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556 results on '"Zeidler, J"'

4. Performance of polarization diversity in correlated Nakagami-m fading channels

Author

Jootar, J, Diouris, J F, and Zeidler, J R

Subjects
fading, maximal radio combining (MRC), polarization diversity, power control, transmit diversity
Abstract

This paper analyzes the performance of systems with dual-polarized antennas in correlated Nakagami-m fading channels as a function of envelope correlation and cross-polarization discrimination by means of the characteristic function of the instantaneous post-maximal ratio combining (MRC) signal-to-noise ratio (SNR). Systems of interest include systems with receive polarization diversity and systems with transmit and receive polarization diversity employing Alamouti space-time code. The expressions for the average symbol error probability as a function of SNR assuming no power control, and the expressions for the average required transmit power to achieve the constant desired post-MRC SNR assuming perfect fast power control, are derived. Finally, a comparison between analytical and simulation results is used to validate the analysis.

Published
2006

5. CINR difference analysis of optimal combining versus maximal ratio combining

Author

Burke, J P, Zeidler, J R, and Rao, B D

Subjects
antenna arrays, diversity methods, fading channels, interference suppression
Abstract

The statistical gain differences between two common spatial combining algorithms: optimum combining (OC) and maximal ratio combining (MRC) are analyzed using a gain ratio method. Using the receive carrier-to-interference plus noise ratio (CINR), the gain ratio CINROC/CINRMRC is evaluated in a flat Rayeligh fading communications system with multiple interferers. Exact analytical solutions are derived for the probability density function (PDF) and the average gain ratio with one interferer. When more than one interferer is present, the PDF of the gain ratio is illustrated using Monte Carlo simulations and its mean value is shown in basic integral form. An upper bound to the gain ratio is derived providing a simple means to determine when OC will exhibit significant gains over MRC.

Published
2005

6. Modeling dynamic channel-allocation algorithms in multi-BS TDD wireless networks with Internet-based traffic

Author

Cooper, W, Zeidler, J R, and Bitmead, R R

Subjects
dynamic channel allocation, Internet traffic, time division duplex (TDD), WiFi, wireless networks
Abstract

Future time-division-duplex (TDD) systems operating over small wireless networks will utilize intelligent base station (BS)-coordinated dynamic channel-allocation algorithms in order to support high-bandwidth asymmetric traffic in adjacent cells. In this paper, we use extensive measurements of wireless Internet traffic from a large 802.11b network to create two random traffic models. One model, called “binomial,” is memoryless and the other, called “dynamic,” is based on an event-driven Markov state model with bidirectional flows and deterministic residence times. We then develop a two-BS two-zone wireless TDD interference model that describes the spatial features of interference between cochannel mobile stations (MSs) in adjacent BSs. This is a simplified precursor to more sophisticated models for multiple BSs and/or multisector BSs. We present a set of candidate TDD channel-allocation algorithms, which vary in their level of time-slot coordination and intelligent allocation between BSs. Lastly, we combine the three components (i.e., traffic models, interference models, and channel-allocation algorithms) to demonstrate the capacity for evaluating dynamic channel-allocation algorithms in realistic interference and Internet traffic scenarios. The results show that, for active MSs, the dynamic traffic model has a higher number of packet requests per time frame than the binomial traffic model, given the same mobile activity factor. Additionally, fixed channel-allocation algorithms generally perform much worse than pseudorandom and intelligent BS-coordinated algorithms, especially for asymmetric BSs. The pseudorandom algorithm performs well at low traffic, but suffers from severe interference blocking at high traffic. The intelligent BS-coordinated algorithm performs best, as it avoids MS-to-MS interference blocking from nearby users in adjacent cells and maximizes the overall throughput by attempting to allocate up- and downlink packet requests in corresponding time slots matched to the incoming uplink–downlink traffic demand for each time frame.

Published
2004

7. Tracking highly maneuverable targets with unknown behavior

Author

Schell, C, Linder, S P, and Zeidler, J R

Subjects
probabilistic data association, state estimation, tracking
Abstract

Tracking of highly maneuvering targets with unknown behavior is a difficult problem in sequential state estimation. The performance of predictive-model-based Bayesian state estimators deteriorates quickly when their models are no longer accurate or their process not. se is large. A data-driven approach to tracking, the segmenting track identifier (STI), is presented as an algorithm that operates well in environments where the measurement system is well understood but target motion is either or both highly unpredictable or poorly characterized. The STI achieves improved state estimates by the least-squares fitting of a motion model to a segment of data that has been partitioned from the total track such that it represents a single maneuver. Real-world STI tracking performance is demonstrated using sonar data collected from free-swimming fish, where the STI is shown to be effective at tracking highly maneuvering targets while relatively insensitive to its tuning parameters. Additionally, an extension of the STI to. allow its use in the most common multiple target and cluttered environment data association frameworks is presented, and an STI-based joint probabilistic data association filter (STIJPDAF) is derived as a specific example. The STIJPDAF is shown by simulation to be effective at tracking a single fish in clutter and through empirical results from video data to be effective at simultaneously tracking multiple free-swimming fish.

Published
2004

8. A Simple Gradient Sign Algorithm for Transmit Antenna Weight Adaptation with Feedback

Author

Banister, B C and Zeidler, J R

Subjects
Adaptive beamforming, antenna array, stochastic gradient algorithms, transmit beamforming
Abstract

In this paper, a simple algorithm for adaptation of the complex baseband weights of a transmit antenna array using feedback from the receiver is proposed and analyzed. The system utilizes stochastic gradient adaptation to maximize the power delivered to the receiver for a constrained transmission power, which provides both fading diversity and beam steering gain. Dual perturbed transmission weight vectors are time multiplexed onto the pilot signal, and the receiver generates feedback selecting the perturbed weight vector which delivers greater power. This feedback is used to provide weight adaptation at the transmitter, and this adaptation is shown to be an update by a coarse estimate of the gradient of the delivered power. The performance of the algorithm is analyzed in terms of convergence and tracking of an AR1 fading channel, with simulations confirming the analysis. Bit error rate (BER) simulations in a dynamic fading channel show that the algorithm outperforms previously proposed vector selection feedback, and in slower fading, the algorithm substantially outperforms diversity space time coding.

