Ch 1: General Introduction

The functional importance of plant biodiversity

Plants are fundamental to life on Earth. Their ability to transform the sun’s energy into living matter, called photosynthesis, is a process that sustains many lives other than their own, including the lives of humans. Their use of photosynthesis to produce organic compounds from carbon dioxide and water, known as primary production, is the basis of almost every food chain. This makes green plants the building blocks of most ecosystems across Earth’s land and ocean—the most vital producers of the world. Plants are the ultimate modifiers of their environment, most notably by regulating the climate and producing the very air we need to breathe. They also provide the food, medicines, materials, and fuels we need to go about our everyday lives (RGB Kew 2016).

It should be a concern, therefore, that the diversity of plants on Earth is under threat. Human activity is placing great strain upon global biodiversity—the variation of genes, species, and ecosystems that make up the diversity of life—one of the descriptions of a safe planetary operating space for humanity (Rockström et al. 2009; Mace et al. 2014). Many plant species are threatened with extinction due to decreased population sizes, and at least 139 known species are already extinct (IUCN 2015). Current extinction rates for animals and plants are estimated to be 100–1000 times greater than what we historically see in the fossil record (Pimm et al. 2014; Ceballos et al. 2015), and these estimates may be overly conservative (Régnier et al. 2015). The most recent reports estimate that one in five plant species are threatened with extinction, perhaps even more (Brummitt et al. 2015; Pimm & Joppa 2015).

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There are many costs to biodiversity loss. The extinction of any species means irreversibly losing a unique lineage of evolutionary history, compounded by the fact that extinction is often focused within related groups of species (Purvis & Hector 2000). Another consequence of losing plant diversity is that it undermines the vital functional role plants play within ecosystems (Cardinale et al. 2012; Hooper et al. 2012; Naeem et al. 2012). This fact may not seem surprising, given that as a functional group they are vital to ecosystem processes. But it was only recently discovered that having a diversity of plant species helps sustain the functioning of ecosystems, and hence there is an ecosystem-level cost to losing plant diversity (Cardinale et al. 2012).

Biodiversity and ecosystem functioning

Over the past two decades, hundreds of studies have shown that losing biodiversity on average reduces the functioning and stability of ecosystem processes (Cardinale et al. 2012; Tilman et al. 2014). At a conference in 1992, researchers presented hypotheses that more diverse communities of species are more productive, use resources more efficiently, and show greater stability in these ecosystem processes (Schulze & Mooney 1993). Early experiments supported these hypotheses, finding that increased species diversity produced communities with higher primary productivity (Naeem et al. 1994, 1995) and that this productivity was more resistant to environmental change (Tilman & Downing 1994). This field of study became known as biodiversity-ecosystem functioning research (also known as biodiversity-functioning or BEF).

The first generation of experiments followed, conducted mainly in grassland plant communities, focusing on primary productivity and its relationship with species composition and richness (Tilman et al. 1996; Hector et al. 1999), although functional group descriptions of biodiversity were also studied (Hooper & Vitousek 1997; Tilman et al. 1997a). These experiments found that nutrient use, total plant abundance, and productivity all depended upon what species (and functional types) were present, but also increased on average as the community included more species. Increases in species richness typically showed diminishing returns, approaching an asymptotic productivity in the most diverse treatments.

The first explanation for this pattern was that species differ in their resource requirements, due to niche differentiation, such that they show complementary resource use and as a result collectively use more (Tilman et al. 1997b). This harks back to Darwin’s principle of divergence, whereby natural selection causes species to diverge into complementary niches that lower interspecific competition (Darwin 1859; McNaughton 1993; Hector & Hooper 2002). Darwin focused on explaining what causes biological diversity, but he also hypothesised what consequences biodiversity would have for the functioning of ecosystems.

In doing so, he suggested that the mechanisms for maintaining biodiversity are the same as those that create a functional role for biodiversity within ecosystems. Since then, a rich body of theory has emerged on the maintenance of biodiversity via the stable coexistence of competing species (Tilman 1982; Chesson 2000; Adler et al. 2007). And this theory was used to explain how diverse mixtures of species could be more productive by partitioning resources (Tilman et al. 1997b; Loreau 1998a, 2004; Yachi & Loreau 1999; Mouquet et al. 2002).

But a second explanation argued that niche differentiation was not the cause for increased and more stable ecosystem functioning, leading to contentious debate (Aarssen 1997; Grime 1997; Huston 1997; Tilman et al. 1997b, 1998; Wardle et al. 1997; Doak et al. 1998; Loreau 1998b; Hector 2000; Huston et al. 2000). The alternative explanation was that having more species is not important in itself; it only increases ecosystem functioning because there is a greater likelihood of the best performing species being present. By this logic, only species identity is important and there is no intrinsic functional value to species diversity. Methods were devised to tease apart the two explanations for biodiversity effects (Loreau & Hector 2001), and subsequent work has shown that they are not mutually exclusive (see below and chapter 3 for more).

