Abstract
Context
The switching pattern between behavioral modes provides a mechanistic basis for understanding how animals perceive and memorize the habitat quality in their home ranges.
Objectives
We assessed if Magellanic woodpeckers (Campephilus magellanicus) move based on habitat quality at local (neighboring trees) and home range scales.
Methods
We used state-space models to examine the relationship between remotely-sensed estimates of habitat quality (tree decay) and movement of adult woodpeckers tracked with GPS telemetry in southern Chile.
Results
Woodpeckers spent most time (> 80%) in the area-restricted search (ARS) mode in contrast to the exploratory transient mode, characterized by frequent directional displacements (> 50 m). The extent to which individuals switched between behavioral modes was related to habitat quality at different scales. Woodpeckers switched to and remained in the ARS mode when encountering moderate levels of heterogeneity in habitat quality. At very low or high heterogeneity levels, however, individuals switched to and remained in the transient mode, respectively. Likewise, as habitat quality declined locally and across home range, woodpeckers were more likely to adopt a transient mode.
Conclusions
Although woodpeckers seemed to easily perceive and memorize habitat quality at different spatial scales, our results suggest that spatial memory will less effective under extreme levels of habitat heterogeneity.
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References
Avgar T, Baker JA, Brown GS, Hagens JS, Kittle AM, Mallon EE, McGreer MT, Mosser A, Newmaster SG, Patterson BR, Reid DEB, Rodgers AR, Shuter J, Street GM, Thompson I, Turetsky MJ, Wiebe PA, Fryxell JM (2015) Space-use behaviour of woodland caribou based on a cognitive movement model. J Anim Ecol 84:1059–1070
Barraquand F, Benhamou S (2008) Animal movements in heterogeneous landscapes: identifying profitable places and homogeneous movement bouts. Ecology 89:3336–3348
Berbert JM, Fagan WF (2012) How the interplay between individual spatial memory and landscape persistence can generate population distribution patterns. Ecol Complex 12:1–12
Berger-Tal O, Bar-David S (2015) Recursive movement patterns: review and synthesis across species. Ecosphere 6(9):1–12
Bestley S, Jonsen ID, Hindell MA, Guinet C, Charrassin JB (2013) Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator. Proc R Soc Lond B 280(1750):20122262
Bestley S, Jonsen ID, Hindell MA, Harcourt RG, Gales NJ (2015) Taking animal tracking to new depths: synthesizing horizontal–vertical movement relationships for four marine predators. Ecology 96:417–427
Beyer HL, Morales JM, Murray D, Fortin MJ (2013) The effectiveness of Bayesian state-space models for estimating behavioural states from movement paths. Methods Ecol Evol 4:433–441
Breed GA, Jonsen ID, Myers RA, Bowen WD, Leonard ML (2009) Sex-specific, seasonal foraging tactics of adult grey seals (Halichoerus grypus) revealed by state-space analysis. Ecology 90:3209–3221
Brooks CJ, Harris S (2008) Directed movement and orientation across a large natural landscape by zebras, Equus burchelli antiquorum. Anim Behav 76:277–285
Burns JG, Thomson JD (2005) A test of spatial memory and movement patterns of bumblebees at multiple spatial and temporal scales. Behav Ecol 17:48–55
Calenge C (2006) The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecol Model 197:516–519
Chazarreta L, Ojeda V, Lammertink M (2012) Morphological and foraging behavioral differences between sexes of the Magellanic woodpecker (Campephilus magellanicus). Ornitol Neotrop 23:529–544
Cobbold CA, Lutscher F (2014) Mean occupancy time: linking mechanistic movement models, population dynamics and landscape ecology to population persistence. J Math Biol 68:549–579
Doherty TS, Driscoll DA (2018) Coupling movement and landscape ecology for animal conservation in production landscapes. Proc R Soc Lond B. https://doi.org/10.1098/rspb.2017.2272
Doster RH, James DA (1998) Home range size and foraging habitat of red-cockaded woodpeckers in the Ouachita Mountains of Arkansas. Wilson Bull 110:110–117
Duron Q, Jiménez JE, Vergara PM, Soto GE, Lizama M, Rozzi R (2018) Intersexual segregation in foraging microhabitat use by Magellanic Woodpeckers (Campephilus magellanicus): seasonal and habitat effects at the world’s southernmost forests. Aust Ecol 43:25–34
Fagan WF, Lewis MA, Auger-Methe M, Avgar T, Benhamou S, Breed G, LaDage L, Schlägel UE, Tang W, Papastamatiou Y, Forester J, Mueller T (2013) Spatial memory and animal movement. Ecol Lett 16:1316–1329