Published
2003

9. Feedback assisted transmission subspace tracking for MIMO systems

Author

Banister, B C and Zeidler, J R

Subjects
adaptive arrays, gradient methods, multiple-input-multiple-output (MINO) systems, transmitting antennas
Abstract

This paper describes a feedback assisted stochastic gradient algorithm for transmission tracking of the dominant channel subspaces for multiple-input-multiple-output (MIMO) communications systems. Subspace tracking is introduced as a means of tracking multiple transmission weights, being the MIMO generalization of beam steering in the familiar multiple-input-single-output case. The subspace solution approximates that of water filling (WF) in some cases, without the complete rate/power allocation required by WE The gain of subspace tracking in low rank systems is demonstrated, particularly, in the case where the number of transmit antennas exceeds the number of receive antennas. Simulations of ergodic capacity show the utility of both subspace tracking in general and of the specific adaptation algorithm, and simulations of frame-error rates show the utility in a specific coding example.

Published
2003

10. Error probability performance for W-CDMA systems with multiple transmit and receive antennas in correlated Nakagami fading channels

Author

Luo, J X, Zeidler, J R, and Proakis, J G

Subjects
convolutional coding, correlated Nakagami fading, multiple-input-multiple-output (MIMO) systems, pairwise error probability, space-path diversity, two-dimensional (2-D) RAKE receiver
Abstract

The bit error rate (BER) performance of a two-dimensional (2-D) RAKE receiver, in combination with transmit diversity on the downlink of a wide-band CDMA (W-CDMA) system, is presented. The analyses assume correlated fading between receive antenna array elements, and an arbitrary number of independent but nonidentical resolvable multipaths combined by the RAKE receiver in the general Nakagami-m fading channel framework. The impact of the array configuration (e.g., the number of transmit antennas and receive antennas, the antenna element separation) and the operating environment parameters (such as the fading severity, angular spread and path delay profile) on the overall space-path diversity gain can be directly evaluated. In addition, the exact pairwise error probability of a convolutional coded system is obtained, and the coding gain of a space-path diversity receiver is quantified.

Published
2002

23. Rheuma-VOR: Verbesserung der rheumatologischen Versorgungsqualität durch koordinierte Kooperation

Author

Schwarting, A, Dreher, M, Assmann, G, Witte, T, Hoeper, K, Triantafyllias, K, Murawski, N, Karberg, K, Proft, F, Poddubnyy, D, Zeidler, J, Binder, H, Grodd, M, Graf, E, Callhoff, J, and Schmidt, RE

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Einleitung: Rheuma-VOR ist die größte Versorgungsforschungsstudie in Deutschland, mit dem Ziel, in vier Bundesländern drei entzündlich-rheumatische Erkrankungsbilder, die Rheumatoide Arthritis (RA), die Psoriasis Arthritis (PsA) und die axiale Spondyolarthritis (axSpA) möglichst[zum vollständigen Text gelangen Sie über die oben angegebene URL], Deutscher Rheumatologiekongress 2021, 49. Kongress der Deutschen Gesellschaft für Rheumatologie (DGRh), 35. Jahrestagung der Deutschen Gesellschaft für Orthopädische Rheumatologie (DGORh), Wissenschaftliche Herbsttagung der Gesellschaft für Kinder- und Jugendrheumatologie (GKJR)

Published
2021
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26. Solar photovoltaic module detection using laboratory and airborne imaging spectroscopy data

Author

Ji, C., Bachmann, M., Esch, T., Feilhauer, Hannes, Heiden, U., Heldens, W., Hueni, A., Lakes, T., Metz-Marconcini, A., Schroedter-Homscheidt, M., Weyand, S., Zeidler, J., Ji, C., Bachmann, M., Esch, T., Feilhauer, Hannes, Heiden, U., Heldens, W., Hueni, A., Lakes, T., Metz-Marconcini, A., Schroedter-Homscheidt, M., Weyand, S., and Zeidler, J.

Abstract

Over the past decades, solar panels have been widely used to harvest solar energy owing to the decreased cost of silicon-based photovoltaic (PV) modules, and therefore it is essential to remotely map and monitor the presence of solar PV modules. Many studies have explored on PV module detection based on color aerial photography and manual photo interpretation. Imaging spectroscopy data are capable of providing detailed spectral information to identify the spectral features of PV, and thus potentially become a promising resource for automated and operational PV detection. However, PV detection with imaging spectroscopy data must cope with the vast spectral diversity of surface materials, which is commonly divided into spectral intra-class variability and inter-class similarity. We have developed an approach to detect PV modules based on their physical absorption and reflection characteristics using airborne imaging spectroscopy data. A large database was implemented for training and validating the approach, including spectra-goniometric measurements of PV modules and other materials, a HyMap image spectral library containing 31 materials with 5627 spectra, and HySpex imaging spectroscopy data sets covering Oldenburg, Germany. By normalizing the widely used Hydrocarbon Index (HI), we solved the intra-class variability caused by different detection angles, and validated it against the spectra-goniometric measurements. Knowing that PV modules are composed of materials with different transparencies, we used a group of spectral indices and investigated their interdependencies for PV detection with implementing the image spectral library. Finally, six well-trained spectral indices were applied to HySpex data acquired in Oldenburg, Germany, yielding an overall PV map. Four subsets were selected for validation and achieved overall accuracies, producer's accuracies and user's accuracies, respectively. This physics-based approach was validated against a large database collecte

Published
2021

29. Delegation und Vernetzung bei chronisch-inflammatorischen Erkrankungen (DELIVER-CARE) – Evaluationskonzept zur Etablierung einer MFA-Sprechstunde

