The Deleterious Effect of Water and Low Temperature on Germination of Pea Seed

Some pea seeds were killed or damaged by soaking in water, andthe damage was aggravated by low temperatures. Low-vigour seedlots were more sensitive to injury than high-vigour lots. Reducedwater uptake in osmotic solutions resulted in less damage andmost injury occurred during the initial phase of imbibition. More electrolytes exuded from dead and low-vigour seeds thanfrom high-vigour seeds and increased exudation at low temperaturewas associated with a higher incidence of dead seeds. Death is thought to be caused by a sudden inrush of water whichdisrupts the sub-cellular organization and membranes of a proportionof seeds predisposed to injury.     

Salmon‐derived nutrients drive diatom beta‐diversity patterns

1. Pacific salmon are a textbook example of migratory animals that transfer nutrients between ecosystems, but little is known about how salmon‐derived nutrients (SDN) affect the biodiversity of recipient freshwater ecosystems. We examined paleolimnological records from six Alaskan lakes to define how changes in SDN from sockeye salmon (Oncorhynchus nerka) influenced sedimentary diatom community structure and beta‐diversity among lakes and through time. 2. Using an isotopic mixing model, we showed that SDN loading could account for >80% of the lake total nitrogen budgets and strongly regulated diatom community composition. Spatial dissimilarity in diatom communities was positively related to differences in SDN among lakes (r² = 0.69, P < 0.01, n = 10). Likewise, temporal dissimilarity in diatom communities was positively related to differences in SDN in a sediment core with substantial variation in salmon spawner dynamics between 1700 and 1950 AD (r² = 0.34, P < 0.01, n = 19). Finally, beta‐diversity metrics quantifying temporal turnover within each lake’s sediment record were also positively related to the variance in SDN loading among lakes (r² = 0.88, P < 0.05, n = 5). Mean SDN was only negatively correlated to temporal diatom beta‐diversity. 3. Spatially subsidised systems often receive temporally variable resource inputs, and thus, it is not surprising that, unlike previous studies, we found that resource variability was the key driver of community composition and beta‐diversity. In habitats that receive strongly fluctuating external nutrient loads, environment heterogeneity may overweigh stochastic community processes. In addition, freshwater diatoms are characterised by great dispersal capabilities and short life cycles and therefore may be a more sensitive indicator for evaluating the role of resource variability than previously used model organisms. These results suggest that productivity–diversity relationship vary with the nature of nutrient loading and the life history of the community studied. 4. Overall, our study highlights that the transport of nutrients by sockeye salmon across ecosystem boundaries is a significant driver of algal community and biodiversity in nursery lakes, mainly through changing the magnitude of nutrient variation. As such, freshwater species diversity in regions like the U.S. Pacific Northwest may become impoverished where there have been long‐term declines in salmon populations and decreases in nutrient variability among lakes.     

Detecting chaotic dynamics of insect populations from long-term survey data

1. Estimates of the Lyapunov exponent, a statistic that measures the sensitive dependence of the dynamic behaviour of a system on its initial conditions, are used to characterize several sets of insect time series.
2. A new method is described to overcome the difficulty of defining the dynamics of an observed, noisy, short ecological time series. This method provides two test statistics for the estimated Lyapunov exponent.
3. This method is applied to forty-six time series comprising six aphid species from five sites and four moth species from six sites. There are few positive Lyapunov exponents and none is sufficiently large to characterize its time series as chaotic.
4. Two methods to estimate the Lyapunov exponent are compared; that based on logarithmically transformed counts yields less variable estimates for highly variable insect data than that based on untransformed counts.