ReviewThe spatial and temporal dynamics of species interactions in mixed-species forests: From pattern to process
Introduction
Many studies have shown that given the correct conditions, mixed-species forests and plantations can be more productive than monospecific stands (Assmann, 1970, Binkley, 1992, Kelty, 1992, Forrester et al., 2006b, Kelty, 2006). However, interactions between a given pair of species are often dynamic, changing as resource availability or climatic conditions change, and it is not unusual for net complementary interactions between a given pair of species to transform into net competitive interactions, or vice versa (Binkley, 2003, Boyden et al., 2005, Pretzsch et al., 2010, Forrester et al., 2011, Bouillet et al., 2013). Understanding how these interactions change is necessary when managing mixtures and to determine what is driving productivity–diversity relationships, which are the net effects of many different species interactions. Understanding when and how species interactions will change is also critical given that one of the biggest current challenges in forestry is to adapt forest ecosystems to climate change. Mixed-species stands are viewed as one of the most important adaptation and risk-reduction strategies (Reif et al., 2010) so understanding how short- to long-term climatic variability can influence species interactions is considered a priority (Brooker, 2006).
The literature is reviewed to examine what is known about how complementary effects in mixed-species forests and plantations change spatially or temporally, and the importance of considering stand density when examining mixed-species interactions. The mechanisms that drive these patterns are examined using the production ecology equation (Eq. (1); Monteith, 1977).
Wood or above-ground biomass production can be examined using Eq. (1) after subtracting carbon allocation to respiration or non-woody tissues (Binkley et al., 2004). Several reviews have used this equation to understand the mechanisms driving growth responses to a wide range of factors, including geographic gradients, fertiliser application, irrigation, pruning, thinning, spacing, genotypes, species, stand age (Binkley, 2012, Forrester, 2013) and the influence of mixed-species interactions on plant nutrition (Richards et al., 2010).
Interactions between species growing in mixtures are often described in terms of competition, competitive reduction and facilitation (Vandermeer, 1989). Competition occurs when different plants or populations interact such that one exerts a negative effect on the growth or survival of the other. Competitive reduction occurs when inter-specific competition is less than intra-specific competition because of an inter-specific differentiation in resource use. Facilitation occurs when plants interact such that at least one species positively influences the growth or survival of another. The stress-gradient hypothesis (SGH) is often referred to when examining the dynamics of species interactions, and suggests that facilitation will increase, and competition decrease, as conditions become harsher (Bertness and Callaway, 1994). The SGH usually fits with observations in forests, however it is worth noting that it was largely developed outside of forest ecosystems, and definitions of facilitation usually differ between forest and SGH studies. In SGH studies facilitation is usually quantified by comparing the survival, growth or fitness of a plant growing with neighbours vs. without neighbours. This “without neighbours” situation is rare in forests, which have higher stand densities, and instead facilitation or competitive reduction are often assumed to have occurred when growth (or survival) is greater with inter- than with intra-specific competition. Consistent with this contrast, a recent SGH meta-analysis and review by He et al. (2013) did not include any studies of tree-tree interactions unless the trees were in woodlands (not forests) or seedlings of tree species were examined.
Section snippets
Complementarity calculations and a conceptual complementarity model
Competitive reduction and facilitation often occur simultaneously and their effects can be difficult to separate, so in this review each of these are collectively described as complementarity. Many studies have examined the interactions that occur between trees in forests and these have been reviewed previously (Assmann, 1970, Binkley, 1992, Kelty, 1992, Forrester et al., 2006b, Kelty, 2006, Richards et al., 2010), however far fewer studies have examined how these interactions are influenced by
Spatial effects of interactions that influence nutrient availability
Mechanisms that improve nutrient availability, uptake and use efficiency often result in greater complementary effects on sites where that nutrient is limiting, consistent with the conceptual model of Fig. 1. Several examples of this trend are shown in Fig. 2. A classic example is the facilitative effect of nitrogen(N)-fixing species on the growth of non-N-fixing species, which increases as N becomes more limiting (Binkley, 2003, Forrester et al., 2006b, Forrester et al., 2006c, Bouillet et
Spatial effects of interactions that influence water availability
Following the model in Fig. 1, interactions or mechanisms that influence water availability and uptake will be more useful where water is limiting (Fig. 4). For example, Abies alba was found to be less sensitive to summer droughts when growing in mixtures with Picea abies or Fagus sylvatica than when growing in monospecific neighbourhoods and this complementary effect was only found at dry sites and not at mesic or humid sites (Fig. 4, Study 5, Lebourgeois et al., 2013). It was suggested that
Spatial effects of interactions that influence light absorption and use
Increasing complementary effects with increasing site quality, or as climatic conditions improve, have been observed in several studies (Fig. 3, Fig. 5). While none of those studies quantified the mechanisms behind the response by measuring the variables on the right-hand side of the production ecology equation, they are useful for developing hypotheses that can be tested in new experiments. For example, one of those (Study 6) showed that for a given tree diameter, the crown projection area of
Temporal effects and interactions between resources
Temporal changes in species interactions result from abiotic factors, such as climatic conditions and stand disturbances, or stands developing and potentially influencing the availability of light and soil resources. Considering all of these factors, and the fact that different species often have contrasting growth dynamics, it is not surprising that as stands develop there are often changes in the relative dominance of species or complementarity effects, in terms of the relative growth of
Stand structure
Stand density may also influence species interactions and growth in mixed-species forests. Stand density is important for at least two reasons when analysing species interactions. Firstly, stand growth usually increases with density initially before levelling off at higher densities, and stand density can be positively correlated with species diversity (e.g. Chisholm et al., 2013, Vilà et al., 2013). Therefore greater productivity in mixtures may sometimes result from higher densities or
Conclusions and implications for future research
The literature reviewed above indicates that for a given species combination, there are probably several different processes that lead to the net complementary (or competitive) effects. For example in mixtures that contain N-fixing species, there are also processes that reduce competition for light and accelerate rates of P cycling (Binkley et al., 1992a, Forrester et al., 2005, Richards et al., 2010, Hinsinger et al., 2011). The contribution of these processes to the net complementary effects
Acknowledgements
This study was part of the Lin2Value project (project number 033L049) supported by the Federal Ministry of Education and Research (BMBF, Bundesministerium für Bildung und Forschung). Dan Binkley and Damien Bonal provided comments that improved the manuscript and these are gratefully acknowledged. Thank you also to two anonymous reviewers who also provided comments that improved the manuscript.
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