Author

Kutscher, M, Kerkemeyer, L, Amelung, VE, Zeidler, J, Hoeper, J, and Hoeper, K

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund und Stand (inter)nationaler Forschung: Die Delegation von ärztlichen Tätigkeiten an nichtärztliches Personal ist in anderen Ländern (z.B. Skandinavien, England) bereits etabliert. In Deutschland gehört ein strukturierter Einsatz von Medizinischen Fachangestellten[zum vollständigen Text gelangen Sie über die oben angegebene URL], 19. Deutscher Kongress für Versorgungsforschung (DKVF)

Published
2020
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30. Star Clusters Near and Far

Author

Angela Adamo, Peter Zeidler, J. M. Diederik Kruijssen, Mélanie Chevance, Mark Gieles, Daniela Calzetti, Corinne Charbonnel, Hans Zinnecker, Martin G. H. Krause

Published
2020
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33. City-descriptive input data for urban climate models: Model requirements, data sources and challenges

Author

Masson, V., Heldens, W., Bocher, E., Bonhomme, M., Bucher, B., Burmeister, C., de Munck, C., Esch, T., Hidalgo, J., Kanani-Sühring, F., Kwok, Y.-T., Lemonsu, A., Lévy, J.-P., Maronga, B., Pavlik, D., Petit, G., See, L., Schoetter, R., Tornay, N., Votsis, A., Zeidler, J., Masson, V., Heldens, W., Bocher, E., Bonhomme, M., Bucher, B., Burmeister, C., de Munck, C., Esch, T., Hidalgo, J., Kanani-Sühring, F., Kwok, Y.-T., Lemonsu, A., Lévy, J.-P., Maronga, B., Pavlik, D., Petit, G., See, L., Schoetter, R., Tornay, N., Votsis, A., and Zeidler, J.

Abstract

Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed.

Published
2020

39. Rheuma-VOR: Eine Proof-of-Concept-Netzwerkstudie für die Verbesserung der rheumatologischen Versorgungsqualität durch koordinierte Kooperation

Author

Dreher, M, Schmidt, RE, Witte, T, Assmann, G, Hoeper, K, Triantafyllias, K, Zeidler, J, Binder, H, and Schwarting, A

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund: Die Rheumatoide Arthritis (RA), die Psoriasis Arthritis (PsA) und die Spondylarthritis (SpA) zählen zu den häufigsten entzündlich-rheumatischen Erkrankungen. Bei allen drei Erkrankungsbildern scheint sich das „window of opportunity“ [ref:1], [ref:2],[zum vollständigen Text gelangen Sie über die oben angegebene URL], 18. Deutscher Kongress für Versorgungsforschung (DKVF)

Published
2019
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42. Gute Praxis Datenlinkage

Author

March, S, Andrich, S, Drepper, J, Horenkamp-Sonntag, D, Icks, A, Ihle, P, Kieschke, J, Kollhorst, B, Maier, B, Meyer, I, Müller, G, Ohlmeier, C, Peschke, D, Richter, A, Rosenbusch, ML, Scholten, N, Schulz, M, Stallmann, C, Swart, E, Wobbe-Ribinski, S, Wolter, A, Zeidler, J, Hoffmann, F, March, S, Andrich, S, Drepper, J, Horenkamp-Sonntag, D, Icks, A, Ihle, P, Kieschke, J, Kollhorst, B, Maier, B, Meyer, I, Müller, G, Ohlmeier, C, Peschke, D, Richter, A, Rosenbusch, ML, Scholten, N, Schulz, M, Stallmann, C, Swart, E, Wobbe-Ribinski, S, Wolter, A, Zeidler, J, and Hoffmann, F

Published
2019

48. Primary data analysis on the use of antidementia drugs in German patients with Alzheimer’s disease across all severity stages of the disease

Author

Heßmann, P, Dodel, R, Kis, B, Zeidler, J, Klora, M, Reese, JP, and Balzer-Geldsetzer, M

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Background: Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases in the elderly with more than 600.000 patients in Germany. Curative therapies for AD are lacking. Earlier studies showed positive effects of antidementia drugs (ADDs) on the patients’ cognition, the[for full text, please go to the a.m. URL], 16. Deutscher Kongress für Versorgungsforschung (DKVF)

Published
2017
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49. Die Krankheitskosten des Mammakarzinoms nach Behandlungsphasen in Deutschland – eine GKV-Routinedatenanalyse

Author

Kreis, K, Plöthner, M, Seufert, R, Schreeb, K, Jahndel, V, Maas, S, Kuhlmann, A, Zeidler, J, and Schramm, A

Subjects
Epidemiologie, Medizinische Dokumentation, ddc: 610, 610 Medical sciences, Medicine, Biometrie
Abstract

Einleitung: Mit einer jährlichen Inzidenz von rund 70.000 Patienten handelt es sich beim Mammakarzinom mit Abstand um die häufigste onkologische Erkrankung bei Frauen in Deutschland. Ebenfalls platziert sich das Mammakarzinom an der Spitze aller krebsbedingten Todesfälle und auf dem vierten[zum vollständigen Text gelangen Sie über die oben angegebene URL], 62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Published
2017
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50. The database of the Predicts (Projecting responses of ecological diversity in changing terrestrial systems) project

