Ecology Letters (2010) 13: 716-727 Understanding the maintenance and origin of biodiversity is a formidable task, yet many ubiquitous ecological patterns are predicted by a surprisingly simple and ...widely studied neutral model that ignores functional differences between species. However, this model assumes that new species arise instantaneously as singletons and consequently makes unrealistic predictions about species lifetimes, speciation rates and number of rare species. Here, we resolve these anomalies - without compromising any of the original model's existing achievements and retaining computational and analytical tractability - by modelling speciation as a gradual, protracted, process rather than an instantaneous event. Our model also makes new predictions about the diversity of 'incipient' species and rare species in the metacommunity. We show that it is both necessary and straightforward to incorporate protracted speciation in future studies of neutral models, and argue that non-neutral models should also model speciation as a gradual process rather than an instantaneous one.
Clinical cancer imaging focuses on tumor growth rather than metastatic phenotypes. The microtubule-depolymerizing drug, Vinorelbine, reduced the metastatic phenotypes of microtentacles, reattachment ...and tumor cell clustering more than tumor cell viability. Treating mice with Vinorelbine for only 24 h had no significant effect on primary tumor survival, but median metastatic tumor survival was extended from 8 to 30 weeks. Microtentacle inhibition by Vinorelbine was also detectable within 1 h, using tumor cells isolated from blood samples. As few as 11 tumor cells were sufficient to yield 90% power to detect this 1 h Vinorelbine drug response, demonstrating feasibility with the small number of tumor cells available from patient biopsies. This study establishes a proof-of-concept that targeted microtubule disruption can selectively inhibit metastasis and reveals that existing FDA-approved therapies could have anti-metastatic actions that are currently overlooked when focusing exclusively on tumor growth.
All organisms grow. Numerous growth functions have been applied to a wide taxonomic range of organisms, yet some of these models have poor fits to empirical data and lack of flexibility in capturing ...variation in growth rate. We propose a new VBGF framework that broadens the applicability and increases flexibility of fitting growth curves. This framework offers a curve-fitting procedure for five parameterisations of the VBGF: these allow for different body-size scaling exponents for anabolism (biosynthesis potential), besides the commonly assumed 2/3 power scaling, and allow for supra-exponential growth, which is at times observed. This procedure is applied to twelve species of diverse aquatic invertebrates, including both pelagic and benthic organisms. We reveal widespread variation in the body-size scaling of biosynthesis potential and consequently growth rate, ranging from isomorphic to supra-exponential growth. This curve-fitting methodology offers improved growth predictions and applies the VBGF to a wider range of taxa that exhibit variation in the scaling of biosynthesis potential. Applying this framework results in reliable growth predictions that are important for assessing individual growth, population production and ecosystem functioning, including in the assessment of sustainability of fisheries and aquaculture.
Individual-based models, 'IBMs', describe naturally the dynamics of interacting organisms or social or financial agents. They are considered too complex for mathematical analysis, but computer ...simulations of them cannot give the general insights required. Here, we resolve this problem with a general mathematical framework for IBMs containing interactions of an unlimited level of complexity, and derive equations that reliably approximate the effects of space and stochasticity. We provide software, specified in an accessible and intuitive graphical way, so any researcher can obtain analytical and simulation results for any particular IBM without algebraic manipulation. We illustrate the framework with examples from movement ecology, conservation biology, and evolutionary ecology. This framework will provide unprecedented insights into a hitherto intractable panoply of complex models across many scientific fields.
Farming and the Fate of Wild Nature Green, Rhys E.; Cornell, Stephen J.; Jörn P. W. Scharlemann ...
Science (American Association for the Advancement of Science),
01/2005, Letnik:
307, Številka:
5709
Journal Article
Recenzirano
World food demand is expected to more than double by 2050. Decisions about how to meet this challenge will have profound effects on wild species and habitats. We show that farming is already the ...greatest extinction threat to birds (the best known taxon), and its adverse impacts look set to increase, especially in developing countries. Two competing solutions have been proposed: wildlife-friendly farming (which boosts densities of wild populations on farmland but may decrease agricultural yields) and land sparing (which minimizes demand for farmland by increasing yield). We present a model that identifies how to resolve the trade-off between these approaches. This shows that the best type of farming for species persistence depends on the demand for agricultural products and on how the population densities of different species on farmland change with agricultural yield. Empirical data on such density-yield functions are sparse, but evidence from a range of taxa in developing countries suggests that high-yield farming may allow more species to persist.
We use recently developed technical methods to study species–area relationships from a spatially explicit extension of Hubbell's neutral model on an infinite landscape. Our model includes variable ...dispersal distances and exhibits qualitatively different behaviour from the cases of nearest‐neighbour dispersal and finite periodic landscapes that have previously been studied. We show that different dispersal distances and even different dispersal kernels produce identical species–area curves up to rescaling of the two axes. This scaling property provides a straightforward method for fitting the model to empirical data. The species–area curves display all three phases observed empirically and enable the exponent describing the power law relationship for species–area curves to be identified as the gradient at the central phase. This exponent can take all values between 0 and 1 and is given by a simple function of the speciation rate, independent of all other model variables.
We simulate species-area curves (SACs) using a spatially explicit neutral model. These display three distinct phases with the central phase being well approximated by a "power law" where species ...richness (S) is related to area (A) by $S=cA^{z}$. If seeds are normally distributed in space about their parent, the power law phase of the SAC is unrealistically narrow, and implausibly large speciation rates are required to fit empirical data. However, if dispersal follows a more realistic "fat-tailed" distribution (where long-distance dispersal events are more likely) the SACs fit the empirical data better, have a power law that holds for a much broader range of areas, and require a dramatically smaller speciation rate than when dispersal is normally distributed. Neutral models with biologically plausible dispersal parameters and speciation rates lead to empirically realistic SACs.
Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm-based stochastic model of the current UK epidemic. The fine grain of the ...epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We show that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks. The other key dynamical component is long-tailed stochastic dispersal of infection, combining frequent local movements with occasional long jumps. We assess the history and possible duration of the epidemic, the performance of control strategies, and general implications for disease dynamics in space and time.
Dispersal polymorphism and mutation play significant roles during biological invasions, potentially leading to evolution and complex behaviour such as accelerating or decelerating invasion fronts. ...However, life-history theory predicts that reproductive fitness-another key determinant of invasion dynamics-may be lower for more dispersive strains. Here, we use a mathematical model to show that unexpected invasion dynamics emerge from the combination of heritable dispersal polymorphism, dispersal-fitness trade-offs, and mutation between strains. We show that the invasion dynamics are determined by the trade-off relationship between dispersal and population growth rates of the constituent strains. We find that invasion dynamics can be 'anomalous' (i.e. faster than any of the strains in isolation), but that the ultimate invasion speed is determined by the traits of, at most, two strains. The model is simple but generic, so we expect the predictions to apply to a wide range of ecological, evolutionary, or epidemiological invasions.
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