Written by Alejandra Feliciano
Gardens are dynamic
Too often landscapes are designed in a static manner, conceptualized both aesthetically and operationally in ways that do not allow for natural community assembly processes to take place. Through a functional understanding of these processes, there is a potential for informed designers to shape the future trajectory of plant communities, prevent undesirable plant invasions, and promote long-term biodiversity. Functional trait approaches can help develop tools to work with the underpinning sub-processes of succession, effectively scaling from plant traits to ecosystems.
[1] Community assembly: the study of the processes that shape the identity and abundance of species within ecological communities (Kraft and Ackerly 2014)
When selecting plant companions for ornamental landscaping applications, it is significant to consider that the parameters determining optimal fitness, and by extent long-term coexistence, change continuously through the community assembly[1] process. Traits that respond to the status-quo in ways that stabilize niches and equalize fitness across the community during one stage of development may not be as effective over the subsequent stage.
Although the use of functional traits has become popular in recent years to answer questions related to climate change and the sharp loss of biodiversity world-wide, functional approaches have always been a part of ecological studies, dating back to Darwin himself back in the 1850s. For a historical review of functional approaches spanning broader ecological topics, see (Orlandi Laureto et al. 2015). Let’s begin by examining how plant communities change over time.
I like to use the term ‘site-community’ to describe the status-quo confronted by candidate plants at the moment of potential community recruitment. This term reflects the inherent duality where ‘site’ (abiotic, environmental, spatial, temporal) and ‘community’ (biotic, organismal) factors do not operate separately, but as complementing parts of a single site-community which represents the balance of opposites found in nature. As we’ll see, the community assembly processes can modify sites, and sites can in turn modify community assembly parameters. I submit that plant functional traits and site functional attributes are a single factor, and that one can be used to measure the other because ‘communities’ and ‘sites’ mirror one another. This has been termed the ‘Janus Perspective’ (Grime and Pierce 2012).
Using more descriptive terminology can shift the focus of our inquiry, and it is important that the ‘site’ is not evaluated only as the sum of environmental factors. Support for frameworks championing simultaneous consideration of temporal, spatial, environmental, and biotic interactions has gained ground in recent studies (Kraft et al. 2015). In that paper, coexistence theory, intra- and inter-specific competition effects, stabilizing mechanisms, the environmental filter, and niche effects are integrated to explain community assembly. This ‘simultaneous consideration’ approach is part of the functional perspective that is presented in this review.
How plant communities evolve: functional community assembly
Community assembly is the main mechanism driving succession, drift[2], and speciation[3]. The process of community assembly can be summarized in functional terms using filter models (Chang and HilleRisLambers 2016). A phenotype candidate will face a series of functional filters before it can be recruited into the site-community (FIG 3‑1). Once recruited, it is considered an ‘fit phenotype’ and it may play a role in stabilizing the site-community’s functional state or in facilitating the next functional state. For succession to pause, all communities in the metacommunity must enter functional stability, otherwise the process repeats.
[2] Ecological drift: the random change in species abundance over time due to stochastic effects such as random extinctions, mutations, and speciation.
[3] Speciation: the evolutionary process by which new species emerge.
FIG 3-1 Summary of community assembly models. Community assembly models vary in the dominance of their controlling filters. Recognized community assembly models include (1) patch-dynamic, (2) species-sorting, (3) mass-effect, and (4) sparse. Each filter can be conceptualized as a fitness test, comparing the site-community’s functional state to the candidate’s functional traits. Through this process, the site-community selects for fitting candidates, and the resulting functionally fit population pool can either modify the filter parameters (if its recruitment results in de-stabilizing per capita effects) or stabilize the community. Note recruitment is depicted at the phenotype level, which includes both intra- and inter-specific trait variation (Violle et al. 2012). Site-community functional states are detectable at the patch scale (Messier et al. 2010).
From the functional perspective, filters are chained tests which compare the equivalence between effects of patch attributes and phenotype traits on per capita population growth. A site-community’s functional state can be defined as the community-weighted mean C-S-R proportion for all species in the plant community (Li and Shipley 2017).
