, C. and Porter, T. and Poutanen, J. and Prandini, E. and Prantzos, N. and Produit, N. and Profumo, S. and Queiroz, F. S. and Raino, S. and Raklev, A. and Regis, M. and Reichardt, I. and Rephaeli, Y. and Rico, J. and Rodejohann, W. and Fernandez, G. Rodriguez and Roncadelli, M. and Roso, L. and Rovero, A. and Ruffini, R. and Sala, G. and Sanchez-Conde, M. A. and Santangelo, A. and Parkinson, P. Saz and Sbarrato, T. and Shearer, A. and Shellard, R. and Short, K. and Siegert, T. and Siqueira, C. and Spinelli, P. and Stamerra, A. and Starrfield, S. and Strong, A. and Strumke, I. and Tavecchio, F. and Taverna, R. and Terzic, T. and Thompson, D. J. and Tibolla, O. and Torres, D. F. and Turolla, R. and Ulyanov, A. and Ursi, A. and Vacchi, A. and Van den Abeele, J. and Vankova-Kirilovai, G. and Venter, C. and Verrecchia, F. and Vincent, P. and Wang, X. and Weniger, C. and Wu, X. and Zaharijas, G. and Zampieri, L. and Zane, S. and Zimmer, S. and Zoglauer, A.},
  title     = {Science with e-ASTROGAM A space mission for MeV-GeV gamma-ray astrophysics},
  series = {Journal of High Energy Astrophysics},
  volume    = {19},
  journal   = {Journal of High Energy Astrophysics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  organization    = {e-ASTROGAM Collaboration},
  issn      = {2214-4048},
  doi       = {10.1016/j.jheap.2018.07.001},
  pages     = {1 -- 106},
  year      = {2018},
  language  = {en}
}
@article{BarbosaCoelhoGusmaoetal.2022,
  author    = {Barbosa, Luis Romero A. and Coelho, Victor Hugo R. and Gusmao, Ana Claudia V. L. F. and Fernandes, Lucila A. E. and da Silva, Bernardo B. and Galvao, Carlos de O. and Caicedo, Nelson O. L. and da Paz, Adriano R. and Xuan, Yunqing and Bertrand, Guillaume F. and Melo, Davi de C. D. and Montenegro, Suzana M. G. L. and Oswald, Sascha E. and Almeida, Cristiano das N.},
  title     = {A satellite-based approach to estimating spatially distributed groundwater recharge rates in a tropical wet sedimentary region despite cloudy conditions},
  series = {Journal of hydrology},
  volume    = {607},
  journal   = {Journal of hydrology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-1694},
  doi       = {10.1016/j.jhydrol.2022.127503},
  pages     = {15},
  year      = {2022},
  abstract  = {Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries. This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions. The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations. The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction. This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method. The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9\%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19\% to-22\% of our monthly evaluation. The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.},
  language  = {en}
}
@article{TiegsCostelloIskenetal.2019,
  author    = {Tiegs, Scott D. and Costello, David M. and Isken, Mark W. and Woodward, Guy and McIntyre, Peter B. and Gessner, Mark O. and Chauvet, Eric and Griffiths, Natalie A. and Flecker, Alex S. and Acuna, Vicenc and Albarino, Ricardo and Allen, Daniel C. and Alonso, Cecilia and Andino, Patricio and Arango, Clay and Aroviita, Jukka and Barbosa, Marcus V. M. and Barmuta, Leon A. and Baxter, Colden V. and Bell, Thomas D. C. and Bellinger, Brent and Boyero, Luz and Brown, Lee E. and Bruder, Andreas and Bruesewitz, Denise A. and Burdon, Francis J. and Callisto, Marcos and Canhoto, Cristina and Capps, Krista A. and Castillo, Maria M. and Clapcott, Joanne and Colas, Fanny and Colon-Gaud, Checo and Cornut, Julien and Crespo-Perez, Veronica and Cross, Wyatt F. and Culp, Joseph M. and