Folse LJ, Packard JM, Grant WE (1989) AI modelling of animal movements in a heterogeneous habitat. Ecol Model 46:57–72
Fortin JA Merkle, Sigaud M, Cherry SG, Plante S, Drolet A, Labrecque M (2015) Temporal dynamics in the foraging decisions of large herbivores. Anim Prod Sci 55:376–383
Franzreb KE (2006) Implications of home-range estimation in the management of red-cockaded woodpeckers in South Carolina. For Ecol Manag 228:274–284
Fryxell JM, Hazell M, Borger L, Dalziel BD, Haydon DT, Morales JM, McIntosh T, Rosatte RC (2008) Multiple movement modes by large herbivores at multiple spatiotemporal scales. Proc Natl Acad Sci 105:19114–19119
Gelman A, Rubin DB (1992) Inference from iterative simulation using multiple sequences. Stat Sci 7:457–472
Horne JS, Garton EO, Krone SM, Lewis JS (2007) Analyzing animal movements using Brownian bridges. Ecology 88:2354–2363
Janson CH (1998) Experimental evidence for spatial memory in foraging wild capuchin monkeys, Cebus apella. Anim Behav 55:1229–1243
Johnson AR, Wiens JA, Milne BT, Crist TO (1992) Animal movements and population dynamics in heterogeneous landscapes. Landscape Ecol 7:63–75
Jonsen I (2016) Joint estimation over multiple individuals improves behavioural state inference from animal movement data. Sci Rep 6:20625
Jonsen ID, Basson M, Bestley S, Bravington MV, Patterson TA, Pedersen MW, Thomson R, Thygesen UH, Wotherspoon SJ (2013) State-space models for bio-loggers: a methodological road map. Deep Sea Res Part II 88:34–46
Jonsen ID, Flemming JM, Myers RA (2005) Robust state-space modeling of animal movement data. Ecology 86:2874–2880
Jonsen ID, Myers RA, Flemming JM (2003) Meta-analysis of animal movement using state-space models. Ecology 84:3055–3063
Jonsen ID, Myers RA, James MC (2006) Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles. J Anim Ecol 75:1046–1057
Lima SL, Zollner PA (1996) Towards a behavioral ecology of ecological landscapes. Trends Ecol Evol 11:131–135
McClintock BT, Michelot T (2018) momentuHMM: r package for generalized hidden Markov models of animal movement. Methods Ecol Evol 9:1518–1530
McKellar AE, Langrock R, Walters JR, Kesler DC (2014) Using mixed hidden Markov models to examine behavioral states in a cooperatively breeding bird. Behav Ecol 26:148–157
McNamara JM, Houston AI (1987) Memory and the efficient use of information. J Theor Biol 125:385–395
Merzlyak MN, Gitelson AA, Chivkunova OB, Rakitin VY (1999) Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiol Plant 106:135–141
Morales JM, Ellner SP (2002) Scaling up animal movements in heterogeneous landscapes: the importance of behavior. Ecology 83:2240–2247
Morales JM, Haydon DT, Frair J, Holsinger KE, Fryxell JM (2004) Extracting more out of relocation data: building movement models as mixtures of random walks. Ecology 85:2436–2445
Morales JM, Fortin D, Frair JL, Merrill EH (2005) Adaptive models for large herbivore movements in heterogeneous landscapes. Landscape Ecol 20:301–316
Mueller T, Fagan WF (2008) Search and navigation in dynamic environments-from individual behaviors to population distributions. Oikos 117:654–664
Mueller T, Fagan WF, Grimm V (2011) Integrating individual search and navigation behaviors in mechanistic movement models. Theor Ecol 4:341–355
Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, Smouse PE (2008) A movement ecology paradigm for unifying organismal movement research. Proc Natl Acad Sci 105:19052–19059
Ojeda V, Chazarreta L (2014) Home range and habitat use by Magellanic Woodpeckers in an old-growth forest of Patagonia. Can J For Res 44:1265–1273
Ojeda VS, Chazarreta ML (2006) Provisioning of Magellanic Woodpecker (Campephilus magellanicus) nestlings with vertebrate prey. Wilson J Ornithol 118:251–254
Osbourn MS, Connette GM, Semlitsch RD (2014) Effects of fine-scale forest habitat quality on movement and settling decisions in juvenile pond-breeding salamanders. Ecol Appl 24:1719–1729
Ovaskainen O, Cornell SJ (2003) Biased movement at a boundary and conditional occupancy times for diffusion processes. J Appl Probab 40:557–580
Pasinelli G (2000) Oaks (Quercus sp.) and only oaks? Relations between habitat structure and home range size of the middle spotted woodpecker (Dendrocopos medius). Biol Conserv 93:227–235
Patterson TA, Thomas L, Wilcox C, Ovaskainen O, Matthiopoulos J (2008) State-space models of individual animal movement. Trends Ecol Evol 23:87–94
Pechacek P, d’Oleire-Oltmanns W (2004) Habitat use of the three-toed woodpecker in central Europe during the breeding period. Biol Conserv 116:333–341
Polansky L, Kilian W, Wittemyer G (2015) Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state-space models. Proc R Soc Lond B 282(1805):20143042
