Interactive controls of herbivory and fluvial dynamics on landscape vegetation patterns on the Tanana River floodplain, interior Alaska

Aim  We examined the interactive effects of mammalian herbivory and fluvial dynamics on vegetation dynamics and composition along the Tanana River in interior Alaska.
Location  Model parameters were obtained from field studies along the Tanana River, Alaska between Fairbanks (64°50.50' N, 147°43.30' W) and Manley Hot Springs (65°0.0' N, 150°36.0' W).
Methods  We used a spatially explicit model of landscape dynamics (ALFRESCO) to simulate vegetation changes on a 1-year time-step. The model was run for 250 years and was replicated 100 times.
Results  Increases in herbivory decreased the proportion of early successional vegetation and increased the proportion of late successional vegetation on the simulated landscape. Erosion and accretion worked as antagonists to herbivory, increasing the amount of early successional vegetation and decreasing the amount of late successional vegetation. However, the interactive effects of herbivory and erosion/accretion were especially important in determining system response, particularly in early seral vegetation types. High erosion rates, when coupled with low herbivory, greatly increased the proportion of willow on the landscape. When coupled with high herbivory, however, they greatly increased the proportion of alder on the landscape. At low levels of herbivory, alder abundance peaked at intermediate levels of erosion/accretion.
Main conclusions  Neither erosion/accretion nor herbivory produced consistent landscape patterns that could be predicted independently of the other. These findings underscore the importance of the interactive effects of biotic and abiotic disturbances in shaping large-scale landscape vegetation patterns in boreal floodplain ecosystems – systems traditionally thought to be driven primarily by abiotic disturbance alone.     

Cascading costs: An economic nitrogen cycle

The chemical nitrogen cycle is becoming better characterized in terms of fluxes and reservoirs on a variety of scales. Galloway has demonstrated that reactive nitrogen can cascade through multiple ecosystems causing environmental damage at each stage before being denitrifled to N2. We propose to construct a parallel economic nitrogen cascade (ENC) in which economic impacts of nitrogen fluxes can be estimated by the costs associated with each stage of the chemical cascade. Using economic data for the benefits of damage avoided and costs of mitigation in the Chesapeake Bay basin, we have constructed an economic nitrogen cascade for the region. Since a single tonne of nitrogen can cascade through the system, the costs also cascade.Therefore evaluating the benefits of mitigating a tonne of reactive nitrogen released needs to consider the damage avoided in all of the ecosystems through which that tonne would cascade.The analysis reveals that it is most cost effective to remove a tonne of nitrogen coming from combustion since it has the greatest impact on human health and creates cascading damage through the atmospheric, terrestrial, aquatic and coastal ecosystems. We will discuss the implications of this analysis for determining the most cost effective policy option for achieving environmental quality goals.     

GM1 Ganglioside: In Vivo and In Vitro Trophic Actions on Central Neurotransmitter Systems

Abstract: There is now substantial evidence that GM1 ganglioside is effective in partially correcting the consequences of neuroinjury in a number of in vivo and in vitro model systems. Although the molecular mechanism(s) and the substrates for the neurotrophic activity of the gangliosides are not fully understood, the published experimental work suggests that GM1 has antineurotoxic, neuroprotective, and neurorestorative effects on various central neurotransmitter systems. This review focuses attention on studies reporting that GM1 restores neuronal integrity and function in the brain of lesioned young as well as aged animals. Critical analysis of these studies can provide guidance for future ganglioside research and may point to novel approaches for treating neuroinjury and a variety of degenerative conditions, including aging.     

