The population dynamics of Anisantha sterilis in winter wheat: comparative demography and the role of management

Abstract

Summary 1. We report on a 3‐year field study designed to monitor the detailed population dynamics of Anisantha sterilis in winter wheat, as well as to explore the consequences of changing broad‐scale patterns of management, in the form of reduced fertilizer inputs. 2. In the absence of herbicides, population dynamics were dominated by density‐dependent population growth. Unusually, this occurred mainly through density‐dependent recruitment. This was estimated to reduce population growth rates by 50‐fold, compared with the effects of density‐dependent competition between plants for resources. Density‐dependent recruitment also tended to buffer populations against year‐to‐year variations in emergence levels. 3. Little evidence for temporal variations in allometric seed production, the strength of competition between plants for resources or maximal mean plant performance was found in this study, or in comparison with previously published data. 4. No aspect of the life cycle was significantly affected by variation in the level of applied nitrogen fertilizer. In the case of competitive interactions we postulate that this lack of effect results from reduced intraspecific competitive effects as a consequence of decreased maximal plant size under low nitrogen conditions. The highly competitive nature of the environment in which A. sterilis occurs means that such changes tend to mask the effects of changing nitrogen levels. 5. Estimates of the effects of cultivation, on the other hand, indicated that seed germination, and hence population growth, was reduced by up to 90% when ploughing was employed rather than minimum tillage. While to some extent the effects of variation in the form of cultivation on population numbers may be buffered by density‐dependent recruitment, this effect outweighs any effects of nutrients or spatial or temporal variability in population dynamics. 6. Using previously published models for the dynamics of Alopecurus myosuroides, Avena sterilis and Avena fatua, we show that the response of populations of Anisantha sterilis to cultivation is very different from that of other grass weeds. In addition we show how single species models for population dynamics may be used to predict the responses of weed assemblages to changes in forms of management.

The comparative demography of the pasture weed Echium plantagineum between its native and invaded ranges

“…The results for E. plantagineum correspond well with these conclusions and provide further evidence of the often critical importance of the recruitment process in the determination of population size and in determining the success of a plant invasion. More recently, studies on annual weed species have suggested that some population demographic parameters may remain remarkably constant both spatially and temporally (Freckleton & Watkinson 1998; Lintell Smith et al . 1999).…”

Are weed population dynamics chaotic?

“…This form of recruitment thus sets a fixed upper limit to population size and has an extremely stabilizing effect on population dynamics. Notably, the maximal finite rate of increase of the population of Anisatha sterilis described by Lintell Smith et al . (1999) was greater than 100 individuals individual −1 year −1 and hence should have been capable of revealing any source of intrinsic instability.…”

“…Other stages of the life cycle have also provided evidence for density dependence within the course of a single growing season. In the arable weed Anisantha sterilis , for example, it was found that the proportion of seeds emerging from the seed bank declined as a function of density (Lintell Smith et al . 1999).…”

“…1; (v) Freckleton et al . (2000); (vi) Lonsdale (1996); (vii) Lintell Smith et al . (1999); (viii) Freckleton & Watkinson (1998b); (ix) Watkinson, Freckleton & Forrester (2000b).…”

“…Evidence for the role and nature of such variability may be hard to obtain, however, and there is a clear need for more long‐term time‐series on weed systems (Cousens 1995). In the absence of such data, however, it is possible, by combining the statistical analysis of field data with detailed analysis of existing literature within a population modelling framework, to try to explore the potential factors impacting on the variability of annual weed populations (Jones & Medd 1997; Freckleton & Watkinson 1998a,b; Lintell Smith et al . 1999; Watkinson, Freckleton & Dowling 2000a;Watkinson et al .…”