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5 resultados encontrados para: AUTOR: Miller, Jennifer A.
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1.
Artículo
*Solicítelo con su bibliotecario/a
Population status, connectivity, and conservation action for the endangered Baird's tapir
Schank, Cody J. (autor) ; Cove, Michael V. (autor) ; Arima, Eugenio Y. (autor) ; Brandt, Laroy S. E. (autor) ; Brenes Mora, Esteban (autor) ; Carver, Andrew (autor) ; Diaz Pulido, Angelica (autora) ; Estrada, Nereyda (autora) ; Foster, Rebecca J. (autora) ; Godínez Gómez, Oscar (autor) ; Harmsen, Bart J. (autor) ; Jordan, Christopher A. (autor) ; Keitt, Timothy H. (autor) ; Kelly, Marcella J. (autora) ; Sáenz Méndez, Joel (autor) ; Mendoza Ramírez, Eduardo (autor) ; Meyer, Ninon France Victoire (autora) ; Pozo Montuy, Gilberto (autor) ; Naranjo Piñera, Eduardo Jorge (autor) (1963-) ; Nielsen, Clayton K. (autor) ; O´Farril Cruz, Elsa Georgina (autora) ; Reyna Hurtado, Rafael Ángel (autor) ; Rivero Hernández, Crysia Marina (autora) ; Carvajal Sánchez, José Pablo (autor) ; Singleton, Maggie (autora) ; Torre, J. Antonio de la (autor) ; Wood, Margot A. (autora) ; Young, Kenneth R. (autor) ; Miller, Jennifer A. (autora) ;
Disponible en línea
Contenido en: Biological Conservation Volumen 245, número 108501 (May 2020), p. 1-12 ISSN: 0006-3207
Nota: Solicítelo con su bibliotecario/a
Resumen en: Inglés |
Resumen en inglés

Although many large mammals currently face significant threats that could lead to their extinction, resources for conservation are often scarce, resulting in the need to develop efficient plans to prioritize conservation actions. We combined several methods in spatial ecology to identify the distribution of the endangered Baird's tapir across its range from southern Mexico to northern Colombia. Twenty-eight habitat patches covering 23% of the study area were identified, harboring potentially 62% or more of the total population for this flagship species. Roughly half of the total area is under some form of protection, while most of the remaining habitat (~70%) occurs in indigenous/local communities. The network with maximum connectivity created from these patches contains at least one complete break (in Mexico between Selva El Ocote and Selva Lacandona) even when considering the most generous dispersal scenario. The connectivity analysis also highlighted a probable break at the Panama Canal and high habitat fragmentation in Honduras. In light of these findings, we recommend the following actions to facilitate the conservation of Baird's tapir: 1) protect existing habitat by strengthening enforcement in areas already under protection, 2) work with indigenous territories to preserve and enforce their land rights, and help local communities maintain traditional practices; 3) re-establish connections between habitat patches that will allow for connectivity across the species' distribution; 4) conduct additional noninvasive surveys in patches with little or no species data; and 5) collect more telemetry and genetic data on the species to estimate home range size, dispersal capabilities, and meta-population structure.


Resumen en: Inglés |
Resumen en inglés

Species distribution models (SDMs) are statistical tools used to develop continuous predictions of species occurrence. ‘Integrated SDMs’ (ISDMs) are an elaboration of this approach with potential advantages that allow for the dual use of opportunistically collected presence-only data and site-occupancy data from planned surveys. These models also account for survey bias and imperfect detection through the use of a hierarchical modelling framework that separately estimates the species–environment response and detection process. This is particularly helpful for conservation applications and predictions for rare species, where data are often limited and prediction errors may have significant management consequences. Despite this potential importance, ISDMs remain largely untested under a variety of scenarios. We performed an exploration of key modelling decisions and assumptions on an ISDM using the endangered Baird’s tapir (Tapirus bairdii) as a test species. We found that site area had the strongest effect on the magnitude of population estimates and underlying intensity surface and was driven by estimates of model intercepts. Selecting a site area that accounted for the individual movements of the species within an average home range led to population estimates that coincided with expert estimates. ISDMs that do not account for the individual movements of species will likely lead to less accurate estimates of species intensity (number of individuals per unit area) and thus overall population estimates.

This bias could be severe and highly detrimental to conservation actions if uninformed ISDMs are used to estimate global populations of threatened and data-deficient species, particularly those that lack natural history and movement information. However, the ISDM was consistently the most accurate model compared to other approaches, which demonstrates the importance of this new modelling framework and the ability to combine opportunistic data with systematic survey data. Thus, we recommend researchers use ISDMs with conservative movement information when estimating population sizes of rare and data-deficient species. ISDMs could be improved by using a similar parameterization to spatial capture–recapture models that explicitly incorporate animal movement as a model parameter, which would further remove the need for spatial subsampling prior to implementation.