Danger, Michael and Dangles, Olivier and de Eyto, Elvira and Derry, Alison M. and Diaz Villanueva, Veronica and Douglas, Michael M. and Elosegi, Arturo and Encalada, Andrea C. and Entrekin, Sally and Espinosa, Rodrigo and Ethaiya, Diana and Ferreira, Veronica and Ferriol, Carmen and Flanagan, Kyla M. and Fleituch, Tadeusz and Shah, Jennifer J. Follstad and Frainer, Andre and Friberg, Nikolai and Frost, Paul C. and Garcia, Erica A. and Lago, Liliana Garcia and Garcia Soto, Pavel Ernesto and Ghate, Sudeep and Giling, Darren P. and Gilmer, Alan and Goncalves, Jose Francisco and Gonzales, Rosario Karina and Graca, Manuel A. S. and Grace, Mike and Grossart, Hans-Peter and Guerold, Francois and Gulis, Vlad and Hepp, Luiz U. and Higgins, Scott and Hishi, Takuo and Huddart, Joseph and Hudson, John and Imberger, Samantha and Iniguez-Armijos, Carlos and Iwata, Tomoya and Janetski, David J. and Jennings, Eleanor and Kirkwood, Andrea E. and Koning, Aaron A. and Kosten, Sarian and Kuehn, Kevin A. and Laudon, Hjalmar and Leavitt, Peter R. and Lemes da Silva, Aurea L. and Leroux, Shawn J. and Leroy, Carri J. and Lisi, Peter J. and MacKenzie, Richard and Marcarelli, Amy M. and Masese, Frank O. and Mckie, Brendan G. and Oliveira Medeiros, Adriana and Meissner, Kristian and Milisa, Marko and Mishra, Shailendra and Miyake, Yo and Moerke, Ashley and Mombrikotb, Shorok and Mooney, Rob and Moulton, Tim and Muotka, Timo and Negishi, Junjiro N. and Neres-Lima, Vinicius and Nieminen, Mika L. and Nimptsch, Jorge and Ondruch, Jakub and Paavola, Riku and Pardo, Isabel and Patrick, Christopher J. and Peeters, Edwin T. H. M. and Pozo, Jesus and Pringle, Catherine and Prussian, Aaron and Quenta, Estefania and Quesada, Antonio and Reid, Brian and Richardson, John S. and Rigosi, Anna and Rincon, Jose and Risnoveanu, Geta and Robinson, Christopher T. and Rodriguez-Gallego, Lorena and Royer, Todd V. and Rusak, James A. and Santamans, Anna C. and Selmeczy, Geza B. and Simiyu, Gelas and Skuja, Agnija and Smykla, Jerzy and Sridhar, Kandikere R. and Sponseller, Ryan and Stoler, Aaron and Swan, Christopher M. and Szlag, David and Teixeira-de Mello, Franco and Tonkin, Jonathan D. and Uusheimo, Sari and Veach, Allison M. and Vilbaste, Sirje and Vought, Lena B. M. and Wang, Chiao-Ping and Webster, Jackson R. and Wilson, Paul B. and Woelfl, Stefan and Xenopoulos, Marguerite A. and Yates, Adam G. and Yoshimura, Chihiro and Yule, Catherine M. and Zhang, Yixin X. and Zwart, Jacob A.},
  title     = {Global patterns and drivers of ecosystem functioning in rivers and riparian zones},
  series = {Science Advances},
  volume    = {5},
  journal   = {Science Advances},
  number    = {1},
  publisher = {American Assoc. for the Advancement of Science},
  address   = {Washington},
  issn      = {2375-2548},
  doi       = {10.1126/sciadv.aav0486},
  pages     = {8},
  year      = {2019},
  abstract  = {River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth's biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented "next-generation biomonitoring" by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.},
  language  = {en}
}
@article{DentonOfmanShpritsetal.2019,
  author    = {Denton, Richard E. and Ofman, L. and Shprits, Yuri Y. and Bortnik, J. and Millan, R. M. and Rodger, C. J. and da Silva, C. L. and Rogers, B. N. and Hudson, M. K. and Liu, K. and Min, K. and Glocer, A. and Komar, C.},
  title     = {Pitch Angle Scattering of Sub-MeV Relativistic Electrons by Electromagnetic Ion Cyclotron Waves},
  series = {Journal of geophysical research : Space physics},
  volume    = {124},
  journal   = {Journal of geophysical research : Space physics},