Without using C-S-R functional proportions, calculating filter outcomes is challenging. Trait and attribute units differ, so net functional effects cannot be calculated using trait values directly. For example, soil density (a patch attribute) can affect leaf area (functional trait), but comparing their numerical values to each other is not very insightful. Additionally, many traits and attributes may contribute to a single filter, so calculating net effects arithmetically may not count for all possible factors. For example, canopy height, leaf area, and propagule mass have been found to map to the plant size axis (Diaz 2004, Cerabolini et al. 2010), but are there other key traits mapping to the same axis? Because of this redundancy, reductionary methods in which key trait values can be translated into calibrated units which map to the plant size and economic axes can more effectively measure the degree of phenotype adaptability to each filter (Pierce et al. 2013). The Diaz paper was a significant step forward for functional successional inquiry because it guides future focus in looking for key traits mapping to the size and leaf economic spectrum, which offer a direct link to community assembly filters. Similar studies are needed linking site attributes to each filter, so that community assembly simulations may be built and tested. Studying the diversity of functional guilds can distill key functional combinations that shape local community assembly processes (Laughlin 2014).
Connecting community assembly and succession: How communities at different successional stages are controlled by different filters
FIG 3‑2: Secondary Succession. A disturbance event changes the functional trajectory of a community. Priority effects reflect the functional state at this coordinate. Successional stages can be described as transitions between functional states driven by the differential in filter parameters among communities.
Let’s describe succession in functional terms. Succession can be defined as a series of transitions between functional states. Both primary and secondary succession occur following a disturbance event, an event of biomass destruction. In secondary succession, the disturbance event typically creates a temporal disturbance gradient from high to low disturbance which shifts the functional trajectory of the metacommunity (FIG 3‑2). This disturbance gradient may vary in its scope, affecting some communities and not others. It may also vary in its intensity, creating a disturbance differential which could have cascading effects on the community assembly processes throughout all communities in the metacommunity.
To put community assembly processes in the context of succession, the initial disturbance event establishes new test parameters for each filter by altering site-community attributes. Primary succession can be distinguished from secondary succession in terms of the level of impact the disturbance event has on filter parameters. In primary succession, the disturbance event is very severe, magnifying stress and eliminating competition.
Successive filters control assembly in progression
There is a logical progression of dominating community assembly filters over the successional timeframe: from high dispersal in early succession, to competition in intermediate stages, to stress in late stages. Understanding this natural progression can help designers optimize fitness in plant selections at each stage.
In landscaping applications, we are installing an initial plant community into a substrate with seed bank but devoid of mature plants. These conditions are reminiscent of those immediately following a secondary-succession-level disturbance event. It would be reasonable to expect filter parameters at this early successional stage to select for plants with high dispersal ability, regardless of competitive ability. Abiotic stress may or may not be a limiting factor at this point, depending on the productivity potential for the given patches.
As succession progresses, patches become colonized, community density increases, and competition becomes a more dominant filter than dispersal. Late in succession, as resources become stored in plant tissues stress increases, community density becomes moderated by resource limitation, and stress becomes the final controlling filter. Depending on the productivity potential of the site-community this general pattern may be difficult to detect. In his seminal paper, Grime theorized that in communities with low productivity potential, the pattern would be almost undetectable because those extreme conditions would not be conducive to biomass production (Grime 1977).
Conclusion
These models present an attractive alternative to traditional plant selection practices: if designers are able to stabilize community assembly filters through plant selection, successional progression becomes more predictable and can be used as a design tool. Further study is needed to explore best horticultural practices to maximize fitness at each successional stage. Is seeding an initial community with estimated ‘fitness champions’ for each stage of successional development the best strategy to maximize diversity and control unwanted invasions? How do the initial proportions of each ‘champion’ affect community development?
Functional approaches to community assembly can also enable us to reframe old questions regarding the role of diversity on community stability and provide the foundation for empirical studies to inform community invasibility. How pervasive is functional stability? How is functional stability affected by taxonomic diversity? Is ‘nativeness’ a driving factor behind superior local fitness? Are successful exotic invaders functionally superior to natives?
Finally, the plant size and leaf economic spectrum explain most of the variability in plant traits, but not all. The plant size spectrum correlates strongly to negative interactions (competition) but we still lack a sense of the weight mutualisms and exploitation may have on this correlation. This could present a good starting point to begin to unravel the mechanisms guiding the roughly 25% remaining unexplained variability in plant traits (Diaz et al. 2016).
Works Cited
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