Author

Hudson, LN, Newbold, T, Contu, S, Hill, SLL, Lysenko, I, De Palma, A, Phillips, HRP, Alhusseini, TI, Bedford, FE, Bennett, DJ, Booth, H, Burton, VJ, Chng, CWT, Choimes, A, Correia, DLP, Day, J, Echeverría-Londoño, S, Emerson, SR, Gao, D, Garon, M, Harrison, MLK, Ingram, DJ, Jung, M, Kemp, V, Kirkpatrick, L, Martin, CD, Pan, Y, Pask-Hale, GD, Pynegar, EL, Robinson, AN, Sanchez-Ortiz, K, Senior, RA, Simmons, BI, White, HJ, Zhang, H, Aben, J, Abrahamczyk, S, Adum, GB, Aguilar-Barquero, V, Aizen, MA, Albertos, B, Alcala, EL, del Mar Alguacil, M, Alignier, A, Ancrenaz, M, Andersen, AN, Arbeláez-Cortés, E, Armbrecht, I, Arroyo-Rodríguez, V, Aumann, T, Axmacher, JC, Azhar, B, Azpiroz, AB, Baeten, L, Bakayoko, A, Báldi, A, Banks, JE, Baral, SK, Barlow, J, Barratt, BIP, Barrico, L, Bartolommei, P, Barton, DM, Basset, Y, Batáry, P, Bates, AJ, Baur, B, Bayne, EM, Beja, P, Benedick, S, Berg, Å, Bernard, H, Berry, NJ, Bhatt, D, Bicknell, JE, Bihn, JH, Blake, RJ, Bobo, KS, Bóçon, R, Boekhout, T, Böhning-Gaese, K, Bonham, KJ, Borges, PAV, Borges, SH, Boutin, C, Bouyer, J, Bragagnolo, C, Brandt, JS, Brearley, FQ, Brito, I, Bros, V, Brunet, J, Buczkowski, G, Buddle, CM, Bugter, R, Buscardo, E, Buse, J, Cabra-García, J, Cáceres, NC, Cagle, NL, Calviño-Cancela, M, Cameron, SA, Cancello, EM, Caparrós, R, Cardoso, P, Carpenter, D, Carrijo, TF, Carvalho, AL, Cassano, CR, Castro, H, Castro-Luna, AA, Rolando, CB, Cerezo, A, Chapman, KA, Chauvat, M, Christensen, M, Clarke, FM, Cleary, DFR, Colombo, G, Connop, SP, Craig, MD, Cruz-López, L, Cunningham, SA, D'Aniello, B, D'Cruze, N, da Silva, PG, Dallimer, M, Danquah, E, Darvill, B, Dauber, J, Davis, ALV, Dawson, J, de Sassi, C, de Thoisy, B, Deheuvels, O, Dejean, A, Devineau, J-L, Diekötter, T, Dolia, JV, Domínguez, E, Dominguez-Haydar, Y, Dorn, S, Draper, I, Dreber, N, Dumont, B, Dures, SG, Dynesius, M, Edenius, L, Eggleton, P, Eigenbrod, F, Elek, Z, Entling, MH, Esler, KJ, de Lima, RF, Faruk, A, Farwig, N, Fayle, TM, Felicioli, A, Felton, AM, Fensham, RJ, Fernandez, IC, Ferreira, CC, Ficetola, GF, Fiera, C, Filgueiras, BKC, Fırıncıoğlu, HK, Flaspohler, D, Floren, A, Fonte, SJ, Fournier, A, Fowler, RE, Franzén, M, Fraser, LH, Fredriksson, GM, Freire, GB, Frizzo, TLM, Fukuda, D, Furlani, D, Gaigher, R, Ganzhorn, JU, García, KP, Garcia-R, JC, Garden, JG, Garilleti, R, Ge, B-M, Gendreau-Berthiaume, B, Gerard, PJ, Gheler-Costa, C, Gilbert, B, Giordani, P, Giordano, S, Golodets, C, Gomes, LGL, Gould, RK, Goulson, D, Gove, AD, Granjon, L, Grass, I, Gray, CL, Grogan, J, Gu, W, Guardiola, M, Gunawardene, NR, Gutierrez, AG, Gutiérrez-Lamus, DL, Haarmeyer, DH, Hanley, ME, Hanson, T, Hashim, NR, Hassan, SN, Hatfield, RG, Hawes, JE, Hayward, MW, Hébert, C, Helden, AJ, Henden, J-A, Henschel, P, Hernández, L, Herrera, JP, Herrmann, F, Herzog, F, Higuera-Diaz, D, Hilje, B, Höfer, H, Hoffmann, A, Horgan, FG, Hornung, E, Horváth, R, Hylander, K, Isaacs-Cubides, P, Ishida, H, Ishitani, M, Jacobs, CT, Jaramillo, VJ, Jauker, B, Hernández, FJ, Johnson, MF, Jolli, V, Jonsell, M, Juliani, SN, Jung, TS, Kapoor, V, Kappes, H, Kati, V, Katovai, E, Kellner, K, Kessler, M, Kirby, KR, Kittle, AM, Knight, ME, Knop, E, Kohler, F, Koivula, M, Kolb, A, Kone, M, Kőrösi, Á, Krauss, J, Kumar, A, Kumar, R, Kurz, DJ, Kutt, AS, Lachat, T, Lantschner, V, Lara, F, Lasky, JR, Latta, SC, Laurance, WF, Lavelle, P, Le Féon, V, LeBuhn, G, Légaré, J-P, Lehouck, V, Lencinas, MV, Lentini, PE, Letcher, SG, Li, Q, Litchwark, SA, Littlewood, NA, Liu, Y, Lo-Man-Hung, N, López-Quintero, CA, Louhaichi, M, Lövei, GL, Lucas-Borja, ME, Luja, VH, Luskin, MS, MacSwiney G, MC, Maeto, K, Magura, T, Mallari, NA, Malone, LA, Malonza, PK, Malumbres-Olarte, J, Mandujano, S, Måren, IE, Marin-Spiotta, E, Marsh, CJ, Marshall, EJP, Martínez, E, Martínez Pastur, G, Moreno Mateos, D, Mayfield, MM, Mazimpaka, V, McCarthy, JL, McCarthy, KP, McFrederick, QS, McNamara, S, Medina, NG, Medina, R, Mena, JL, Mico, E, Mikusinski, G, Milder, JC, Miller, JR, Miranda-Esquivel, DR, Moir, ML, Morales, CL, Muchane, MN, Muchane, M, Mudri-Stojnic, S, Munira, AN, Muoñz-Alonso, A, Munyekenye, BF, Naidoo, R, Naithani, A, Nakagawa, M, Nakamura, A, Nakashima, Y, Naoe, S, Nates-Parra, G, Navarrete Gutierrez, DA, Navarro-Iriarte, L, Ndang'ang'a, PK, Neuschulz, EL, Ngai, JT, Nicolas, V, Nilsson, SG, Noreika, N, Norfolk, O, Noriega, JA, Norton, DA, Nöske, NM, Nowakowski, AJ, Numa, C, O'Dea, N, O'Farrell, PJ, Oduro, W, Oertli, S, Ofori-Boateng, C, Oke, CO, Oostra, V, Osgathorpe, LM, Otavo, SE, Page, NV, Paritsis, J, Parra-H, A, Parry, L, Pe'er, G, Pearman, PB, Pelegrin, N, Pélissier, R, Peres, CA, Peri, PL, Persson, AS, Petanidou, T, Peters, MK, Pethiyagoda, RS, Phalan, B, Philips, TK, Pillsbury, FC, Pincheira-Ulbrich, J, Pineda, E, Pino, J, Pizarro-Araya, J, Plumptre, AJ, Poggio, SL, Politi, N, Pons, P, Poveda, K, Power, EF, Presley, SJ, Proença, V, Quaranta, M, Quintero, C, Rader, R, Ramesh, BR, Ramirez-Pinilla, MP, Ranganathan, J, Rasmussen, C, Redpath-Downing, NA, Reid, JL, Reis, YT, Rey