80 research outputs found
Modelling population redistribution in a leaf beetle: an evaluation of alternative dispersal functions
No full text1. Dispersal is a fundamental ecological process, so spatial models require realistic dispersal kernels. We compare five different forms for the dispersal kernel of the tansy beetle Chrysolina graminis moving between patches of its host-plant (tansy Tanacetum vulgare) in a riparian landscape.
2. Multi-patch mark–recapture data were collected every 2 weeks over 2 years within a large network of patches and from 2226 beetles. Dispersal was common (28·4% of 880 recaptures after a fortnight) and was more likely over longer intervals, out of small patches, for females and during flooding. Interpatch movement rates did not differ between years and exhibited no density dependence. Dispersal distances were similar for males and females, in both years and over all intervals, with a median dispersal distance of just 9·8 m, although a maximum of 856 m was recorded.
3. A model of dispersal, where patches competed for dispersers based on their size and distance from the beetle's source patch (scaled by the dispersal kernel) was fitted to the field data with a maximum likelihood procedure and each of five alternative kernels. The best fitting had relatively extended tails of long-distance dispersal, while Gaussian and negative exponential kernels performed worst.
4. The model suggests that females disperse more commonly than males and that both are strongly attracted to large patches but do not differ between years, which are consistent with the empirical results. Model-predicted emigration and immigration rates and dispersal phenologies match those observed, suggesting that the model captured the major drivers of tansy beetle dispersal.
5. Although negative exponential and Gaussian kernels are widely used for their simplicity, we suggest that these should not be the models of automatic choice, and that fat-tailed kernels with relatively higher proportions of long-distance dispersal may be more realistic
Process from pattern in the distribution of an endangered leaf beetle
No full textWe investigated whether signals of known dispersal processes and habitat patch turnover could be detected in a snapshot of the distribution of the tansy leaf beetle Chrysolina graminis among patches of its host plant tansy Tanacetum vulgare. Beetle occupancy in 1305 patches was analysed using autologistic generalised additive models (GAMs). These model spatial autocorrelation with an autocovariate calculated as the distance-weighted rate of occupancy among neighbouring patches. The autocovariate that best explained beetle occupancy was one which represented the active search for patches during beetle dispersal, included a distance weight that closely matched a previously fitted dispersal kernel and had neighbourhood sizes encompassing ?95% of known dispersal distances. Autocovariates distinguishing between neighbours on the same and opposite riverbanks outperformed those that did not, revealing the river as a barrier to dispersal. Differentiating between up and downstream autocorrelation did not improve model fit, as is consistent with the beetle's lack of directional bias in dispersal. Habitat connectivity (the extent to which it was surrounded by other patches) did not appear to affect beetle occupancy in the field, while positive effects were found for distributions simulated from the GAM. We argue that this reflects a non-equilibrium distribution driven by slow responses to high rates of habitat patch turnover due to limited dispersal ability. Our findings suggest that presence/absence snapshots can reveal patterns of dispersal and be used to test whether species? ranges are at equilibrium. Such information is important for effective conservation so the possibility of inferring these patterns from distribution data is an appealing one
Landscape and fine-scale movements of a leaf beetle: the importance of boundary behaviour
No full textMovement underpins animal spatial ecology and is often modelled as habitat-dependent correlated random walks. Here, we develop such a model for the flightless tansy leaf beetle Chrysolina graminis moving within and between patches of its host plant tansy Tanacetum vulgare. To parameterize the model, beetle movement paths on timescales of minutes were observed in uniform plots of tansy and inter-patch matrix (meadow) vegetation. Movement lasted longer, covered greater distances and had narrower turning angles in the matrix. Simulations of the model emulated an independent two-season multi-patch mark–resight study at daily timescales and included variable boundary-mediated behaviour affecting the probability of leaving habitat patches. As boundaries in the model became stronger there were disproportionately large decreases in net displacements, inter-patch movements and the proportion of beetles in the matrix. The model produced realistic patterns of population-level displacement over periods up to 13 days with fully permeable boundaries for one dataset and strong boundaries for the other. This may be explained by the heights of the tansy patches in each study, as beetles will be unable to cross the boundary near the top of a patch that emerges from the matrix. The simulations demonstrate the important effects of boundary behaviour on displacement patterns and indicate temporal and spatial variability in permeability. Realistic models of movement must therefore include behaviour at habitat boundaries
Population fragmentation drives up genetic diversity in signals of individual identity
No full textMany species advertise their unique identity to conspecifics using dedicated individuality signals: one familiar example is human faces. But how unique in the global population do these signals need to be? While human faces are highly variable, each person interacts with many fewer individuals than are found in the total population. This raises the question of how evolutionary mechanisms drive up population-wide diversity when selection occurs at such a local level. We use an individual-based model in which individuals broadcast their identity and quality in separate, genetically-coded signals. Mimicking, for example, scent marking mammal species, females in the model assess males using the quality signal, then attempt to relocate the highest quality male using his identity signal. We ask how population fragmentation affects genetic diversity in the individual identity-signalling region under sexual selection, predicting one of two opposing outcomes: 1) divided populations evolve fewer signal variants globally, since repetition of signals is not costly when individuals interact only with local conspecifics, or 2) stochasticity in mutation and selection cause divergence among subpopulations, increasing the global number of signal variants. We show that local selection drives up global genetic diversity substantially in fragmented populations, even with extremely low rates of dispersal. Because new signal variants arise by mutation and then sweep through their subpopulation, a fragmented population has more global signal variation. This result furthers our understanding of how high levels of diversity in individuality signals are maintained
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