Regulating factors

The primary concern of this study is to create a model where the regulating effect of weed management strategies on population dynamics can be simulated. It is clear that cropping systems and specific farming practices can strongly influence the composition of the weed community, the abundance of individual species within this community and the development of the population of a certain weed species. For example, Albrecht (2005) reported that 6 years after conversion from conventional to organic farming, 31 out of 44 species had increased and 3 species had decreased relative to two years prior to the conversion.

On the other hand, changes in plant population size can occur regardless of management practices. An example is the increase, especially over the last two decades, in thermophilic plant species in the Netherlands that has been attributed to climate change (Tamis et al., 2005).

Similarly, other extrinsic factors (i.e. weather and other organisms) interact with weed management. For example, a number of arable weed species in the UK, once common, are now considered rare. In the case of Agrostemma githago (Firbank, 1988) it was improved seed cleaning that brought about the decline (Bond and Turner, 2004). Looking at the distribution maps of rare arable weeds in the UK reveals that their presence is gravitating towards the south of the UK, where calcareous soils prevail (Wilson and King, 2008). The UK represents the northern boundary of the geographical distribution of A. githago and it is still quite common in the more central area of its distribution, such as Spain. This shows that edaphic, climate and

management factor are interacting forces in shaping the dynamics of weed populations. In conclusion, at any one time, population dynamics are subject to change due to extrinsic factors, to causes intrinsic to the population (e.g. density dependent regulation), to the interaction between both types of factors and to interactions Intrinsic

Management Other

organisms Weather

Figure 2-4 Diagrammatic representation of the

interaction between intrinsic population processes and extrinsic factors (after Cousens and Mortimer, 1995).

amongst individuals in the population (Cousens and Mortimer, 1995) (see Figure 2-4). Understanding the key factors regulating weed population dynamics requires integrating the perspectives of two fields, agronomy and plant ecology.

2.2.2.1 Density dependence

Density-dependent factors regulate population growth in such a way that the impact of these factors per individual changes with population size. One of the best examples of density-dependent processes in plant ecology is competition for limited resources (Firbank and Watkinson, 1986). By increasing plant density, total yield will increase towards an asymptote whereas the average weight of an individual plant decreases according to a negative hyperbole (see Figure 2-5).

Density-dependent effects often tend to work as ‘inhibitory checks’ on the population, but positive density-dependence (also called Allee effects or facilitation) has been observed as well (Cappuccino, 2004; Davis et al., 2004a).

In contrast, the impact of density independent factors (such as weather) remains constant per individual, regardless of population density. Without density-dependent regulation a population would either exponentially increase forever or go extinct. Hence, ignoring density-dependence in population dynamic models may lead to over- estimation of the population size.

Most population dynamic models that include density-dependence have singled out weed seed production as the life-stage through which it is assumed to operate (Holst

et al., 2007). For many plant populations this may be true, but studies have shown that

Figure 2-5 Production-density curves (left graph showing total biomass and right graph

individual plant biomass) describing a hypothetical single-species stand. Curves are based on Håkansson (2003). Left curve is of the form Y = X/(a + bX) with a = 0.05 and b = 0.001. Random noise was added to the resulting Y values to mimic real data.

well (Crawley, 1990; Silvertown and Charlesworth, 2001). Lintell Smith et al. (1999) found that density-dependent recruitment stabilised populations to such an extent that hardly any density-dependent fecundity could be observed. Several authors have shown that density-dependence at different ‘locations’ in the life-cycle can produce different dynamics (Watkinson et al., 1989; Gillman et al., 1993; Buckley et al., 2001). Westerman et al. (2007) compared three scenarios where density-dependence was included at different stages in the lifecycle (seedling emergence, seedling survival or seed production) of a population of the parasitic weed Striga hermonthica

Goldberg

. The mean seed production per individual plant below which the population would go extinct was three times higher if (only) seed production was density-dependent as compared to if (only) seedling emergence was density-dependent. Hence, arbitrarily choosing density-dependence might result in spurious projections of population size and dynamics.

et al.

Weeds that survive weed control will be competing for light and possibly also for water and nutrients with crop plants and this in itself is a density-dependent process. Numerous studies have shown that by increasing crop density and decreasing row distances the total and/or mean individual weed biomass could be reduced (Wilson et al., 1988; Wilson et al., 1995; Murphy et al., 1996; Weiner et al., 2001; Mertens and Jansen, 2002).

(2001) argued that density mediated population regulation is not a within-species matter but rather a mechanism that operates on the level of the entire community. They provided evidence that support this hypothesis from desert annual plants in Israel. At all three life history stages studied (emergence, survival, and final size) strong evidence of community-level density dependence was detected. As the crop either possesses most biomass or is the most abundant species in the ‘crop-weed community’, it makes sense to evaluate the density-mediated effects of the crop on life stages of weeds.