3.
Artículo
The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
Hudson, Lawrence N. (autor) ; Newbold, Tim (coaut.) ; Contu, Sara (coaut.) ; Hill, Samantha L. L. (coaut.) ; Lysenko, Igor (coaut.) ; De Palma, Adriana (coaut.) ; Phillips, Helen R. P. (coaut.) ; Alhusseini, Tamera I. (coaut.) ; Bedford, Felicity E. (coaut.) ; Bennett, Dominic J. (coaut.) ; Booth, Hollie. (coaut.) ; Burton, Victoria J. (coaut.) ; Chng, Charlotte W. T. (coaut.) ; Choimes, Argyrios (coaut.) ; Correia, David L. P. (coaut.) ; Day, Julie (coaut.) ; Echeverría Londoño, Susy (coaut.) ; Emerson, Susan R. (coaut.) ; Gao, Di (coaut.) ; Garon, Morgan (coaut.) ; Harrison, Michelle L. K. (coaut.) ; Ingram, Daniel J. (coaut.) ; Jung, Martin (coaut.) ; Kemp, Victoria (coaut.) ; Kirkpatrick, Lucinda (coaut.) ; Martin, Callum D. (coaut.) ; Pan, Yuan (coaut.) ; Pask Hale, Gwilym D. (coaut.) ; Pynegar, Edwin L. (coaut.) ; Robinson, Alexandra N. (coaut.) ; Sánchez Ortiz, Katia (coaut.) ; Senior, Rebecca A. (coaut.) ; Simmons, Benno I. (coaut.) ; White, Hannah J. (coaut.) ; Zhang, Hanbin (coaut.) ; Aben, Job (coaut.) ; Abrahamczyk, Stefan (coaut.) ; Adum, Gilbert B. (coaut.) ; Aguilar Barquero, Virginia (coaut.) ; Aizen, Marcelo A. (coaut.) ; Albertos, Belén (coaut.) ; Alcalá, Elio L. (coaut.) ; Alguacil, María del Mar (coaut.) ; Alignier, Audrey (coaut.) ; Ancrenaz, Marc (coaut.) ; Andersen, Alan N. (coaut.) ; Arbeláez Cortés, Enrique (coaut.) ; Armbrecht, Inge (coaut.) ; Arroyo Rodríguez, Víctor (coaut.) ; Aumann, Tom (coaut.) ; Axmacher, Jan C. (coaut.) ; Azhar, Badrul (coaut.) ; Azpiroz, Adrián B. (coaut.) ; Baeten, Lander (coaut.) ; Bakayoko, Adama (coaut.) ; Báldi, András (coaut.) ; Banks, John E. (coaut.) ; Baral, Sharad K. (coaut.) ; Barlow, Jos (coaut.) ; Barratt, Barbara I. P. (coaut.) ; Barrico, Lurdes (coaut.) ; Bartolommei, Paola (coaut.) ; Barton, Diane M. (coaut.) ; Basset, Yves (coaut.) ; Batáry, Péter (coaut.) ; Bates, Adam J. (coaut.) ; Baur, Bruno (coaut.) ; Bayne, Erin M. (coaut.) ; Beja, Pedro (coaut.) ; Benedick, Suzan (coaut.) ; Berg, Åke (coaut.) ; Bernard, Henry (coaut.) ; Berry, Nicholas J. (coaut.) ; Bhatt, Dinesh (coaut.) ; Bicknell, Jake E. (coaut.) ; Bihn, Jochen H. (coaut.) ; Blake, Robin J. (coaut.) ; Bobo, Kadiri S. (coaut.) ; Bóçon, Roberto (coaut.) ; Boekhout, Teun (coaut.) ; Böhning Gaese, Katrin (coaut.) ; Bonham, Kevin J. (coaut.) ; Borges, Paulo A. V. (coaut.) ; Borges, Sérgio H. (coaut.) ; Boutin, Céline (coaut.) ; Bouyer, Jérémy (coaut.) ; Bragagnolo, Cibele (coaut.) ; Brandt, Jodi S. (coaut.) ; Brearley, Francis Q. (coaut.) ; Brito, Isabel (coaut.) ; Bros, Vicenç (coaut.) ; Brunet, Jörg (coaut.) ; Buczkowski, Grzegorz (coaut.) ; Buddle, Christopher M. (coaut.) ; Bugter, Rob (coaut.) ; Buscardo, Erika (coaut.) ; Buse, Jörn (coaut.) ; Cabra García, Jimmy (coaut.) ; Cáceres, Nilton C. (coaut.) ; Cagle, Nicolette L. (coaut.) ; Calviño Cancela, María (coaut.) ; Cameron, Sydney A. (coaut.) ; Cancello, Eliana M. (coaut.) ; Caparrós, Rut (coaut.) ; Cardoso, Pedro (coaut.) ; Carpenter, Dan (coaut.) ; Carrijo, Tiago F. (coaut.) ; Carvalho, Anelena L. (coaut.) ; Cassano, Camila R. (coaut.) ; Castro, Helena (coaut.) ; Castro Luna, Alejandro A. (coaut.) ; Cerda B., Rolando (coaut.) ; Cerezo, Alexis (coaut.) ; Chapman, Kim Alan (coaut.) ; Chauvat, Matthieu (coaut.) ; Christensen, Morten (coaut.) ; Clarke, Francis M. (coaut.) ; Cleary, Daniël Francis Richard (coaut.) ; Colombo, Giorgio (coaut.) ; Connop, Stuart P. (coaut.) ; Craig, Michael D. (coaut.) ; Cruz López, Leopoldo Caridad (coaut.) ; Cunningham, Saul A. (coaut.) ; D’Aniello, Biagio (coaut.) ; D'Cruze, Neil C. (coaut.) ; da Silva, Pedro Giovâni (coaut.) ; Dallimer, Martin (coaut.) ; Danquah, Emmanuel (coaut.) ; Darvill, Ben (coaut.) ; Dauber, Jens (coaut.) ; Davis, Adrian L. V. (coaut.) ; Dawson, Jeff (coaut.) ; de Sassi, Claudio (coaut.) ; de Thoisy, Benoit (coaut.) ; Deheuvels, Olivier (coaut.) ; Dejean, Alain (coaut.) ; Devineau, Jean Louis (coaut.) ; Diekötter, Tim (coaut.) ; Dolia, Jignasu V. (coaut.) ; Domínguez, Erwin (coaut.) ; Domínguez Haydar, Yamileth (coaut.) ; Dorn, Silvia (coaut.) ; Draper, Isabel (coaut.) ; Dreber, Niels (coaut.) ; Dumont, Bertrand (coaut.) ; Dures, Simon G. (coaut.) ; Dynesius, Mats (coaut.) ; Edenius, Lars (coaut.) ; Eggleton, Paul (coaut.) ; Eigenbrod, Felix (coaut.) ; Elek, Zoltán (coaut.) ; Entling, Martin H. (coaut.) ; Esler, Karen J. (coaut.) ; Lima, Ricardo F. de (coaut.) ; Faruk, Aisyah (coaut.) ; Farwig, Nina (coaut.) ; Fayle, Tom M. (coaut.) ; Felicioli, Antonio (coaut.) ; Felton, Annika M. (coaut.) ; Fensham, Roderick J. (coaut.) ; Fernández, Ignacio C. (coaut.) ; Ferreira, Catarina C. (coaut.) ; Ficetola, Gentile F. (coaut.) ; Fiera, Cristina (coaut.) ; Filgueiras, Bruno K. C. (coaut.) ; Fırıncıoğlu, Hüseyin K. (coaut.) ; Flaspohler, David (coaut.) ; Floren, Andreas (coaut.) ; Fonte, Steven J. (coaut.) ; Fournier, Anne (coaut.) ; Fowler, Robert E. (coaut.) ; Franzén, Markus (coaut.) ; Fraser, Lauchlan H. (coaut.) ; Fredriksson, Gabriella Margit (coaut.) ; Freire Jr, Geraldo B. (coaut.) ; Frizzo, Tiago L. M. (coaut.) ; Fukuda, Daisuke (coaut.) ; Furlani, Dario (coaut.) ; Gaigher, René (coaut.) ; Ganzhorn, Jörg U. (coaut.) ; García, Karla P. (coaut.) ; García R., Juan C. (coaut.) ; Garden, Jenni G. (coaut.) ; Garilleti, Ricardo (coaut.) ; Ge, Bao Ming (coaut.) ; Gendreau Berthiaume, Benoit (coaut.) ; Gerard, Philippa J. (coaut.) ; Gheler Costa, Carla (coaut.) ; Gilbert, Benjamin (coaut.) ; Giordani, Paolo (coaut.) ; Giordano, Simonetta (coaut.) ; Golodets, Carly (coaut.) ; Gomes, Laurens G. L. (coaut.) ; Gould, Rachelle K. (coaut.) ; Goulson, Dave (coaut.) ; Gove, Aaron D. (coaut.) ; Granjon, Laurent (coaut.) ; Grass, Ingo (coaut.) ; Gray, Claudia L. (coaut.) ; Grogan, James (coaut.) ; Gu, Weibin (coaut.) ; Guardiola, Moisès (coaut.) ; Gunawardene, Nihara R. (coaut.) ; Gutiérrez, Álvaro G. (coaut.) ; Gutiérrez Lamus, Doris L. (coaut.) ; Haarmeyer, Daniela H. (coaut.) ; Hanley, Mick E. (coaut.) ; Hanson, Thor (coaut.) ; Hashim, Nor R. (coaut.) ; Hassan, Shombe N. (coaut.) ; Hatfield, Richard G. (coaut.) ; Hawes, Joseph E. (coaut.) ; Hayward, Matt W. (coaut.) ; Hébert, Christian (coaut.) ; Helden, Alvin J. (coaut.) ; Henden, John André (coaut.) ; Henschel, Philipp (coaut.) ; Hernández, Lionel (coaut.) ; Herrera, James P. (coaut.) ; Herrmann, Farina (coaut.) ; Herzog, Félix (coaut.) ; Higuera Díaz, Diego (coaut.) ; Hilje, Branko (coaut.) ; Höfer, Hubert (coaut.) ; Hoffmann, Anke (coaut.) ; Horgan, Finbarr G. (coaut.) ; Hornung, Elisabeth (coaut.) ; Horváth, Roland (coaut.) ; Hylander, Kristoffer (coaut.) ; Isaacs-Cubides, Paola (coaut.) ; Ishida, Hiroaki (coaut.) ; Ishitani, Masahiro (coaut.) ; Jacobs, Carmen T. (coaut.) ; Jaramillo, Víctor J. (coaut.) ; Jauker, Birgit (coaut.) ; Jiménez Hernández, F. (coaut.) ; Johnson, McKenzie F. (coaut.) ; Jolli, Virat (coaut.) ; Jonsell, Mats (coaut.) ; Juliani, S. Nur (coaut.) ; Jung, Thomas S. (coaut.) ; Kapoor, Vena (coaut.) ; Kappes, Heike (coaut.) ; Kati, Vassiliki (coaut.) ; Katovai, Eric (coaut.) ; Kellner, Klaus (coaut.) ; Kessler, Michael (coaut.) ; Kirby, Kathryn R. (coaut.) ; Kittle, Andrew M. (coaut.) ; Knight, Mairi E. (coaut.) ; Knop, Eva (coaut.) ; Kohler, Florian (coaut.) ; Koivula, Matti (coaut.) ; Kolb, Annette (coaut.) ; Kone, Mouhamadou (coaut.) ; Kőrösi, Ádám (coaut.) ; Krauss, Jochen (coaut.) ; Kumar, Ajith (coaut.) ; Kumar, Raman (coaut.) ; Kurz, David J. (coaut.) ; Kutt, Alex S. (coaut.) ; Lachat, Thibault (coaut.) ; Lantschner, Victoria (coaut.) ; Lara Valencia, Francisco (coaut.) ; Lasky, Jesse R. (coaut.) ; Latta, Steven C. (coaut.) ; Laurance, William F. (coaut.) ; Lavelle, Patrick (coaut.) ; Le Féon, Violette (coaut.) ; LeBuhn, Gretchen (coaut.) ; Légaré, Jean-Philippe (coaut.) ; Lehouck, Valérie (coaut.) ; Lencinas, María V. (coaut.) ; Lentini, Pia E. (coaut.) ; Letcher, Susan G. (coaut.) ; Li, Qi (coaut.) ; Litchwark, Simon A. (coaut.) ; Littlewood, Nick A. (coaut.) ; Liu, Yunhui (coaut.) ; Lo Man Hung, Nancy (coaut.) ; López Quintero, Carlos Alberto (coaut.) ; Louhaichi, Mounir (coaut.) ; Lövei, Gabor L. (coaut.) ; Lucas Borja, Manuel Esteban (coaut.) ; Luja Molina, Víctor Hugo (coaut.) ; Luskin, Matthew S. (coaut.) ; Mac Swiney González, María Cristina (coaut.) ; Maeto, Kaoru (coaut.) ; Magura, Tibor (coaut.) ; Mallari, Neil Aldrin (coaut.) ; Malone, Louise A. (coaut.) ; Malonza, Patrick K. (coaut.) ; Malumbres Olarte, Jagoba (coaut.) ; Mandujano Rodríguez, Salvador (coaut.) ; Måren, Inger E. (coaut.) ; Marín Spiotta, Erika (coaut.) ; Marsh, Charles J. (coaut.) ; Marshall, E. J. P. (coaut.) ; Martínez, Eliana (coaut.) ; Martínez Pastur, Guillermo (coaut.) ; Moreno Mateos, David (coaut.) ; Mayfield, Margaret M. (coaut.) ; Mazimpaka, Vicente (coaut.) ; McCarthy, Jennifer L. (coaut.) ; McCarthy, Kyle P. (coaut.) ; McFrederick, Quinn S. (coaut.) ; McNamara, Sean (coaut.) ; Medina, Nagore G. (coaut.) ; Medina, Rafael (coaut.) ; Mena, José L. (coaut.) ; Mico, Estefania (coaut.) ; Mikusinski, Grzegorz (coaut.) ; Milder, Jeffrey C. (coaut.) ; Miller, James R. (coaut.) ; Miranda Esquivel, Daniel R. (coaut.) ; Moir, Melinda L. (coaut.) ; Morales, Carolina L. (coaut.) ; Muchane, Mary N. (coaut.) ; Muchane, Muchai (coaut.) ; Mudri Stojnic, Sonja (coaut.) ; Munira, A. Nur (coaut.) ; Muñoz Alonso, Luis Antonio (coaut.) ; Munyekenye, B. F. (coaut.) ; Naidoo, Robin (coaut.) ; Naithani, A. (coaut.) ; Nakagawa, Michiko (coaut.) ; Nakamura, Akihiro (coaut.) ; Nakashima, Yoshihiro (coaut.) ; Naoe, Shoji (coaut.) ; Nates Parra, Guiomar (coaut.) ; Navarrete Gutiérrez, Darío Alejandro (coaut.) ; Navarro Iriarte, Luis (coaut.) ; Ndang’ang’a, Paul K. (coaut.) ; Neuschulz, Eike L. (coaut.) ; Ngai, Jacqueline T. (coaut.) ; Nicolás, Violaine (coaut.) ; Nilsson, Sven G. (coaut.) ; Noreika, Norbertas (coaut.) ; Norfolk, Olivia (coaut.) ; Noriega, Jorge Ari (coaut.) ; Norton, David A. (coaut.) ; Nöske, Nicole M. (coaut.) ; Nowakowski, A. Justin (coaut.) ; Numa, Catherine (coaut.) ; O’Dea, Niall (coaut.) ; O’Farrell, Patrick J. (coaut.) ; Oduro, William (coaut.) ; Oertli, Sabine (coaut.) ; Ofori Boateng, Caleb (coaut.) ; Oke, Christopher Omamoke (coaut.) ; Oostra, Vicencio (coaut.) ; Osgathorpe, Lynne M. (coaut.) ; Otavo, Samuel Eduardo (coaut.) ; Page, Navendu V. (coaut.) ; Paritsis, Juan (coaut.) ; Parra H., Alejandro (coaut.) ; Parry, Luke (coaut.) ; Pe’er, Guy (coaut.) ; Pearman, Peter B. (coaut.) ; Pelegrin, Nicolás (coaut.) ; Pélissier, Raphaël (coaut.) ; Peres, Carlos A. (coaut.) ; Peri, Pablo L. (coaut.) ; Persson, Anna S. (coaut.) ; Petanidou, Theodora (coaut.) ; Peters, Marcell K. (coaut.) ; Pethiyagoda, Rohan S. (coaut.) ; Phalan, Ben (coaut.) ; Philips, T. Keith (coaut.) ; Pizarro Araya, Jaime (coaut.) ; Plumptre, A. J. (coaut.) ; Poggio, Santiago L. (coaut.) ; Politi, Natalia (coaut.) ; Pons, Pere (coaut.) ; Poveda, Katja (coaut.) ; Power, Eileen F. (coaut.) ; Presley, Steven J. (coaut.) ; Proença, Vânia (coaut.) ; Quaranta, Marino (coaut.) ; Quintero, Carolina (coaut.) ; Rader, Romina (coaut.) ; Ramesh, B. R. (coaut.) ; Ramírez Pinilla, Martha Patricia (coaut.) ; Ranganathan, Jai (coaut.) ; Rasmussen, Claus (coaut.) ; Redpath Downing, Nicola A. (coaut.) ; Reid, J. Leighton (coaut.) ; Reis, Yana T. (coaut.) ; Rey Benayas, José María (coaut.) ; Rey Velasco, Juan Carlos (coaut.) ; Reynolds, Chevonne (coaut.) ; Bandini Ribeiro, Danilo (coaut.) ; Richards, Miriam H. (coaut.) ; Richardson, Barbara A. (coaut.) ; Richardson, Michael J. (coaut.) ; Macip Ríos, Rodrigo (coaut.) ; Robinson, Richard (coaut.) ; Robles, Carolina A. (coaut.) ; Römbke, Jörg (coaut.) ; Romero Duque, Luz Piedad (coaut.) ; Rös, Matthias (coaut.) ; Rosselli, Loreta (coaut.) ; Rossiter, Stephen J. (coaut.) ; Roth, Dana S. (coaut.) ; Roulston, T’ai H. (coaut.) ; Rousseau, Laurent (coaut.) ; Rubio, André V. (coaut.) ; Ruel, Jean Claude (coaut.) ; Sadler, Jonathan P. (coaut.) ; Sáfián, Szabolcs (coaut.) ; Saldaña Vázquez, Romeo A. (coaut.) ; Sam, Katerina (coaut.) ; Samnegård, Ulrika (coaut.) ; Santana, Joana (coaut.) ; Santos, Xavier (coaut.) ; Savage, Jade (coaut.) ; Schellhorn, Nancy A. (coaut.) ; Schilthuizen, Menno (coaut.) ; Schmiedel, Ute (coaut.) ; Schmitt, Christine B. (coaut.) ; Schon, Nicole L. (coaut.) ; Schüepp, Christof (coaut.) ; Schumann, Katharina (coaut.) ; Schweiger, Oliver (coaut.) ; Scott, Dawn M. (coaut.) ; Scott, Kenneth A. (coaut.) ; Sedlock, Jodi L. (coaut.) ; Seefeldt, Steven S. (coaut.) ; Shahabuddin, Ghazala (coaut.) ; Shannon, Graeme (coaut.) ; Sheil, Douglas (coaut.) ; Sheldon, Frederick H. (coaut.) ; Shochat, Eyal (coaut.) ; Siebert, Stefan J. (coaut.) ; Silva, Fernando A. B. (coaut.) ; Simonetti, Javier A. (coaut.) ; Slade, Eleanor M. (coaut.) ; Smith, Jo (coaut.) ; Smith Pardo, Allan H. (coaut.) ; Sodhi, Navjot S. (coaut.) ; Somarriba, Eduardo J. (coaut.) ; Sosa, Ramón A. (coaut.) ; Soto Quiroga, Grimaldo (coaut.) ; St Laurent, Martin Hugues (coaut.) ; Starzomski, Brian M. (coaut.) ; Stefanescu, Constanti (coaut.) ; Steffan Dewenter, Ingolf (coaut.) ; Stouffer, Philip C. (coaut.) ; Stout, Jane C. (coaut.) ; Strauch, Ayron M. (coaut.) ; Struebig, Matthew J. (coaut.) ; Su, Zhimin (coaut.) ; Suárez Rubio, Marcela (coaut.) ; Sugiura, Shinji (coaut.) ; Summerville, Keith S. (coaut.) ; Sung, Yik Hei (coaut.) ; Sutrisno, Hari (coaut.) ; Svenning, Jens Christian (coaut.) ; Teder, Tiit (coaut.) ; Threlfall, Caragh G. (coaut.) ; Tiitsaar, Anu (coaut.) ; Todd, Jacqui H. (coaut.) ; Tonietto, Rebecca K. (coaut.) ; Torre, Ignasi (coaut.) ; Tóthmérész, Béla (coaut.) ; Tscharntke, Teja (coaut.) ; Turner, Edgar C. (coaut.) ; Tylianakis, Jason M. (coaut.) ; Uehara Prado, Marcio (coaut.) ; Urbina Cardona, Nicolas (coaut.) ; Vallan, Denis (coaut.) ; Vanbergen, Adam J. (coaut.) ; Vasconcelos, Heraldo L. (coaut.) ; Vassilev, Kiril (coaut.) ; Verboven, Hans A. F. (coaut.) ; João Verdasca, Maria (coaut.) ; Verdú, José R. (coaut.) ; Vergara, Carlos H. (coaut.) ; Vergara, Pablo M. (coaut.) ; Verhulst, Jort (coaut.) ; Virgilio, Massimiliano (coaut.) ; Van Vu, Lien (coaut.) ; Waite, Edward M. (coaut.) ; Walker, Tony R. (coaut.) ; Wang, Hua Feng (coaut.) ; Wang, Yanping (coaut.) ; Watling, James I. (coaut.) ; Weller, Britta (coaut.) ; Wells, Konstans (coaut.) ; Westphal, Catrin (coaut.) ; Wiafe, Edward D. (coaut.) ; Williams, Christopher D. (coaut.) ; Willig, Michael R. (coaut.) ; Woinarski, John C. Z. (coaut.) ; Wolf, Jan Hendrik Diederik (coaut.) ; Wolters, Volkmar (coaut.) ; Woodcock, Ben A. (coaut.) ; Wu, Jihua (coaut.) ; Wunderle, Joseph M. (coaut.) ; Yamaura, Yuichi (coaut.) ; Yoshikura, Satoko (coaut.) ; Yu, Douglas W. (coaut.) ; Zaitsev, Andrey S. (coaut.) ; Zeidler, Juliane (coaut.) ; Zou, Fasheng (coaut.) ; Collen, Ben (coaut.) ; Ewers, Rob M. (coaut.) ; Mace, Georgina M. (coaut.) ; Purves, Drew W. (coaut.) ; Scharlemann, Jörn P. W. (coaut.) ; Purvi, Andy (coaut.) ;
Contenido en: Ecology and Evolution Vol. 7, no. 1 (January 2017), p. 145–188 ISSN: 2045-7758
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Resumen en: Inglés |
Resumen en inglés