  number    = {7},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9402},
  doi       = {10.1029/2018JA026384},
  pages     = {5610 -- 5626},
  year      = {2019},
  abstract  = {Electromagnetic ion cyclotron (EMIC) waves have long been considered to be a significant loss mechanism for relativistic electrons. This has most often been attributed to resonant interactions with the highest amplitude waves. But recent observations have suggested that the dominant energy of electrons precipitated to the atmosphere may often be relatively low, less than 1 MeV, whereas the minimum resonant energy of the highest amplitude waves is often greater than 2 MeV. Here we use relativistic electron test particle simulations in the wavefields of a hybrid code simulation of EMIC waves in dipole geometry in order to show that significant pitch angle scattering can occur due to interaction with low-amplitude short-wavelength EMIC waves. In the case we examined, these waves are in the H band (at frequencies above the He+ gyrofrequency), even though the highest amplitude waves were in the He band frequency range (below the He+ gyrofrequency). We also present wave power distributions for 29 EMIC simulations in straight magnetic field line geometry that show that the high wave number portion of the spectrum is in every case mostly due to the H band waves. Though He band waves are often associated with relativistic electron precipitation, it is possible that the He band waves do not directly scatter the sub-megaelectron volts (sub-MeV) electrons, but that the presence of He band waves is associated with high plasma density which lowers the minimum resonant energy so that these electrons can more easily resonate with the H band waves.},
  language  = {en}
}
@article{vanderValkKreinerMollerKooijmanetal.2015,
  author    = {van der Valk, Ralf J. P. and Kreiner-Moller, Eskil and Kooijman, Marjolein N. and Guxens, Monica and Stergiakouli, Evangelia and Saaf, Annika and Bradfield, Jonathan P. and Geller, Frank and Hayes, M. Geoffrey and Cousminer, Diana L. and Koerner, Antje and Thiering, Elisabeth and Curtin, John A. and Myhre, Ronny and Huikari, Ville and Joro, Raimo and Kerkhof, Marjan and Warrington, Nicole M. and Pitkanen, Niina and Ntalla, Ioanna and Horikoshi, Momoko and Veijola, Riitta and Freathy, Rachel M. and Teo, Yik-Ying and Barton, Sheila J. and Evans, David M. and Kemp, John P. and St Pourcain, Beate and Ring, Susan M. and Smith, George Davey and Bergstrom, Anna and Kull, Inger and Hakonarson, Hakon and Mentch, Frank D. and Bisgaard, Hans and Chawes, Bo Lund Krogsgaard and Stokholm, Jakob and Waage, Johannes and Eriksen, Patrick and Sevelsted, Astrid and Melbye, Mads and van Duijn, Cornelia M. and Medina-Gomez, Carolina and Hofman, Albert and de Jongste, Johan C. and Taal, H. Rob and Uitterlinden, Andre G. and Armstrong, Loren L. and Eriksson, Johan and Palotie, Aarno and Bustamante, Mariona and Estivill, Xavier and Gonzalez, Juan R. and Llop, Sabrina and Kiess, Wieland and Mahajan, Anubha and Flexeder, Claudia and Tiesler, Carla M. T. and Murray, Clare S. and Simpson, Angela and Magnus, Per and Sengpiel, Verena and Hartikainen, Anna-Liisa and Keinanen-Kiukaanniemi, Sirkka and Lewin, Alexandra and Alves, Alexessander Da Silva Couto and Blakemore, Alexandra I. F. and Buxton, Jessica L. and Kaakinen, Marika and Rodriguez, Alina and Sebert, Sylvain and Vaarasmaki, Marja and Lakka, Timo and Lindi, Virpi and Gehring, Ulrike and Postma, Dirkje S. and Ang, Wei and Newnham, John P. and Lyytikainen, Leo-Pekka and Pahkala, Katja and Raitakari, Olli T. and Panoutsopoulou, Kalliope