Summary1 The paper reviews the literature on seed dormancy, with special regard to inconsistencies in terms and definitions used. It presents a concept of seed dormancy in which physiology and ecology are integrated. Its aim is to increase the understanding of seed dormancy and germination, and to help defining ecological research questions. 2 It is claimed that seed dormancy should not be identified with the absence of germination. Seed dormancy should rather be defined as a characteristic, the degree of which determines the range of conditions in which a seed is able to germinate. Dormancy varies on a continuous scale, which is visualized by continuous changes in the range of conditions suitable for germination. If the conditions required by the seed are met by its environment, the seed will germinate. 3 The concept of dormancy that is described in the paper is partly based on a physiological model for the regulation of dormancy and the stimulation of germination. In this model dormancy is related to the amount of a hypothetical phytochrome receptor in the seed. 4 It is argued that the process of dormancy release should be clearly distinguished from the germination process itself. It is stated that as yet only temperature has been shown to alter the degree of dormancy in seeds. Factors like light and nitrate are often indispensable for germination, but only by promoting the germination process itself, not by mitigating the requirements for germination. 5 It is suggested that seed dormancy prevents germination when conditions are favourable for germination, at a time of the year when it can be expected that the plant originating from the seed will not survive and produce offspring. 6 It is concluded that dormancy should not be regarded as inactivity of seeds. At any degree of dormancy, seeds continuously react to their environment by adjusting their level of dormancy to the changing environment.

A model was developed to calculate carbon fluxes from agricultural soils. The model includes the effects of crop (species, yield and rotation), climate (temperature, rainfall and evapotranspiration) and soil (carbon content and water retention capacity) on the carbon budget of agricultural land. The changes in quality of crop residues and organic material as a result of changes in CO2 concentration and changed management were not considered in this model. The model was parameterized for several arable crops and grassland. Data from agricultural, meteorological, soil, and land use databases were input to the model, and the model was used to evaluate the effects of different carbon dioxide mitigation measures on soil organic carbon in agricultural areas in Europe. Average carbon fluxes under the business as usual scenario in the 2008–2012 commitment period were estimated at 0.52 tC ha−1 y−1 in grassland and −0.84 tC ha−1 y−1 in arable land. Conversion of arable land to grassland yielded a flux of 1.44 tC ha−1 y−1. Farm management related activities aiming at carbon sequestration ranged from 0.15 tC ha−1 y−1 for the incorporating of straw to 1.50 tC ha−1 y−1 for the application of farmyard manure. Reduced tillage yields a positive flux of 0.25 tC ha−1 y−1. The indirect effect associated with climate was an order of magnitude lower. A temperature rise of 1 °C resulted in a −0.05 tC ha−1 y−1 change whereas the rising CO2 concentrations gave a 0.01 tC ha−1 y−1 change. Estimates are rendered on a 0.5 × 0.5° grid for the commitment period 2008–2012. The study reveals considerable regional differences in the effectiveness of carbon dioxide abatement measures, resulting from the interaction between crop, soil and climate. Besides, there are substantial differences between the spatial patterns of carbon fluxes that result from different measures.

A model was developed to simulate weed emergence patterns after soil cultivation. In the model, the consecutive processes of dormancy release, germination and pre-emergence growth were modelled in separate modules. Input variables of the model were : date of soil cultivation, soil temperature and soil penetration resistance. Output variables of the model were : seedling density and timing of seedling emergence. The model was parameterized for Polygonum persicaria, Chenopodium album and Spergula arvensis with data from previous field and laboratory experiments. The model was evaluated with data from an experiment, in which emergence of P. persicaria, C. album and S. arvensis was monitored in field plots that were cultivated once only, at one of five dates in the spring. At the same time as the field observations on seedling emergence, seasonal changes in seed dormancy of the buried weed seeds were assessed by testing the germination of seed lots that were buried in envelopes. From a comparison between field observations and simulated data, it appeared that the model overestimated the rate of dormancy release in spring, whereas germination and pre-emergence growth were simulated well. In general, therefore, both the numbers of emerging seedlings and the timing of emergence could be predicted accurately, when dormancy was not simulated but introduced from experimental data. Improvement of predictions of field emergence of weeds should mainly focus on increasing the precision of the simulation of dormancy release. Close correlations were found between seedbed temperature and both the extent and rate of seedling emergence, but analysis with the simulation model revealed that they were only partly based on causal relationships, so that they have limited predictive value.

A systematic theoretical evaluation has been made of three important plant life history traits: adult longevity, seed longevity and seed mass, where seed mass is interpreted as being indicative of dispersal distance and seedling vigour. This model study examined the role of these three traits in relation to environmental disturbance. We chose temperate grasslands, widespread in north Western Europe and northern and eastern America, as our reference system for our simulations. Eight plant strategies were defined by allowing two levels in each of the three and combining them in all eight possible ways. A simple, spatially explicit model was developed to simulate competition among individuals with these eight trait combinations at different levels of disturbance. 
Simulation results were compared with the actual occurrence over a disturbance gradient of species with similar plant trait combinations in a large database from the Sheffield area (UK). This showed that with increasing disturbance level, non‐dormant perennials, dormant perennials, non‐dormant annuals and dormant annuals, respectively, became dominant but only if small‐seeded, indicating the relative viability of these particular strategies with respect to disturbance. 
A new prediction from the model was that stable coexistence occurs between plant strategies with dormant and with non‐dormant seeds over a range of levels of disturbance. Plant strategies with large seeds were inferior to small‐seeded ones if competitive ability of seedlings is proportional to seed weight. This difference was highest at low seed densities and low germination probabilities, indicating that large‐seeded species secure no advantage from being dormant (i.e. having a low germination probability). Finally, the results indicated that dormancy is superior to dispersal as a method of coping with disturbance.

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