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.


4.
- Artículo con arbitraje
*Solicítelo con su bibliotecario/a
Using a novel model approach to assess the distribution and conservation status of the endangered Baird’s tapir
Schank, Cody J. ; Cove, Michael V. (coaut.) ; Kelly, Marcella J. (coaut.) ; Mendoza Ramírez, Eduardo (coaut.) ; O´Farril Cruz, Elsa Georgina (coaut.) ; Reyna Hurtado, Rafael Ángel (coaut.) ; Meyer, Ninon France Victoire (coaut.) ; Jordan, Christopher A. (coaut.) ; González Maya, José F. (coaut.) ; Lizcano, Diego J. (coaut.) ; Moreno, Ricardo (coaut.) ; Dobbins, Michael T. (coaut.) ; Montalvo, Víctor (coaut.) ; Sáenz Bolaños, Carolina (coaut.) ; Carillo Jiménez, Eduardo (coaut.) ; Estrada, Nereyda (coaut.) ; Cruz Díaz, Juan Carlos (coaut.) ; Sáenz, Joel (coaut.) ; Spínola, Manuel (coaut.) ; Carver, Andrew (coaut.) ; Fort, Jessica (coaut.) ; Nielsen, Clayton K. (coaut.) ; Botello, Francisco (coaut.) ; Pozo Montuy, Gilberto (coaut.) ; Rivero Hernández, Crysia Marina (coaut.) ; De la Torre, José Antonio (coaut.) ; Brenes Mora, Esteban (coaut.) ; Godínez Gómez, Oscar (coaut.) ; Wood, Margot A. (coaut.) ; Gilbert, Jessica (coaut.) ; Miller, Jennifer A. (coaut.) ;
Contenido en: Diversity and Distributions Vol. 23, no. 12 (December 2017), p. 1459–1471 ISSN: 1809-127X
Nota: Solicítelo con su bibliotecario/a
Resumen en: Inglés |
Resumen en inglés

