The potential for and constraints on the evolution of compensatory ability in Asclepias syriaca

To investigate the potential for and constraints on the evolution of compensatory ability, we performed a greenhouse experiment using Asclepias syriaca in which foliar damage and soil nutrient concentration were manipulated. Under low nutrient conditions, significant genetic variation was detected for allocation patterns and for compensatory ability. Furthermore, resource allocation to storage was positively, genetically correlated both with compensatory ability and biomass when damaged, the last two being positively, genetically correlated with each other. Thus, in the low nutrient environment, compensatory ability via resource allocation to storage provided greater biomass when damaged. A negative genetic correlation between compensatory ability and plant biomass when undamaged suggests that this mechanism entailed an allocation cost, which would constrain the evolution of greater compensatory ability when nutrients are limited. Under high nutrient conditions, neither compensatory ability nor allocation patterns predicted biomass when damaged, even though genetic variation in compensatory ability existed. Instead, plant biomass when undamaged predicted biomass when damaged. The differences in outcomes between the two nutrient treatments highlight the importance of considering the possible range of environmental conditions that a genotype may experience. Furthermore, traits that conferred compensatory ability did not necessarily contribute to biomass when damaged, demonstrating that it is critical to examine both compensatory ability and biomass when damaged to determine whether selection by herbivores can favor the evolution of increased compensation. Received: 2 April 1999 / Accepted: 21 September 1999     

Genetic and evolutionary relationships among Asian Macaques

Published gene frequency data, checked for consistency of allele definitions across laboratories and for comparability of geographically identical samples, were pooled into a data set containing frequencies at nine loci for each of 20 populations that encompassed 10 macaque species. Genetic distances were calculated by the methods of Kidd and Cavalli-Sforza (1974). These distances were used to construct phylogenetic trees and to evaluate the relationships between divergence times and effective population sizes. Inter-and intraspecific genetic distances and the groupings defined by phenetic tree analyses support Fooden’s (1976) classification of the genus Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain qualitatively the inferred evolutionary relationships among macaque species. Many assumptions are required in order to estimate the variables necessary in the quantitative prediction of genetic differences for a comparison between any two populations. Examination of those assumptions demonstrates the need for more accurate genetic as well as paleozoogeographic information. An erratum to this article is available at .     

Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series

1. The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
2. We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
3. We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
4. This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.

     

The effect of costs associated with toxin production in a competitive system

In this paper, we study a two-species competitive system where both the species produce toxin against each other at some cost to their growth rates. A much wider set of outcomes is possible for our system. These outcomes are important contrasts to competitive exclusion or bistable attractors that are often the outcomes for competitive systems. We show that toxin helps to gain an advantage in competition for toxic species whenever the cost of toxin production remains within some moderate value; otherwise it may result in the extinction of the species itself.     

Tracking wind‐dispersed seeds using 15N‐isotope enrichment

Seed dispersal influences a wide range of ecological processes. However, measuring dispersal patterns, particularly long‐distance dispersal, has been a difficult task. Marking bird‐dispersed seeds with stable ¹⁵N isotopes has been shown to be a user‐friendly method to trace seed dispersal. In this study, we determined whether ¹⁵N urea solution could be used to enrich seeds of two common wind‐dispersed plants, Eupatorium glaucescens (Asteraceae) and Sericocarpus tortifolius (Asteraceae). We further tested if the water type (distilled versus tap) in ¹⁵N urea solutions influences the level and variability of enrichment of plant seeds, and if increasing spraying frequency per se increases enrichment. Because droughts may lower seed set or kill plants, we wanted to investigate if the additional use of an externally applied anti‐transpirant affects the intake of externally applied ¹⁵N into seeds. The results demonstrate that ¹⁵N enrichment of seeds can facilitate dispersal experiments with wind‐dispersed plants. The use of distilled water in ¹⁵N urea solutions did not increase ¹⁵N enrichment compared to tap water. Further, enrichment was more efficient at lower spray frequencies. Both the use of tap water and low frequencies could lower time, effort and project costs. The results suggest that species can be protected from drought using an anti‐transpirant without decreasing the incorporation of ¹⁵N into seeds.     

Estimation of Individual Growth Curves by Empirically Weighted Least Squares

The simultaneous estimation of individual growth curves and a mean growth curve is accomplished by weighted least squares. A polynomial curve is fitted for each individual and the polynomial parameters are linear functions of parameters corresponding to covariates. A simple, computationally efficient variance-covariance estimator is derived. The resultant estimate is used in the weighted least squares estimation. The results are compared to empirical Bayes estimation.