and Zeggini, Eleftheria and Boomsma, Dorret I. and Groen-Blokhuis, Maria and Ilonen, Jorma and Franke, Lude and Hirschhorn, Joel N. and Pers, Tune H. and Liang, Liming and Huang, Jinyan and Hocher, Berthold and Knip, Mikael and Saw, Seang-Mei and Holloway, John W. and Melen, Erik and Grant, Struan F. A. and Feenstra, Bjarke and Lowe, William L. and Widen, Elisabeth and Sergeyev, Elena and Grallert, Harald and Custovic, Adnan and Jacobsson, Bo and Jarvelin, Marjo-Riitta and Atalay, Mustafa and Koppelman, Gerard H. and Pennell, Craig E. and Niinikoski, Harri and Dedoussis, George V. and Mccarthy, Mark I. and Frayling, Timothy M. and Sunyer, Jordi and Timpson, Nicholas J. and Rivadeneira, Fernando and Bonnelykke, Klaus and Jaddoe, Vincent W. V.},
  title     = {A novel common variant in DCST2 is associated with length in early life and height in adulthood},
  series = {Human molecular genetics},
  volume    = {24},
  journal   = {Human molecular genetics},
  number    = {4},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  organization    = {Early Genetics Lifecourse, Genetic Invest ANthropometric, Early Growth Genetics EGG},
  issn      = {0964-6906},
  doi       = {10.1093/hmg/ddu510},
  pages     = {1155 -- 1168},
  year      = {2015},
  abstract  = {Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 x 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; beta = 0.046, SE = 0.008, P = 2.46 x 10(-8), explained variance = 0.05\%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 x 10(-4)) and adult height (N = 127 513; P = 1.45 x 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13\% of variance in birth length. The same SNPs explained 2.95\% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.},
  language  = {en}
}
@inproceedings{TatischeffDeAngelisTavanietal.2018,
  author    = {Tatischeff, V. and De Angelis, A. and Tavani, M. and Grenier, I. and Oberlack, U. and Hanlon, L. and Walter, R. and Argan, A. and von Ballmoos, P. and Bulgarelli, A. and Donnarumma, I. and Hernanz, Margarita and Kuvvetli, I. and Mallamaci, M. and Pearce, M. and Zdziarski, A. and Aboudan, A. and Ajello, M. and Ambrosi, G. and Bernard, D. and Bernardini, E. and Bonvicini, V. and Brogna, A. and Branchesi, M. and Budtz-Jorgensen, C. and Bykov, A. and Campana, R. and Cardillo, M. and Ciprini, S. and Coppi, P. and Cumani, P. and da Silva, R. M. Curado and De Martino, D. and Diehl, R. and Doro, M. and Fioretti, V. and Funk, S. and Ghisellini, G. and Giordano, F. and Grove, J. E. and Hamadache, C. and Hartmann, D. H. and Hayashida, M. and Isern, J. and Kanbach, G. and Kiener, J. and Knodlseder, J. and Labanti, C. and Laurent, P. and Leising, M. and Limousin, O. and Longo, F. and Mannheim, K. and Marisaldi, M. and Martinez, M. and Mazziotta, M. N. and McEnery, J. E. and Mereghetti, S. and Minervini, G. and Moiseev, A. and Morselli, A. and Nakazawa, K. and Orleanski, P. and Paredes, J. M. and Patricelli, B. and Peyre, J. and Piano, G. and Pohl, Martin and Rando, R. and Roncadelli, M. and Tavecchio, F. and Thompson, D. J. and Turolla, R. and Ulyanov, A. and Vacchi, A. and Wu, X. and Zoglauer, A.},
  title     = {The e-ASTROGAM gamma-ray space observatory for the multimessenger astronomy of the 2030s},
  series = {Space Telescopes and Instrumentation 2018: Ultraviolet to Gamma Ray},
  volume    = {10699},
  booktitle = {Space Telescopes and Instrumentation 2018: Ultraviolet to Gamma Ray},
  editor    = {DenHerder, JWA Nikzad},
  publisher = {SPIE - The International Society for Optical Engineering},
  address   = {Bellingham},
  isbn      = {978-1-5106-1952-4},
  issn      = {0277-786X},