Benayas, JM, Rey-Velasco, JC, Reynolds, C, Ribeiro, DB, Richards, MH, Richardson, BA, Richardson, MJ, Ríos, RM, Robinson, R, Robles, CA, Römbke, J, Romero-Duque, LP, Rös, M, Rosselli, L, Rossiter, SJ, Roth, DS, Roulston, TH, Rousseau, L, Rubio, AV, Ruel, J-C, Sadler, JP, Sáfián, S, Saldaña-Vázquez, RA, Sam, K, Samnegård, U, Santana, J, Santos, X, Savage, J, Schellhorn, NA, Schilthuizen, M, Schmiedel, U, Schmitt, CB, Schon, NL, Schüepp, C, Schumann, K, Schweiger, O, Scott, DM, Scott, KA, Sedlock, JL, Seefeldt, SS, Shahabuddin, G, Shannon, G, Sheil, D, Sheldon, FH, Shochat, E, Siebert, SJ, Silva, FAB, Simonetti, JA, Slade, EM, Smith, J, Smith-Pardo, AH, Sodhi, NS, Somarriba, EJ, Sosa, RA, Soto Quiroga, G, St-Laurent, M-H, Starzomski, BM, Stefanescu, C, Steffan-Dewenter, I, Stouffer, PC, Stout, JC, Strauch, AM, Struebig, MJ, Su, Z, Suarez-Rubio, M, Sugiura, S, Summerville, KS, Sung, Y-H, Sutrisno, H, Svenning, J-C, Teder, T, Threlfall, CG, Tiitsaar, A, Todd, JH, Tonietto, RK, Torre, I, Tóthmérész, B, Tscharntke, T, Turner, EC, Tylianakis, JM, Uehara-Prado, M, Urbina-Cardona, N, Vallan, D, Vanbergen, AJ, Vasconcelos, HL, Vassilev, K, Verboven, HAF, Verdasca, MJ, Verdú, JR, Vergara, CH, Vergara, PM, Verhulst, J, Virgilio, M, Vu, LV, Waite, EM, Walker, TR, Wang, H-F, Wang, Y, Watling, JI, Weller, B, Wells, K, Westphal, C, Wiafe, ED, Williams, CD, Willig, MR, Woinarski, JCZ, Wolf, JHD, Wolters, V, Woodcock, BA, Wu, J, Wunderle, JM, Yamaura, Y, Yoshikura, S, Yu, DW, Zaitsev, AS, Zeidler, J, Zou, F, Collen, B, Ewers, RM, Mace, GM, Purves, DW, Scharlemann, JPW, Purvis, A, The Natural History Museum [London] (NHM), United Nations Environment Programme World Conservation Monitoring Centre, Department of Genetics, Evolution and Environment, Centre for Biodiversity and Environment, Research, University College of London [London] (UCL), Department of Life Sciences [Trieste], Università degli studi di Trieste, Imperial College London, Department of Zoology, Auburn University (AU), Frankfurt Zoological Society, Science and Solutions for a Changing Planet DTP and the Department of Life Sciences, Centre d’étude de la forêt, Université Laval, School of Life Sciences, University of Sussex, School of Biological Sciences [London], Queen Mary University of London (QMUL), School of Biological and Ecological Sciences, University of Stirling, School of Biological Sciences [Egham), Royal Holloway [University of London] (RHUL), School of Environment, Natural Resources and Geography, Bangor University, University College London (UCL), School of Biological Sciences [Clayton], Monash University [Clayton], Institute of Biological and Environmental Sciences, (SFIRC), Evolutionary Ecology Group, University of Antwerp (UA), Nees Institute for Plant Biodiversity, Rheinische Friedrich-Wilhelms-Universität Bonn, Wildlife and Range Management Department, Faculty of Renewable Natural Resources, College of Agriculture and Natural Resources (CANR), Kwame Nkrumah University of Science and Technology (KNUST), Save the frogs!, Escuela de Biología, Universidad Nacional de Costa Rica, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente [Bariloche] (INIBIOMA-CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), Departamento de Botánica, Facultad de Farmacia, Universidad de Valencia, Marine Laboratory, Silliman University-Angelo King Center for Research and Environmental Management, Silliman University, Department of Soil and Water Conservation, Centro de Edafologia y Biologia Aplicada del Segura, SAD Paysage (SAD Paysage), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Dynamiques Forestières dans l'Espace Rural (DYNAFOR), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Abeilles et Environnement (AE), Institut National de la Recherche Agronomique (INRA)-Avignon Université (AU), Patrimoines locaux, Environnement et Globalisation (PALOC), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU), Università degli studi di Trieste = University of Trieste, Université Laval [Québec] (ULaval), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), The Royal Society, Natural Environment Research Council (NERC), Kwame Nkrumah University of Science and Technology [GHANA] (KNUST), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Westerdijk Fungal Biodiversity Institute, Westerdijk Fungal Biodiversity Institute - Yeast Research, Hudson, Lawrence N [0000-0003-4072-7469], Choimes, Argyrios [0000-0002-9849-1500], Jung, Martin [0000-0002-7569-1390], Apollo - University of Cambridge Repository, Hudson, Lawrence N, Newbold, Tim, Contu, Sara, Hill, Samantha L. L., Lysenko, Igor, De Palma, Adriana, Phillips, Helen R. P., Alhusseini, Tamera I., Bedford, Felicity E., Bennett, Dominic J., Booth, Hollie, Burton, Victoria J., Chng, Charlotte W. T., Choimes, Argyrio, Correia, David L. P., Day, Julie, Echeverría Londoño, Susy, Emerson, Susan R., Gao, Di, Garon, Morgan, Harrison, Michelle L. K., Ingram, Daniel J., Jung, Martin, Kemp, Victoria, Kirkpatrick, Lucinda, Martin, Callum D., Pan, Yuan, Pask Hale, Gwilym D., Pynegar, Edwin L., Robinson, Alexandra N., Sanchez Ortiz, Katia, Senior, Rebecca A., Simmons, Benno I., White, Hannah J., Zhang, Hanbin, Aben, Job, Abrahamczyk, Stefan, Adum, Gilbert B., Aguilar Barquero, Virginia, Aizen, Marcelo A., Albertos, Belén, Alcala, E. L., del Mar Alguacil, Maria, Alignier, Audrey, Ancrenaz, Marc, Andersen, Alan N., Arbeláez Cortés, Enrique, Armbrecht, Inge, Arroyo Rodríguez, Víctor, Aumann, Tom, Axmacher, Jan