Aim: We test a new species distribution modelling (SDM) framework, while comparing results to more common distribution modelling techniques. This framework allows for the combination of presence-only (PO) and presence-absence (PA) data and accounts for imperfect detection and spatial bias in presence data. The new framework tested here is based on a Poisson point process model, which allows for predictions of population size. We compared these estimates to those provided by experts on the species. Species and Location: Presence data on Baird’s tapir (Tapirus bairdii) throughout its range from southern México to northern Colombia were used in this research, primarily from the years 2000 to 2016. Methods: Four SDM frameworks are compared as follows: (1) Maxent, (2) a presence-only (PO) SDM based on a Poisson point process model (PPM), (3) a presence-absence (PA) SDM also based on a PPM and (4) an Integrated framework which combines the previous two models. Model averaging was used to produce a single set of coefficient estimates and predictive maps for each model framework. A hotspot analysis (Gi*) was used to identify habitat cores from the predicted intensity of the Integrated model framework. Results: Important variables to model the distribution of Baird’s tapir included land cover, human pressure and topography. Accounting for spatial bias in the presence data affected which variables were important in the model. Maxent and the Integrated model produced predictive maps with similar patterns and were considered to be more in agreement with expert knowledge compared to the PO and PA models.

Main conclusions: Total abundance as predicted by the model was higher than expert opinion on the species, but local density estimates from our model were similar to available independent assessments. We suggest that these results warrant further validation and testing through collection of independent test data, development of more precise predictor layers and improvements to the model framework.


