Toshinori Okuyama

Rice University, Houston, TX, United States

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Publications (11)87.23 Total impact

  • Toshinori Okuyama
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    ABSTRACT: Theoretical models of intraguild predation (IGP) predict that IGP decreases the effectiveness of biological control while many empirical studies do not agree with this prediction. In this study, I discuss the importance of explicit consideration of multiple resource species that has been neglected in most theoretical IGP models. In the previous models of IGP, a single resource species represented the pest species. However, there are multiple resource species (e.g., multiple pest species or aggregates of pest and non-pest species) in real systems. This study shows that models with multiple resource species can predict a variety of outcomes including those consistent with the empirical observations. The explicit consideration of resource species is useful for the future development of theories in biological control.
    BioControl 01/2009; 54(1):3-7. · 2.22 Impact Factor
  • Toshinori Okuyama, J Nathaniel Holland
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    ABSTRACT: Key advances are being made on the structures of predator-prey food webs and competitive communities that enhance their stability, but little attention has been given to such complexity-stability relationships for mutualistic communities. We show, by way of theoretical analyses with empirically informed parameters, that structural properties can alter the stability of mutualistic communities characterized by nonlinear functional responses among the interacting species. Specifically, community resilience is enhanced by increasing community size (species diversity) and the number of species interactions (connectivity), and through strong, symmetric interaction strengths of highly nested networks. As a result, mutualistic communities show largely positive complexity-stability relationships, in opposition to the standard paradox. Thus, contrary to the commonly-held belief that mutualism's positive feedback destabilizes food webs, our results suggest that interplay between the structure and function of ecological networks in general, and consideration of mutualistic interactions in particular, may be key to understanding complexity-stability relationships of biological communities as a whole.
    Ecology Letters 04/2008; 11(3):208-16. · 17.95 Impact Factor
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    Toshinori Okuyama
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    ABSTRACT: Species interactions are central to the structure and dynamics of biological communities. Recently, of particular interest, is the analysis of ecological networks where the number of species to species interactions vary depending on the degree of specialization. For mutualistic networks, species degree has been suggested to follows a power distribution or a truncated power distribution. In this paper, I discuss previously estimated parameters and associated model selection may be unreliable. I use the likelihood approach and compare the results from previous findings and show that the parameter estimates as well as model selection results are indeed very different. Furthermore, the likelihood approach reveals that many mutualistic networks do not follow either power distribution or truncated power distribution.
    Ecological Complexity. 01/2008;
  • Toshinori Okuyama
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    ABSTRACT: Consumer–resource interactions with intraguild predation (IGP) were studied in a spatial setting (i.e., predators catch prey and individuals reproduce within local neighborhoods only). Pair approximation (a method for deriving ordinary differential equations that approximate the dynamics of a community that interacts in a lattice environment) was used to study the effect of spatially structured species interactions. An individual-based computer simulation was used to extend the study to a case with spatially variable resource densities. The qualitative results of the pair approximation model were similar to those of the corresponding non-spatial model. However, the spatial model predicted coex((istence over a wider range of parameters than the non-spatial model when intraguild prey are nutritionally valuable to intraguild predators. Spatially heterogeneous resource distributions and spatially structured interaction could overturn the qualitative predictions of non-spatial models.
    Basic and Applied Ecology - BASIC APPL ECOL. 01/2008; 9(2):135-144.
  • Toshinori Okuyama, Benjamin M Bolker
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    ABSTRACT: Indirect effects, whether density-mediated (DMII) or trait-mediated (TMII), have been recognized as potentially important drivers of community dynamics. However, empirical studies that have attempted to detect TMII or to quantify the relative strength of DMII and TMII in short-term studies have used a range of different metrics. We review these studies and assess both the consistency of a variety of different metrics and their robustness to (or ability to detect) ecological phenomena such as the dependence of forager behaviour on conspecific density. Quantifying indirect effects over longer time scales when behaviour and population density vary is more challenging, but also necessary if we really intend to incorporate indirect effects into predictions of long-term community dynamics; we discuss some problems associated with this effort and conclude with general recommendations for quantifying indirect effects.
    Ecology Letters 05/2007; 10(4):264-71. · 17.95 Impact Factor
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    ABSTRACT: Traditional mixed stock analyses use morphological, chemical, or genetic markers measured in several source populations and in a single mixed population to estimate the proportional contribution of each source to the mixed population. In many systems, however, different individuals from a particular source population may go to a variety of mixed populations. Now that data are becoming available from (meta)populations with multiple mixed stocks, the need arises to estimate contributions in this 'many-to-many' scenario. We suggest a Bayesian hierarchical approach, an extension of previous Bayesian mixed stock analysis algorithms, that can estimate contributions in this case. Applying the method to mitochondrial DNA data from green turtles (Chelonia mydas) in the Atlantic gives results that are largely consistent with previous results but makes some novel points, e.g. that the Florida, Bahamas and Corisco Bay foraging grounds have greater contributions than previously thought from distant foraging grounds. More generally, the 'many-to-many' approach gives a more complete understanding of the spatial ecology of organisms, which is especially important in species such as the green turtle that exhibit weak migratory connectivity (several distinct subpopulations at one end of the migration that mix in unknown ways at the other end).
