Aims Neutral theory consists of a suite of models that assume ecological equivalence among individual organisms.They have been most commonly applied to tropical forest tree communities either as null models or as appr...Aims Neutral theory consists of a suite of models that assume ecological equivalence among individual organisms.They have been most commonly applied to tropical forest tree communities either as null models or as approximations.Neutral models typically only include reproductive adults;therefore,fitting to empirical tree community data requires defining a reproductive-size threshold,which for trees is usually set arbitrarily to a diameter at breast height(DBH)of 100 mm.The inevitable exclusion of some reproductive adults and inclusion of some saplings cause a non-random sampling bias in neutral model fits.Here,we investigate this problem and resolve it by introducing simple age structure into a neutral model.Methods We compared the performance and sensitivity of DBH threshold of three variants of a spatially explicit neutral model:the traditional model,a model incorporating random sampling and a model with two distinct age classes—reproductive adults and saplings.In the age-structured model,saplings are offspring from adults that disperse according to a Gaussian dispersal kernel around the adults.The only extra parameter is the ratio of adults to saplings,which is not a free parameter but directly measurable.We used species–area relationships(SARs)to explore the predicted effect of saplings on the species richness at different scales in our model.We then evaluated the three model variations to find the parameters required to maintain the observed level of species richness in the 50-ha plot on Barro Colorado Island(BCI).We repeated our analysis filtering the data at different minimum tree-size thresholds in order to find the effect this threshold has on our results.Lastly,we used empirical species–individual relationships(SIRs)to test the pre-existing hypothesis that environmental filtering is the primary cause of differences between the assemblage of saplings and that of adults on BCI.Important Findings Our age-structured neutral model was characterized by SARs that were insensitive to the presence of saplings at large scales and highly sensitive to them at small scales.Both models without age structure were highly sensitive to the DBH threshold chosen in a way that could not be explained based on random samplings alone.The age-structured neutral model,which allowed for non-random sampling based on life stage,was consistent with species richness observations.Our analysis of empirical SIRs did not support environmental filtering as a dominant force,but it did show evidence for other differences between age classes.Age can now be easily incorporated into future studies of neutral models whenever there is a concern that a sample is not entirely composed of reproductive adult individuals.More generally,we suggest that modeling studies using tree data subject to a minimum size threshold should consider the sensitivity of their results to that threshold.展开更多
基金Engineering and Physical Sciences Research Council overseas postdoctoral research fellowship at the life sciences interface(EP/F043112/1 to J.R.)the Netherlands Organization for Scientific Research(NWO-ALW 864-07-007 to R.S.E.,NWOALW 863-07-008 to P.A.J.).
文摘Aims Neutral theory consists of a suite of models that assume ecological equivalence among individual organisms.They have been most commonly applied to tropical forest tree communities either as null models or as approximations.Neutral models typically only include reproductive adults;therefore,fitting to empirical tree community data requires defining a reproductive-size threshold,which for trees is usually set arbitrarily to a diameter at breast height(DBH)of 100 mm.The inevitable exclusion of some reproductive adults and inclusion of some saplings cause a non-random sampling bias in neutral model fits.Here,we investigate this problem and resolve it by introducing simple age structure into a neutral model.Methods We compared the performance and sensitivity of DBH threshold of three variants of a spatially explicit neutral model:the traditional model,a model incorporating random sampling and a model with two distinct age classes—reproductive adults and saplings.In the age-structured model,saplings are offspring from adults that disperse according to a Gaussian dispersal kernel around the adults.The only extra parameter is the ratio of adults to saplings,which is not a free parameter but directly measurable.We used species–area relationships(SARs)to explore the predicted effect of saplings on the species richness at different scales in our model.We then evaluated the three model variations to find the parameters required to maintain the observed level of species richness in the 50-ha plot on Barro Colorado Island(BCI).We repeated our analysis filtering the data at different minimum tree-size thresholds in order to find the effect this threshold has on our results.Lastly,we used empirical species–individual relationships(SIRs)to test the pre-existing hypothesis that environmental filtering is the primary cause of differences between the assemblage of saplings and that of adults on BCI.Important Findings Our age-structured neutral model was characterized by SARs that were insensitive to the presence of saplings at large scales and highly sensitive to them at small scales.Both models without age structure were highly sensitive to the DBH threshold chosen in a way that could not be explained based on random samplings alone.The age-structured neutral model,which allowed for non-random sampling based on life stage,was consistent with species richness observations.Our analysis of empirical SIRs did not support environmental filtering as a dominant force,but it did show evidence for other differences between age classes.Age can now be easily incorporated into future studies of neutral models whenever there is a concern that a sample is not entirely composed of reproductive adult individuals.More generally,we suggest that modeling studies using tree data subject to a minimum size threshold should consider the sensitivity of their results to that threshold.