An evaluation of randomization models for nested species subsets analysis

Randomization models, often termed “null” models, have been widely used since the 1970s in studies of species community and biogeographic patterns. More recently they have been used to test for nested species subset patterns (or nestedness) among assemblages of species occupying spatially subdivided habitats, such as island archipelagoes and terrestrial habitat patches. Nestedness occurs when the species occupying small or species-poor sites have a strong tendency to form proper subsets of richer species assemblages. In this paper, we examine the ability of several published simulation models to detect, in an unbiased way, nested subset patterns from a simple matrix of site-by-species presence-absence data. Each approach attempts to build in biological realism by following the assumption that the ecological processes that generated the patterns observed in nature would, if they could be repeated many times over using the same species and landscape configuration, produce islands with the same number of species and species present on the same number of islands as observed. In mathematical terms, the mean marginal totals (column and row sums) of many simulated matrices would match those of the observed matrix. Results of model simulations suggest that the true probability of a species occupying any given site cannot be estimated unambiguously. Nearly all of the models tested were shown to bias simulation matrices toward low levels of nestedness, increasing the probability of a Type I statistical error. Further, desired marginal totals could be obtained only through ad-hoc manipulation of the calculated probabilities. Paradoxically, when such results are achieved, the model is shown to have little statistical power to detect nestedness. This is because nestedness is determined largely by the marginal totals of the matrix themselves, as suggested earlier by Wright and Reeves. We conclude that at the present time, the best null model for nested subset patterns may be one based on equal probabilities of occurrence for all species. Examples of such models are readily available in the literature. Received: 3 February 1997 / Accepted: 21 September 1997     

Qualitative behavior of stage-structured populations: application to structural validation

 The transient behavior of a class of nonlinear differential systems representing stage-structured populations is studied. The qualitative dynamics are described in terms of succession of extrema for the state variables, or for the integrated difference between two trajectories. The rules giving the possibilities of extrema are derived, they characterize the classical stage-structured models. These rules can be compared with experiments to validate the structure of the model. An explanation for the disagreement of this transition scheme with some experiments could be an unexpected interaction with another variable. A new model taking the interaction into account thus engenders new transition rules, which are to be compared with experiments. These results are illustrated with experiments on copepods, showing how the qualitative experimental features can help the construction and the validation of the models. Received: 13 May 1996 / Revised version: 20 March 1998     

Crop production structure and stability under climate change in South America

Southern South America is expected to play an increasingly important role in global food production, but climate change could seriously threaten it. Here we have analysed long‐term historical data for major crops (rice, oats, barley, sunflower, soybean, sorghum, wheat, maize) at subnational scale to (a) look for common features among crop yield dynamics, evaluating their structure and implications for the persistence of that crop; (b) address complex crop responses to changes in environmental growing conditions; and (c) identify climate impact hotspots that are crucial for adaptation and mitigation. We have proposed a novel methodological approach based on dynamics systems in order to understand the processes behind annual crop yield fluctuations. We report the results of general patterns in the internal process (biophysical adjustments by rapid negative feedbacks) regulating crop production and analyse how it influences crop persistence and yield ceilings. The structure of a crop yield dynamic system defines its behaviour, but climate variations could displace it from yield equilibrium and affect its stability. Our findings suggest that weather conditions have a stronger impact on yield growth at high rather than at low yield levels (non‐additive impacts). This allows agriculture management to be refined and applied more efficiently, weakening the relationship between crop productivity and climate change and predicting the response of crop production to yield‐improvement strategies. We have identified those crops and regions which are most vulnerable to the current climate change trends in southern South American agroecosystems. Our results allow us to point to new ways to enhance self‐regulatory success, maximising the efficiency of crop production and reducing climate impacts. We have discussed important implications for crop management and climate change mitigation in an area where agriculture plays a key role in its socioeconomic and ecologic dimensions.     

Patterns and processes in shorebird survival rates: a global review

Changes in demographic rates underpin changes in population size, and understanding demographic rates can greatly aid the design and development of strategies to maintain populations in the face of environmental changes. However, acquiring estimates of demographic parameters at relevant spatial scales is difficult. Measures of annual survival rates can be particularly challenging to obtain because large‐scale, long‐term tracking of individuals is difficult and the resulting data contain many inherent biases. In recent years, advances in both tracking and analytical techniques have meant that, for some taxonomic groups, sufficient numbers of survival estimates are available to allow variation within and among species to be explored. Here we review published estimates of annual adult survival rates in shorebird species across the globe, and construct models to explore the phylogenetic, geographical, seasonal and sex‐based variation in survival rates. Models of 295 survival estimates from 56 species show that survival rates calculated from recoveries of dead individuals or from return rates of marked individuals are significantly lower than estimates from mark–recapture models. Survival rates also vary across flyways, largely as a consequence of differences in the genera that have been studied and the analytical methods used, with published estimates from the Americas and from smaller shorebirds (Actitis, Calidris and Charadrius spp.) tending to be underestimated. By incorporating the analytical method used to generate each estimate within a mixed model framework, we provide method‐corrected species‐specific and genus‐specific adult annual survival estimates for 52 species of 15 genera.