    Molecular Ecology 03/2007; 16(4):685-95. · 6.28 Impact Factor
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    ABSTRACT: Bascompte et al. (Reports, 21 April 2006, p. 431) used network asymmetries to explain mathematical conditions necessary for stability in historic models of mutualism. The Lotka-Volterra equations they used artificially created conditions in which some factor, such as asymmetric interaction strengths, is necessary for community coexistence. We show that a more realistic model incorporating nonlinear functional responses requires no such condition and is consistent with their data.
    Science 10/2006; 313(5795):1887; author reply 1887. · 31.20 Impact Factor
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    Toshinori Okuyama, Benjamin M. Bolker
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    ABSTRACT: Many species of sea turtles spend part of their life cycle gathered in large feeding aggregations that combine individuals from widely separated rookery populations. Biologists have applied methods of mixed-stock analysis to mitochondrial DNA samples from rookeries and mixed populations to estimate the contributions of different rookeries to the mixed stock. These methods are limited by the amount of genetic overlap between rookeries and fail to incorporate ecological covariates such as rookery size and location within major ocean currents that are strongly suspected to affect rookery contributions. A new hierarchical Bayesian model for rookery contributions incorporates these covariates (and potentially others) to draw stronger conclusions from existing data. Applying the model to various simple scenarios shows that, in some cases, it can accurately estimate turtle origins even when turtles come from rookeries with high degrees of genetic overlap. Applying the model to more complex simulations shows that it performs well in a wide range of scenarios. Applying the model to existing data on green turtles (Chelonia mydas) narrows confidence intervals but does not change point estimates significantly. Applying it to loggerhead turtles (Caretta caretta) strengthens the dominance of the large rookery in south Florida, and brings estimates from a small data set on sea turtle strandings into line with those from rookery data. Used appropriately, hierarchical Bayesian methods offer great potential for introducing multiple levels of variation and ecological covariates into ecological models.
    Ecological Applications - ECOL APPL. 01/2005; 15(1):315-325.
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    ABSTRACT: Juvenile loggerhead turtles (Caretta caretta) from West Atlantic nesting beaches occupy oceanic (pelagic) habitats in the eastern Atlantic and Mediterranean, whereas larger juvenile turtles occupy shallow (neritic) habitats along the continental coastline of North America. Hence the switch from oceanic to neritic stage can involve a trans-oceanic migration. Several researchers have suggested that at the end of the oceanic phase, juveniles are homing to feeding habitats in the vicinity of their natal rookery. To test the hypothesis of juvenile homing behaviour, we surveyed 10 juvenile feeding zones across the eastern USA with mitochondrial DNA control region sequences (N = 1437) and compared these samples to potential source (nesting) populations in the Atlantic Ocean and Mediterranean Sea (N = 465). The results indicated a shallow, but significant, population structure of neritic juveniles (PhiST = 0.0088, P = 0.016), and haplotype frequency differences were significantly correlated between coastal feeding populations and adjacent nesting populations (Mantel test R2 = 0.52, P = 0.001). Mixed stock analyses (using a Bayesian algorithm) indicated that juveniles occurred at elevated frequency in the vicinity of their natal rookery. Hence, all lines of evidence supported the hypothesis of juvenile homing in loggerhead turtles. While not as precise as the homing of breeding adults, this behaviour nonetheless places juvenile turtles in the vicinity of their natal nesting colonies. Some of the coastal hazards that affect declining nesting populations may also affect the next generation of turtles feeding in nearby habitats.
    Molecular Ecology 01/2005; 13(12):3797-808. · 6.28 Impact Factor
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    ABSTRACT: The contributions of different sea turtle rookeries to mixed-stock populations on foraging grounds can only be estimated by indirect methods such as analysis of mito-chondrial DNA samples from the mixed stocks and rookery populations. We explain and evaluate methods for genetic stock estimation using simulations and data from previous studies. We focus on Markov Chain Monte Carlo (MCMC) estimation, a relatively new method. MCMC differs from older combinations of maximum likelihood (ML) with non-parametric bootstrapping in (1) using a Bayesian prior to quantify previous knowledge; (2) taking account of multiple modes in the probability distribution of contributions; and (3) incorporating sampling error more flexibly, allowing for the possibility that rare haplotypes actually present in a particular rookery were not detected in a small sample. In the context of sea turtle stock analysis, the differences in point estimates between ML and MCMC methods are relatively small, but MCMC gives wider and more accurate confidence limits than ML with bootstrapping, which tends to underestimate small contributions as zero.
    Ecological Applications 01/2003; 13:763-775. · 3.82 Impact Factor
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    Toshinori Okuyama
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    ABSTRACT: The role of individual behavioral variation in community dynamics was studied. Behavioral variation in this study does not refer to differences in average responses (e.g., average response between presence and absence of antipredator behavior). Rather it refers to the variation around the average response that is not explained by trivial experimental treatments. First, the effect of behavioral variation was examined based on Jensen’s inequality. In cases of commonly used modeling framework with type II functional response, neglecting behavioral variation (a component of encounter rate) causes overestimation of predation effects. The effect of this bias on community processes was examined by incorporating the behavioral variation in a commonly used consumer-resource model (Rosenzweig–MacArthur model). How such a consideration affects a model prediction (paradox of enrichment) was examined. The inclusion of behavioral variation can both quantitatively and qualitatively alter the model characteristics. Behavioral variation can substantially increase the stability of the community with respect to enrichment.
    Ecological Research 23(4):665-671. · 1.55 Impact Factor

Publication Stats

372 Citations
212 Downloads
559 Views
87.23 Total Impact Points

Institutions

  • 2008–2009
    • Rice University
      • Department of Ecology and Evolutionary Biology
      Houston, TX, United States
  • 2003–2008
    • University of Florida
      Gainesville, Florida, United States