Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications
The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate...
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| Vydané v: | PloS one Ročník 5; číslo 11; s. e15002 |
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| Hlavní autori: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
Public Library of Science
22.11.2010
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.
Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.
We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. |
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| AbstractList | The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.
Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.
We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.BACKGROUNDThe movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.METHODOLOGY AND PRINCIPAL FINDINGSAerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.CONCLUSIONS AND SIGNIFICANCEWe present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. |
| Audience | Academic |
| Author | Winkelhagen, Annemarie J. S. Walsh, Peter D. Bohlman, Stephanie A. Jansen, Patrick A. Caillaud, Damien Garzon-Lopez, Carol X. Scarpino, Samuel V. Crofoot, Margaret C. |
| AuthorAffiliation | 4 Department of Migration and Immuno-ecology, Max Planck Institute for Ornithology, Radolfzell, Germany 3 Smithsonian Tropical Research Institute, Panamá, República de Panamá University of Western Ontario, Canada 7 Community and Conservation Ecology Group, University of Groningen, Haren, The Netherlands 5 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America 2 Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany 6 Forest Ecology and Forest Management Group, Wageningen University, Wageningen, The Netherlands 8 VaccinApe, Bethesda, Maryland, United States of America 1 Section of Integrative Biology, University of Texas at Austin, Austin, Texas, United States of America |
| AuthorAffiliation_xml | – name: University of Western Ontario, Canada – name: 8 VaccinApe, Bethesda, Maryland, United States of America – name: 4 Department of Migration and Immuno-ecology, Max Planck Institute for Ornithology, Radolfzell, Germany – name: 5 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America – name: 2 Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany – name: 3 Smithsonian Tropical Research Institute, Panamá, República de Panamá – name: 7 Community and Conservation Ecology Group, University of Groningen, Haren, The Netherlands – name: 6 Forest Ecology and Forest Management Group, Wageningen University, Wageningen, The Netherlands – name: 1 Section of Integrative Biology, University of Texas at Austin, Austin, Texas, United States of America |
| Author_xml | – sequence: 1 givenname: Damien surname: Caillaud fullname: Caillaud, Damien – sequence: 2 givenname: Margaret C. surname: Crofoot fullname: Crofoot, Margaret C. – sequence: 3 givenname: Samuel V. surname: Scarpino fullname: Scarpino, Samuel V. – sequence: 4 givenname: Patrick A. surname: Jansen fullname: Jansen, Patrick A. – sequence: 5 givenname: Carol X. surname: Garzon-Lopez fullname: Garzon-Lopez, Carol X. – sequence: 6 givenname: Annemarie J. S. surname: Winkelhagen fullname: Winkelhagen, Annemarie J. S. – sequence: 7 givenname: Stephanie A. surname: Bohlman fullname: Bohlman, Stephanie A. – sequence: 8 givenname: Peter D. surname: Walsh fullname: Walsh, Peter D. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21124927$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2010 Public Library of Science 2010 Caillaud et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Caillaud et al. 2010 Wageningen University & Research |
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| DOI | 10.1371/journal.pone.0015002 |
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| Snippet | The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model... Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most... Background - The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most... Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most... |
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| SubjectTerms | Aerial photography Agriculture Algorithms Animal models Animals approximate bayesian computation Availability behavior Biodiversity Biology Canopies Computer Science Computer Simulation Crop production Dipteryx - growth & development dipteryx-panamensis Dynamical systems Earth Sciences Ecology Ecology - methods el-nino Environmental protection Evolutionary biology Famine Food Food resources Foraging behavior Forest management Fruit - growth & development Fruits Geography Geospatial data Global positioning systems GPS habitat selection Habitats Heterogeneity Imagery Infectious diseases Keystone species Methods Models, Biological Monte Carlo Method movement patterns Ocean currents Panama Phenology Plant species Population Dynamics Population genetics recruitment Remote sensing Resource availability Satellite navigation systems seed dispersal Simulation Spatial distribution Species Stochasticity Stress concentration Surveillance Temporal distribution Temporal variations Trees Trees - growth & development Tropical Climate tropical forest Tropical forests Variation Wild animals |
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| Title | Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications |
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