C., Azhar, Badrul, Azpiroz, Adrián B., Baeten, Lander, Bakayoko, Adama, Báldi, Andrá, Banks, John E., Baral, Sharad K., Barlow, Jo, Barratt, Barbara I. P., Barrico, Lurde, Bartolommei, Paola, Barton, Diane M., Basset, Yve, Batáry, Péter, Bates, Adam J., Baur, Bruno, Bayne, Erin M., Beja, Pedro, Benedick, Suzan, Berg, Åke, Bernard, Henry, Berry, Nicholas J., Bhatt, Dinesh, Bicknell, Jake E., Bihn, Jochen H., Blake, Robin J., Bobo, Kadiri S., Bóçon, Roberto, Boekhout, Teun, Böhning Gaese, Katrin, Bonham, Kevin J., Borges, Paulo A. V., Borges, Sérgio H., Boutin, Céline, Bouyer, Jérémy, Bragagnolo, Cibele, Brandt, Jodi S., Brearley, Francis Q., Brito, Isabel, Bros, Vicenç, Brunet, Jörg, Buczkowski, Grzegorz, Buddle, Christopher M., Bugter, Rob, Buscardo, Erika, Buse, Jörn, Cabra García, Jimmy, Cáceres, Nilton C., Cagle, Nicolette L., Calviño Cancela, María, Cameron, Sydney A., Cancello, Eliana M., Caparrós, Rut, Cardoso, Pedro, Carpenter, Dan, Carrijo, Tiago F., Carvalho, Anelena L., Cassano, Camila R., Castro, Helena, Castro Luna, Alejandro A., Rolando, Cerda B., Cerezo, Alexi, Chapman, Kim Alan, Chauvat, Matthieu, Christensen, Morten, Clarke, Francis M., Cleary, Daniel F. R., Colombo, Giorgio, Connop, Stuart P., Craig, Michael D., Cruz López, Leopoldo, Cunningham, Saul A., D'Aniello, Biagio, D'Cruze, Neil, da Silva, Pedro Giovâni, Dallimer, Martin, Danquah, Emmanuel, Darvill, Ben, Dauber, Jen, Davis, Adrian L. V., Dawson, Jeff, de Sassi, Claudio, de Thoisy, Benoit, Deheuvels, Olivier, Dejean, Alain, Devineau, Jean Loui, Diekötter, Tim, Dolia, Jignasu V., Domínguez, Erwin, Dominguez Haydar, Yamileth, Dorn, Silvia, Draper, Isabel, Dreber, Niel, Dumont, Bertrand, Dures, Simon G., Dynesius, Mat, Edenius, Lar, Eggleton, Paul, Eigenbrod, Felix, Elek, Zoltán, Entling, Martin H., Esler, Karen J., de Lima, Ricardo F., Faruk, Aisyah, Farwig, Nina, Fayle, Tom M., Felicioli, Antonio, Felton, Annika M., Fensham, Roderick J., Fernandez, Ignacio C., Ferreira, Catarina C., Ficetola, Gentile F., Fiera, Cristina, Filgueiras, Bruno K. C., Fırıncıoğlu, Hüseyin K., Flaspohler, David, Floren, Andrea, Fonte, Steven J., Fournier, Anne, Fowler, Robert E., Franzén, Marku, Fraser, Lauchlan H., Fredriksson, Gabriella M., Freire, Geraldo B., Frizzo, Tiago L. M., Fukuda, Daisuke, Furlani, Dario, Gaigher, René, Ganzhorn, Jörg U., García, Karla P., Garcia R, Juan C., Garden, Jenni G., Garilleti, Ricardo, Ge, Bao Ming, Gendreau Berthiaume, Benoit, Gerard, Philippa J., Gheler Costa, Carla, Gilbert, Benjamin, Giordani, Paolo, Giordano, Simonetta, Golodets, Carly, Gomes, Laurens G. L., Gould, Rachelle K., Goulson, Dave, Gove, Aaron D., Granjon, Laurent, Grass, Ingo, Gray, Claudia L., Grogan, Jame, Gu, Weibin, Guardiola, Moisè, Gunawardene, Nihara R., Gutierrez, Alvaro G., Gutiérrez Lamus, Doris L., Haarmeyer, Daniela H., Hanley, Mick E., Hanson, Thor, Hashim, Nor R., Hassan, Shombe N., Hatfield, Richard G., Hawes, Joseph E., Hayward, Matt W., Hébert, Christian, Helden, Alvin J., Henden, John André, Henschel, Philipp, Hernández, Lionel, Herrera, James P., Herrmann, Farina, Herzog, Felix, Higuera Diaz, Diego, Hilje, Branko, Höfer, Hubert, Hoffmann, Anke, Horgan, Finbarr G., Hornung, Elisabeth, Horváth, Roland, Hylander, Kristoffer, Isaacs Cubides, Paola, Ishida, Hiroaki, Ishitani, Masahiro, Jacobs, Carmen T., Jaramillo, Víctor J., Jauker, Birgit, Hernández, F. Jiménez, Johnson, McKenzie F., Jolli, Virat, Jonsell, Mat, Juliani, S. Nur, Jung, Thomas S., Kapoor, Vena, Kappes, Heike, Kati, Vassiliki, Katovai, Eric, Kellner, Klau, Kessler, Michael, Kirby, Kathryn R., Kittle, Andrew M., Knight, Mairi E., Knop, Eva, Kohler, Florian, Koivula, Matti, Kolb, Annette, Kone, Mouhamadou, Kőrösi, Ádám, Krauss, Jochen, Kumar, Ajith, Kumar, Raman, Kurz, David J., Kutt, Alex S., Lachat, Thibault, Lantschner, Victoria, Lara, Francisco, Lasky, Jesse R., Latta, Steven C., Laurance, William F., Lavelle, Patrick, Le Féon, Violette, Lebuhn, Gretchen, Légaré, Jean Philippe, Lehouck, Valérie, Lencinas, María V., Lentini, Pia E., Letcher, Susan G., Li, Qi, Litchwark, Simon A., Littlewood, Nick A., Liu, Yunhui, Lo Man Hung, Nancy, López Quintero, Carlos A., Louhaichi, Mounir, Lövei, Gabor L., Lucas Borja, Manuel Esteban, Luja, Victor H., Luskin, Matthew S., MacSwiney G, M. Cristina, Maeto, Kaoru, Magura, Tibor, Mallari, Neil Aldrin, Malone, Louise A., Malonza, Patrick K., Malumbres Olarte, Jagoba, Mandujano, Salvador, Måren, Inger E., Marin Spiotta, Erika, Marsh, Charles J., Marshall, E. J. P., Martínez, Eliana, Martínez Pastur, Guillermo, Moreno Mateos, David, Mayfield, Margaret M., Mazimpaka, Vicente, Mccarthy, Jennifer L., Mccarthy, Kyle P., Mcfrederick, Quinn S., Mcnamara, Sean, Medina, Nagore G., Medina, Rafael, Mena, Jose L., Mico, Estefania, Mikusinski, Grzegorz, Milder, Jeffrey C., Miller, James R., Miranda Esquivel, Daniel R., Moir, Melinda L., Morales, Carolina L., Muchane, Mary N., Muchane, Muchai, Mudri Stojnic, Sonja, Munira, A. Nur, Muoñz Alonso, Antonio, Munyekenye, B. F., Naidoo, Robin, Naithani, A., Nakagawa, Michiko, Nakamura, Akihiro, Nakashima, Yoshihiro, Naoe, Shoji, Nates Parra, Guiomar, Navarrete Gutierrez, Dario A., Navarro Iriarte, Lui, Ndang'Ang'A, Paul K., Neuschulz, Eike L., Ngai, Jacqueline