R Development Core Team (2017) R: a language and environment for statistical computing. The R Foundation for Statistical Computing, Vienna
Schick RS, Loarie SR, Colchero F, Best BD, Boustany A, Conde DA, Halpin PN, Joppa LN, McClellan CM, Clark JS (2008) Understanding movement data and movement processes: current and emerging directions. Ecol Lett 11:1338–1350
Schultz CB, Crone EE (2001) Edge-mediated dispersal behavior in a prairie butterfly. Ecology 82:1879–1892
Seeber G (2003) Satellite geodesy: foundations, methods, and applications. Walter de Gruyter, Berlin
Semeniuk CA, Musiani M, Hebblewhite M, Grindal S, Marceau DJ (2012) Incorporating behavioral–ecological strategies in pattern-oriented modeling of caribou habitat use in a highly industrialized landscape. Ecol Model 243:18–32
Short LL (1970) The habits and relationships of the Magellanic Woodpecker. Wilson Bull 82:115–129
Soto GE, Pérez-Hernández CG, Hahn IJ, Rodewald AD, Vergara PM (2017) Tree senescence as a direct measure of habitat quality: linking red-edge vegetation indices to space use by Magellanic woodpeckers. Remote Sens Environ 193:1–10
Soto GE, Vergara PM, Lizama ME, Celis C, Rozzi R, Duron Q, Hahn IJ, Jiménez JE (2012) Do beavers improve the habitat quality for Magellanic Woodpeckers in a subantartic forest of Cape Horn, Chile? Bosque 33:271–274
Soto GE, Vergara PM, Smiley A, Lizama ME, Moreira-Arce D, Vásquez RA (2016) Lethal agonistic behavior between two male Magellanic Woodpeckers Campephilus magellanicus observed in the Cape Horn area. Wilson J Ornithol 128:180–184
Spiegel O, Crofoot MC (2016) The feedback between where we go and what we know—information shapes movement, but movement also impacts information acquisition. Curr Opin Behav Sci 12:90–96
Spiegel O, Leu ST, Bull CM, Sih A (2017) What’s your move? Movement as a link between personality and spatial dynamics in animal populations. Ecol Lett 20:3–18
Stephens DW, Krebs JR (1986) Foraging theory. Princeton University Press, Cambridge
Su YS, Yajima M (2015) R2jags: Using R to run ‘JAGS’. R package version 0.5-7
Tingley MW, Wilkerson RL, Bond ML, Howell CA, Siegel RB (2014) Variation in home-range size of Black-backed Woodpeckers. Condor 116:325–340
Vergara P, Schlatter RP (2004) Magellanic woodpecker (Campephilus magellanicus) abundance and foraging in Tierra del Fuego, Chile. J Ornithol 145:343–351
Vergara PM, Meneses L, Saavedra M, Diaz F, Norambuena K, Fierro A, Rodewald A, Soto G (2017) Magellanic woodpeckers living in three national parks of southern Chile: habitat quality and population variation over the last two decades. Avian Conserv Ecol 12(2)
Vergara PM, Meneses LO, Grez AA, Quiroz MS, Soto GE, Pérez-Hernández CG, Diaz PA, Hahn IJ, Fierro A (2016b) Occupancy pattern of a long-horned beetle in a variegated forest landscape: linkages between tree quality and forest cover across spatial scales. Landscape Ecol 32:279–293
Vergara PM, Saura S, Pérez-Hernández CG, Soto GE (2015) Hierarchical spatial decisions in fragmented landscapes: modeling the foraging movements of woodpeckers. Ecol Model 300:114–122
Vergara PM, Soto GE, Moreira-Arce D, Rodewald AD, Meneses LO, Pérez-Hernández CG (2016a) Foraging behaviour in magellanic woodpeckers is consistent with a multi-scale assessment of tree quality. PLoS ONE 11:e0159096
Waser LT, Küchler M, Jütte K, Stampfer T (2014) Evaluating the potential of World-View-2 data to classify tree species and different levels of ash mortality. Remote Sens 6:4515–4545
Wells AG, Blair CC, Garton EO, Rice CG, Horne JS, Rachlow JL, Wallin DO (2014) The Brownian bridge synoptic model of habitat selection and space use for animals using GPS telemetry data. Ecol Model 273:242–250
Zuñiga-Reinoso A (2013) Revisión de los Cerambycidae (Coleoptera) de la región de Magallanes: Lista ilustrada. Anales del Instituto de la Patagonia 41:53–59
Acknowledgements
This study was funded by FONDECYT Grant 1180978 and Proyecto Fondo Fortalecimiento USA1799 (USACH). GES acknowledges W. Hochachka from the Cornell Lab of Ornithology and M. Nazar for their technical support and the Advanced Human Capital Program—CONICYT for supporting his research.
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Vergara, P.M., Soto, G.E., Rodewald, A.D. et al. Behavioral switching in Magellanic woodpeckers reveals perception of habitat quality at different spatial scales. Landscape Ecol 34, 79–92 (2019). https://doi.org/10.1007/s10980-018-0746-5
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DOI: https://doi.org/10.1007/s10980-018-0746-5