  doi       = {10.1117/12.2315151},
  pages     = {15},
  year      = {2018},
  abstract  = {e-ASTROGAM is a concept for a breakthrough observatory space mission carrying a gamma-ray telescope dedicated to the study of the non-thermal Universe in the photon energy range from 0.15 MeV to 3 GeV. The lower energy limit can be pushed down to energies as low as 30 keV for gamma-ray burst detection with the calorimeter. The mission is based on an advanced space-proven detector technology, with unprecedented sensitivity, angular and energy resolution, combined with remarkable polarimetric capability. Thanks to its performance in the MeV-GeV domain, substantially improving its predecessors, e-ASTROGAM will open a new window on the non-thermal Universe, making pioneering observations of the most powerful Galactic and extragalactic sources, elucidating the nature of their relativistic outflows and their effects on the surroundings. With a line sensitivity in the MeV energy range one to two orders of magnitude better than previous and current generation instruments, e-ASTROGAM will determine the origin of key isotopes fundamental for the understanding of supernova explosion and the chemical evolution of our Galaxy. The mission will be a major player of the multiwavelength, multimessenger time-domain astronomy of the 2030s, and provide unique data of significant interest to a broad astronomical community, complementary to powerful observatories such as LISA, LIGO, Virgo, KAGRA, the Einstein Telescope and the Cosmic Explorer, IceCube-Gen2 and KM3NeT, SKA, ALMA, JWST, E-ELT, LSST, Athena, and the Cherenkov Telescope Array.},
  language  = {en}
}
@article{NoonanTuckerFlemingetal.2018,
  author    = {Noonan, Michael J. and Tucker, Marlee A. and Fleming, Christen H. and Akre, Thomas S. and Alberts, Susan C. and Ali, Abdullahi H. and Altmann, Jeanne and Antunes, Pamela Castro and Belant, Jerrold L. and Beyer, Dean and Blaum, Niels and Boehning-Gaese, Katrin and Cullen Jr, Laury and de Paula, Rogerio Cunha and Dekker, Jasja and Drescher-Lehman, Jonathan and Farwig, Nina and Fichtel, Claudia and Fischer, Christina and Ford, Adam T. and Goheen, Jacob R. and Janssen, Rene and Jeltsch, Florian and Kauffman, Matthew and Kappeler, Peter M. and Koch, Flavia and LaPoint, Scott and Markham, A. Catherine and Medici, Emilia Patricia and Morato, Ronaldo G. and Nathan, Ran and Oliveira-Santos, Luiz Gustavo R. and Olson, Kirk A. and Patterson, Bruce D. and Paviolo, Agustin and Ramalho, Emiliano Estero and Rosner, Sascha and Schabo, Dana G. and Selva, Nuria and Sergiel, Agnieszka and da Silva, Marina Xavier and Spiegel, Orr and Thompson, Peter and Ullmann, Wiebke and Zieba, Filip and Zwijacz-Kozica, Tomasz and Fagan, William F. and Mueller, Thomas and Calabrese, Justin M.},
  title     = {A comprehensive analysis of autocorrelation and bias in home range estimation},
  series = {Ecological monographs : a publication of the Ecological Society of America.},
  volume    = {89},
  journal   = {Ecological monographs : a publication of the Ecological Society of America.},
  number    = {2},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0012-9615},
  doi       = {10.1002/ecm.1344},
  pages     = {21},
  year      = {2018},
  abstract  = {Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95\% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95\% (or 50\%) estimates was 95.3\% (or 50.1\%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72\% of the 369 empirical data sets had >1,000 total observations, only 4\% had an N̂ area >1,000, where 30\% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.},
  language  = {en}
}