Density-dependence due to intra- or interspecific weed competition only occurs above a certain weed population threshold size. Unless fields are extremely weedy and/or weed control operations around crop sowing are somehow unsuccessful, the weed population is heavily reduced and may be well below this threshold. For example, Medd (1996) reported that no clear density dependence could be detected for fecundity below a density of 40 individuals of wild oat / m2. Even in a wheat crop sown at a high density of 150 plants / m2 to boost competitiveness, yield losses of around 15-20% would be incurred from densities of up to 40 wild oat plants / m2

(Martin et al., 1987). This is well above the economic threshold (ET) range of 9 – 13 plants m-2 (Jones and Medd, 2000). Therefore, if weed control is successful, the importance of intra- and inter-specific weed competition may be minor. Indeed, Debaeke (1988) showed that a density independent model predicted weed population development well in a three-crop rotation system. The way density dependence is actually represented in most population dynamic model depends on how competition for light between crop and weeds and weed seed production are modelled. If biomass is accounted for, then in fact plant biomass is density-dependent. Alternatively, seed production can be modelled as a function of density.

2.2.2.2 Agronomical aspects: cultural control

Organic as well as conventional farmers in the UK are advised to grow carrots and onions in a 5-7 year rotation (Assured Produce, 2008). This is mainly to avoid the build-up of soil-borne diseases such as white rot in the case of onion (Soil Association, 1999b), and cavity spot and violet root rot for carrots (Soil Association, 1999a; Assured Produce, 2007). The questionnaires and further interviews with carrot growers (see Appendix 1) and crop consultants (Carl Sharp and Tom Will) highlighted that growers often rent a field from arable farmers once every five to eight years. In the other years, a range of arable crops are grown by the arable farmers. Different crops in the rotation may vary in three key aspects; timing (e.g. sowing time) and type of farming practices (e.g. cultivation), crop competitiveness and weed management strategy. These aspects will affect the performance of the weed species in the seedbank. Different cultivation regimes prior to crop sowing may generate different vertical distribution patterns of weed seeds in the soil, thereby regulating the recruitment of weeds (Froud-Williams et al., 1983; Feldman et al., 1998; Vanhala and Pitkanen, 1998). Various studies have shown that weeds produce more biomass and seeds in one crop or crop cultivar than another because of differences in relative emergence, relative crop competitiveness and/or harvest time (van Acker et al., 1997; Lutman, 2002; Sester et al., 2004; Weaver et al., 2006). Weeds belonging to the same botanical genus or family as the crop can have an advantage over other weeds since they can not be targeted by selective herbicides as that would damage the crop as well.

was higher in wheat years than in sunflower years (Jurado Exposito et al., 2004). Moreover, when considering crop rotations, demographic rates in one crop may be affected by the previous crop. For example, fewer weed seedlings were observed in corn when alfalfa was the preceding crop as compared to continuous corn in a low- input system without herbicides (Clay and Aguilar, 1998). Long-term field experiments have shown that the development of the weed flora composition, and with it the abundance of individual weed species, can depend on the type of crops in a crop rotation (Ball, 1992; Liebman and Dyck, 1993; Sosnoskie et al., 2006). Even for crop rotations of the same length and consisting of the same crops, different annual mean weed population growth rates may result depending on crop order (Mertens et al., 2002) or timing of cultivation (Davis et al., 2004b).

The timing of emergence of the weed relative to that of crop plants is paramount as it determines growth and yield of both crop and weed. Early weed cohorts cause higher crop yield loss than later cohorts (Knezevic et al., 1997; O'Donovan and McClay, 2002; Hock et al., 2006). Moreover, early-emerged weed cohorts produce more biomass and seeds than late-emerged weed cohorts (Brainard and Bellinder, 2004; Willenborg et al., 2005; Walsh and Minkey, 2006). This can even fundamentally change the population growth rate; Selman (1970) as cited in Cousens and Mortimer (1995), showed that the ratio of population size between two years of Avena fatua

Scursoni et al. (1999) showed that twice as many

was

higher (λ = 2.74) when sowing of spring barley was early than when sowing was

delayed (λ = 0.40).

Avena fatua seeds entered the seedbank in a wheat crop compared to a barley crop due to the later harvest time of wheat. Bennett and Shaw (2000) showed that early maturing soybean cultivars resulted in lower seed production by Ipomoea lacunosa and reduced germination of

Sesbania exaltata seeds due to harvesting prior to physiological maturity. Finally, Hansson et al. (2001) studied the influence of harvest time (and stubble height) on weed seedling recruitment in barley grown for silage. In the absence of weed control, the later barley was harvested, the higher the percentage of weed seeds that had shed at harvest time. Consequently, the number of weed seeds in the soil at the time of harvest (as well as the number of weed seedlings in the following year) increased with progressive harvest time (see Figure 2-6).

For the plots where barley was harvested early for 6 years the selection pressure was favourable to fast reproducing species; Stellaria media

Although substantial experimental work was conducted relating to cultivation (see Chapter 3), this was in order to evaluate the individual cultivation models available rather than as an effort to use cultivation as a separate component of cultural control.

increased considerably over the 6 year course in comparison with late reproducing weeds.

Figure 2-6 Annual changes in the total number of

weed seeds recovered from the soil after harvesting barley at three progressive stages of grain maturity and leaving 10 cm stubble (redrawn from Hansson et al. (2001). Harvest times: H1 was at grain-water content 50-60%, H2 was at grain-water content 35-45% and H3 was at grain-water content 18-32%. Number of days from H1 to H3 varies between 17 and 26.