T., Nicolas, Violaine, Nilsson, Sven G., Noreika, Norberta, Norfolk, Olivia, Noriega, Jorge Ari, Norton, David A., Nöske, Nicole M., Nowakowski, A. Justin, Numa, Catherine, O'Dea, Niall, O'Farrell, Patrick J., Oduro, William, Oertli, Sabine, Ofori Boateng, Caleb, Oke, Christopher Omamoke, Oostra, Vicencio, Osgathorpe, Lynne M., Otavo, Samuel Eduardo, Page, Navendu V., Paritsis, Juan, Parra H, Alejandro, Parry, Luke, Pe'Er, Guy, Pearman, Peter B., Pelegrin, Nicolá, Pélissier, Raphaël, Peres, Carlos A., Peri, Pablo L., Persson, Anna S., Petanidou, Theodora, Peters, Marcell K., Pethiyagoda, Rohan S., Phalan, Ben, Philips, T. Keith, Pillsbury, Finn C., Pincheira Ulbrich, Jimmy, Pineda, Eduardo, Pino, Joan, Pizarro Araya, Jaime, Plumptre, A. J., Poggio, Santiago L., Politi, Natalia, Pons, Pere, Poveda, Katja, Power, Eileen F., Presley, Steven J., Proença, Vânia, Quaranta, Marino, Quintero, Carolina, Rader, Romina, Ramesh, B. R., Ramirez Pinilla, Martha P., Ranganathan, Jai, Rasmussen, Clau, Redpath Downing, Nicola A., Reid, J. Leighton, Reis, Yana T., Rey Benayas, José M., Rey Velasco, Juan Carlo, Reynolds, Chevonne, Ribeiro, Danilo Bandini, Richards, Miriam H., Richardson, Barbara A., Richardson, Michael J., Ríos, Rodrigo Macip, Robinson, Richard, Robles, Carolina A., Römbke, Jörg, Romero Duque, Luz Piedad, Rös, Matthia, Rosselli, Loreta, Rossiter, Stephen J., Roth, Dana S., Roulston, T'ai H., Rousseau, Laurent, Rubio, André V., Ruel, Jean Claude, Sadler, Jonathan P., Sáfián, Szabolc, Saldaña Vázquez, Romeo A., Sam, Katerina, Samnegård, Ulrika, Santana, Joana, Santos, Xavier, Savage, Jade, Schellhorn, Nancy A., Schilthuizen, Menno, Schmiedel, Ute, Schmitt, Christine B., Schon, Nicole L., Schüepp, Christof, Schumann, Katharina, Schweiger, Oliver, Scott, Dawn M., Scott, Kenneth A., Sedlock, Jodi L., Seefeldt, Steven S., Shahabuddin, Ghazala, Shannon, Graeme, Sheil, Dougla, Sheldon, Frederick H., Shochat, Eyal, Siebert, Stefan J., Silva, Fernando A. B., Simonetti, Javier A., Slade, Eleanor M., Smith, Jo, Smith Pardo, Allan H., Sodhi, Navjot S., Somarriba, Eduardo J., Sosa, Ramón A., Soto Quiroga, Grimaldo, St Laurent, Martin Hugue, Starzomski, Brian M., Stefanescu, Constanti, Steffan Dewenter, Ingolf, Stouffer, Philip C., Stout, Jane C., Strauch, Ayron M., Struebig, Matthew J., Su, Zhimin, Suarez Rubio, Marcela, Sugiura, Shinji, Summerville, Keith S., Sung, Yik Hei, Sutrisno, Hari, Svenning, Jens Christian, Teder, Tiit, Threlfall, Caragh G., Tiitsaar, Anu, Todd, Jacqui H., Tonietto, Rebecca K., Torre, Ignasi, Tóthmérész, Béla, Tscharntke, Teja, Turner, Edgar C., Tylianakis, Jason M., Uehara Prado, Marcio, Urbina Cardona, Nicola, Vallan, Deni, Vanbergen, Adam J., Vasconcelos, Heraldo L., Vassilev, Kiril, Verboven, Hans A. F., Verdasca, Maria João, Verdú, José R., Vergara, Carlos H., Vergara, Pablo M., Verhulst, Jort, Virgilio, Massimiliano, Vu, Lien Van, Waite, Edward M., Walker, Tony R., Wang, Hua Feng, Wang, Yanping, Watling, James I., Weller, Britta, Wells, Konstan, Westphal, Catrin, Wiafe, Edward D., Williams, Christopher D., Willig, Michael R., Woinarski, John C. Z., Wolf, Jan H. D., Wolters, Volkmar, Woodcock, Ben A., Wu, Jihua, Wunderle, Joseph M., Yamaura, Yuichi, Yoshikura, Satoko, Yu, Douglas W., Zaitsev, Andrey S., Zeidler, Juliane, Zou, Fasheng, Collen, Ben, Ewers, Rob M., Mace, Georgina M., Purves, Drew W., Scharlemann, Jörn P. W., Purvis, Andy, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institut National de la Recherche Agronomique - INRA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Natural History Museum, 3Department of Genetics, Evolution and Environment, Centre for Biodiversity and Environment, Research, University College London ( UCL ), Department of Life Sciences, Universita di Trieste, Auburn University, Queen Mary University of London ( QMUL ), Royal Holloway [University of London] ( RHUL ), ( SFIRC ), University of Antwerp ( UA ), University of Bonn (Rheinische Friedrich-Wilhelms), Kwame Nkrumah University of Science and Technology ( KNUST ), Universidad de Costa Rica, Laboratorio Ecotono-CRUB, Universidad Nacional del Comahue, SAD Paysage ( SAD Paysage ), Institut National de la Recherche Agronomique ( INRA ) -AGROCAMPUS OUEST, Dynamiques Forestières dans l'Espace Rural ( DYNAFOR ), Institut National Polytechnique [Toulouse] ( INP ) -Institut National de la Recherche Agronomique ( INRA ) -Ecole Nationale Supérieure Agronomique de Toulouse, Contrôle des maladies animales exotiques et émergentes [Montpellier] ( CMAEE ), Institut National de la Recherche Agronomique ( INRA ) -Centre de coopération internationale en recherche agronomique pour le développement [CIRAD] : UMR15, Unité Mixte de Recherches sur les Herbivores ( UMR 1213 Herbivores ), VetAgro Sup ( VAS ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique ( INRA ), Centre de Biologie pour la Gestion des Populations ( CBGP ), Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Université de Montpellier ( UM ) -Institut de Recherche pour le Développement ( IRD [France-Sud] ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Abeilles et Environnement ( AE ), and Institut National de la Recherche Agronomique ( INRA ) -Université d'Avignon et des Pays de Vaucluse ( UAPV )