5.
Libro
Mapping species distributions: spatial inference and prediction / Janet Franklin ; with contributions by Jennifer A. Miller
Franklin, Janet (1959-) ; Miller, Jennifer A. (coaut.) ;
Cambridge : Cambridge University Press , 2009
Clasificación: 574.9 / F7
Bibliotecas: Campeche , Chetumal , San Cristóbal
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Índice | Resumen en: Inglés |
Resumen en inglés

Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management

Índice

Preface page
Acknowledgments
Part I: History and ecological basis of species distribution modeling
1 Species distribution modeling
1.1 Introduction
1.2 What is in a name?
1.2.1 Niche models
1.2.2 Habitat suitability models
1.3 Heightened interest in species distribution modeling
1.4 What is species distribution modeling and how is this book organized?
1.5 Why model species distributions?
1.5.1 Reserve design and conservation planning
1.5.2 Impact assessment and resource management
1.5.3 Ecological restoration and ecological modeling
1.5.4 Risk and impacts of invasive species including pathogens
1.5.5 Effects of global warming on biodiversity and ecosystems
2 Why do we need species distribution models?
2.1 Introduction
2.2 Mapping species – atlas projects and natural history collections
2.2.1 Grid-based atlases of species distributions
2.2.2 Species locations from natural history collections
2.3 Direct interpolation of species data
2.4 Summary – what do we really want?
3 Ecological understanding of species distributions
3.1 Introduction
3.2 The species niche concept
3.2.1 The species niche in environmental and geographical space
3.2.2 The species niche in evolutionary time
3.2.3 Niche or resource selection function?
3.3 Factors controlling species distributions
3.4 Environmental gradients and species response functions
3.5 Conceptual models of environmental factors controlling species distributions
3.5.1 Heat, moisture, light, nutrients, and the distribution of plants
3.5.2 Hierarchical and nested scales of factors affecting species distributions
3.5.3 Environmental factors affecting species diversity and life form
3.6 Summary
Part II: The data needed for modeling species distributions
4 Data for species distribution models: the biological data
4.1 Introduction – the species data model

4.2 Spatial prediction of species distributions: what is being predicted?
4.3 Scale concepts related to species data
4.4 Spatial sampling design issues related to species data
4.4.1 Probability sample designs
4.4.2 How many observations?
4.4.3 Species prevalence
4.4.4 Sample resolution
4.4.5 Study area extent and sampling environmental gradients
4.4.6 Using existing data for modeling
4.4.7 Species presence-only data
4.5 Temporal sampling issues and species data
4.5.1 Species detectability
4.5.2 Historical species data
4.6 Summary
5 Data for species distribution models: the environmental data
5.1 Introduction
5.2 Spatial data representing primary environmental regimes
5.2.1 Climate maps
5.2.2 Digital terrain maps
5.2.3 Soil factors and geology maps
5.3 Other environmental data for SDM
5.3.1 Vegetation maps
5.3.2 Disturbance and disturbance history
5.3.3 Remote sensing
5.3.4 Landscape pattern
5.3.5 The distributions of other species
5.4 Environmental data for aquatic and marine species
5.5 Summary
Part III: An overview of the modeling methods
6 Statistical models – modern regression (Janet Franklin and Jennifer A. Miller)
6.1 Introduction
6.2 The linear model
6.3 Generalized linear models
6.3.1 Transformations of the predictors
6.3.2 Model estimation
6.3.3 Model selection and predictor collinearity
6.3.4 Use of GLMs in species distribution modeling
6.3.5 Summary
6.4 Generalized additive models
6.4.1 Use of GAMs in species distribution modeling
6.4.2 Summary
6.5 Multivariate adaptive regression splines
6.5.1 Use of MARS in species distribution modeling

6.6 Multivariate statistical approaches to SDM
6.7 Bayesian approaches to SDM
6.8 Spatial autocorrelation and statistical models of species distributions
6.8.1 Consequences of SAC data
6.8.2 Solutions to SAC data
Autoregression
Applications of autoregression methods in SDM
Generalized estimating equations and generalized linear mixed models
Geographically weighted regression
Spatial filtering methods
6.8.3 Summary
7 Machine learning methods
7.1 Introduction
7.2 Decision tree-based methods
7.2.1 How decision trees work
7.2.2 When are decision trees useful?
7.2.3 A note about multivariate decision trees
7.2.4 Application of decision trees in species distribution modeling
7.3 Ensemble methods applied to decision trees – bagging, boosting, and random forests
7.4 Artificial neural networks
7.5 Genetic algorithms
7.6 Maximum entropy
7.7 Support vector machines
7.8 Ensemble forecasting and consensus methods
7.9 Summary
8 Classification, similarity and other methods for presence-only data
8.1 Introduction
8.2 Envelope models and similarity measures
8.2.1 Environmental envelope methods
8.2.2 Environmental distance methods
8.3 Species presence versus habitat availability
8.3.1 Resource selection functions using descriminative models
8.3.2 Ecological niche factor analysis
8.3.3 Genetic algorithms for rule production (GARP)
8.3.4 Maximum entropy
8.4 Habitat suitability indices and other expert models
8.5 Summary
Part IV: Model evaluation and implementation
9 Model evaluation
9.1 Introduction
9.2 Data for model evaluation
9.3 Measures of prediction errors
9.3.1 Threshold-dependent measures of accuracy

AUC
Correlation
Calibration
9.3.4 Evaluating presence-only models
9.3.5 Spatial distribution of model uncertainty and error
9.4 Summary
10 Implementation of species distribution models
10.1 Introduction
10.2 Species attributes
10.3 Species data
10.4 Environmental data and scale
Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management
10.5 Modeling methods
10.6 Model evaluation
10.7 Summary – beyond species distribution modeling
References
Index