Establishment patterns in a secondary tree line ecotone

On semi-open pre-alpine fen pastures Alder encroachment creates a dynamic mosaic of grassland and woodland, which is rich in ecotones from fen to Carr. The structural diversity in colonisation patterns of Alder on fens suggests a dependency on multiple environmental drivers. Unidirectional progressive ecotone development provides an opportunity to address a current deficit in understanding successional patterns, i.e. process-pattern relationships in a multiple factor regime.We developed an individual-based model of Alder establishment on fen grassland to investigate the dependency of encroachment patterns upon seed production, dispersal distances and safe site availability. The purpose of the model is to provide a causal understanding of establishment patterns of Alder. In the model, all life processes of Alder individuals were parameterised with field data. This allowed us to strictly perform bottom-up simulations and successfully check plausibility by comparing simulated establishment patterns of cohorts with observed ecotone structures.Simulation results show that establishment patterns strongly depend on environmental drivers. Spatial progression of Alder encroachment and width of ecotones, respectively, mainly depend on wind speed during seed dispersal. Dense establishment of Alder leading to community change from fen grassland to Carr, requires windows of opportunity, which are defined by the rare coincidence of widespread dispersal, high seed production and favorable establishment conditions. Life-history traits of Alder (mast year cycle, high seed weight, weak establishment in fen) spatially and temporarily constrain the encroachment process. The structural diversity of long-term encroachment patterns is explained by the event-driven character of encroachment.Modelling individual establishment pathways of seedlings starting from germination revealed an endogenous stochasticity in establishment patterns emerging from low seed densities in the tail of the dispersal function. We conclude an inherent stochastic structure of dispersal-limited tree line ecotones, which limits reconstruction of processes from patterns.In order to describe long-term successional patterns of Alder encroachment at landscape scale, we propose the combination of two concepts: deterministic “patch-movement” of Alder woodland driven by continuous ecotone migration together with rare and stochastic “infiltration” of single Alder trees into open fen grasslands. Conservation management can control predictable “patch-movement” by cutting off maturing saplings around existing Alder woods. But the preservation of the actual large proportion of open grassland in fen pastures from infiltrating Alder seedlings and from the subsequent shift of the pasture to a densely wooded state would require mowing additionally to extensive grazing.     

The power of simulating experiments

Addressing complex ecological research questions often requires complex empirical experiments. However, due to the logistic constraints of empirical studies there is a trade-off between the complexity of experimental designs and sample size. Here, we explore if the simulation of complex ecological experiments including stochasticity-induced variation can aid in alleviating the sample size limitation of empirical studies. One area where sample size limitations constrain empirical approaches is in studies of the above- and belowground controls of trophic structure. Based on a rule- and individual-based simulation model on the effect of above- and belowground herbivores and their enemies on plant biomass, we evaluate the reliability of biomass estimates, the probability of experimental failure in terms of missing values, and the statistical power of biomass comparisons for a range of sample sizes. As expected, we observed superior performance of setups with sample sizes typical of simulations (n = 1000) as compared to empirical experiments (n = 10). At low sample sizes, simulated standard errors were smaller than expected from statistical theory, indicating that stochastic simulation models may be required in those cases where it is not possible to perform pilot studies for determining sample sizes. To avoid experimental failure, a sample size of n = 30 was required. In conclusion, we propose that the standard tool box of any ecologist should comprise a combination of simulation and empirical approaches to benefit from the realism of empirical experiments as well as the statistical power of simulations.     

Simple rules for ranking and optimally managing metapopulations

We present two ‘rules of thumb’ for metapopulation management. The first identifies an explicit formula for the persistence time of the population, and thus enables the population manager to form a priority species ranking by identifying those species most at risk of extinction. The second identifies an optimal management strategy that gives direction on how to alter the colonisation rate (creation or improvement of habitat corridors) and local extinction rate (restoring habitat quality or expanding habitat) in order to maximise the persistence time under a budgetary constraint. We employ a simple stochastic version of Levins (1969) metapopulation model, which is first calibrated to a more realistic spatial model. Our rules are tested on computer-generated patch networks and a model for malleefowl (Leipoa ocellata) in the Bakara region of South Australia.     

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

A primary goal in ecotoxicology is the prediction of population-level effects of contaminant exposure based on individual-level response. Assessment of toxicity at the population level has predominately focused on the population growth rate (PGR), but the PGR may not be a relevant toxicological endpoint for populations at equilibrium. Equilibrium population size may be a more meaningful endpoint than the PGR because a population with smaller equilibrium size is more susceptible to the negative effects of environmental variability. We address the individual-to-population extrapolation problem with modeling utilizing classical mathematical theory. We developed and analyzed a general model applicable to many freshwater fish species, that includes density-dependent juvenile survival and additional juvenile mortality due to toxicity exposure, and we quantified effect on equilibrium population size as a means of assessing toxicity. Individual-level effects are typically greater than population-level effects until the individual effect is large, due to compensatory density-dependent relationships. These effects are sensitive to the recruitment potential of a population, in particular the low-density first-year survival rate S_b. Assuming high S_b could result in underestimating effects of population-level toxicity. The equilibrium size depends directly on S_b, the reproductive potential, the toxin concentration at which mean mortality is 50% (LC₅₀), and the rate at which individual mortality increases with increasing toxin concentration. More experimental data are needed to decrease the uncertainty in estimating these parameters. We then used existing data for selenium toxicity in bluegill sunfish to parameterize a simulation version of the model as an example to assess the effects of environmental stochasticity on toxicity response. Effects of environmental variability resulted in simulated extinctions at much lower toxin concentrations than predicted deterministically.