Modeling the spatial distribution and fruiting pattern of a key tree species in a neotropical forest: methodology and potential applications

• Published in: PloS one 2010-11, Vol.5 (11), p.e15002-e15002
• Main Authors: Caillaud, Damien, Crofoot, Margaret C, Scarpino, Samuel V, Jansen, Patrick A, Garzon-Lopez, Carol X, Winkelhagen, Annemarie J S, Bohlman, Stephanie A, Walsh, Peter D
• Format: Article
• Language: English
• Subjects: 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
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0015002

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.