Subjects
VDP::Mathematics and natural science: 400::Zoology and botany: 480::Ecology: 488, Biodiversité et Ecologie, data sharing, habitat, Biológiai tudományok, Q1, BIRD SPECIES RICHNESS, TROPICAL DRY FOREST, VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488, MEXICAN COFFEE PLANTATIONS, Természettudományok, Data and Information, Milieux et Changements globaux, LOWLAND, ComputingMilieux_MISCELLANEOUS, Original Research, Ecology, global biodiversity modeling, global change, habitat destruction, land use, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, LAND-USE CHANGE, [ SDE.MCG ] Environmental Sciences/Global Changes, Chemistry, Earth and Related Environmental Sciences, Evolution, [SDE.MCG]Environmental Sciences/Global Changes, INTENSIVELY MANAGED FARMLAND, Ingénierie de l'environnement, CARABID BEETLE ASSEMBLAGES, FRUIT-FEEDING BUTTERFLIES, Ecology and Environment, Biodiversity and Ecology, keywords: data sharing, Behavior and Systematics, Biology, Ekologi, [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, QL, DIPTEROCARP FOREST, QH, PLANT COMMUNITY COMPOSITION, Geovetenskap och miljövetenskap, Biology and Life Sciences, destruction, Ecology, Evolution, Behavior and Systematic, URBAN-RURAL GRADIENT, Earth and Environmental Sciences, Environnement et Société, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

Source at https://doi.org/10.1002/ece3.2579. The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

Published
2017
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