A consensus emerged on the effects of biodiversity on ecosystem functioning after a first generation of synthesis (Hooper et al. 2005; Balvanera et al. 2006; Cardinale et al. 2006, 2007; Worm et al. 2006; Stachowicz et al. 2007; Cadotte et al. 2008): diverse communities could more effectively capture limiting resources and convert those resources into biomass. The same general result was found across terrestrial, marine, and freshwater ecosystems; within many organism groups spanning different trophic levels; and using genotypic, species, and functional expressions of biodiversity. Following a continued explosion of experiments there was another round of synthesis (Cardinale et al. 2011, 2012; Hooper et al. 2012; Naeem et al. 2012), and a consensus emerged that species identity and richness are both important aspects of biodiversity for ecosystem functioning. It is still not clear how prevalent niche differentiation is as a mechanism for biodiversity-functioning effects, nor is it clear what biological processes would be involved in such niche differentiation.

Box 1.1. Glossary

The future of biodiversity-functioning research

In the most recent consensus paper, Cardinale et al. (2012) described the current state of knowledge and then listed emerging challenges for the next generation of experiments. They suggested that, for biodiversity-functioning research to better inform policy and manage the consequences of biodiversity loss, future work should focus on increasing its “realism, relevance and predictive ability” (Figure 1.1). Doing so would strengthen our understanding of how biodiversity loss might impact the provisioning and regulating services that ecosystems provide to humanity. To meet these challenges, they suggested three key areas for development.

Consensus and the future. Left: The consensus on the form of biodiversity-functioning relationships. Right: Research can progress by improving our predictive and mechanistic knowledge, expanding our focus of experiments, and linking functions to services in real-world ecosystems. From Cardinale et al. (2012).

Figure 1.1. Consensus and the future. Left: The consensus on the form of biodiversity-functioning relationships. Right: Research can progress by improving our predictive and mechanistic knowledge, expanding our focus of experiments, and linking functions to services in real-world ecosystems. From Cardinale et al. (2012).

Firstly, to improve our ability to predict the impacts of diversity loss, we need mathematical modelling that will develop our mechanistic understanding of biodiversity-functioning effects. Such modelling would also help us scale experimental results up to insights for whole landscapes. Secondly, as well as scaling up the modelling we should scale up our experimental focus, in terms of the temporal and spatial scale of experiments and also the types of ecosystems that experiments encompass. These landscape-level experiments would provide insights at the scale most relevant to management and better reflect the nature of real-world ecosystems. Thirdly, we should use these experiments to link realistic scenarios of diversity loss with the provisioning and regulating services that ecosystem functions support.

So far the effects of plant diversity on ecosystem functioning have been extensively demonstrated in controlled experiments, and in ecosystems that are amenable to controlled study. Most experiments have been short-term and small-scale. The early evidence is that some effects of diversity only become apparent at larger temporal and spatial scales, and so most experiments may have underestimated the impacts of diversity loss (Dimitrakopoulos & Schmid 2004; Tilman et al. 2006; Cardinale et al. 2007; Duffy 2009; Venail et al. 2010; Reich et al. 2012). Theory was first developed to explain the early experiments (Tilman et al. 1997b).

Theoretical frameworks that can unify biodiversity-function research by scaling in time, space, and biological organisation are in development (Loreau 2010b). But we still lack the mechanistic understanding of how interactions between species influence the way diverse communities perform (Turnbull et al. 2013). Continued interplay between theory and experiments will be needed to further develop our basic ecological understanding of how plant communities are structured, from interactions between individuals up to the population, community, and ecosystem levels of organisation (Loreau 2010a).

One of the criticisms of biodiversity-functioning research has been that such controlled experiments are not relevant to real-world ecosystems and therefore this research is of limited relevance to understanding the impacts of global biodiversity change (Srivastava & Vellend 2005; Duffy 2009; Wardle & Jonsson 2010). Such criticisms focused on the abstracted nature and small spatial scale of past experiments, which may not reflect the scope and scale of biodiversity change in real-world ecosystems—although the spatial scale of biodiversity change is in itself a hotly debated topic (Vellend et al. 2013; Dornelas et al. 2014; Newbold et al. 2015; Gonzalez et al. 2016). As Cardinale et al. (2012) noted, the connection between biodiversityfunction research and the realistic impacts of diversity loss on ecosystem functions and services needs to be verified further. This can be achieved by understanding the scale of actual biodiversity loss in real-world ecosystems, and placing biodiversityfunctioning experiments more closely within this real context. As part of this effort, we should look at the most important drivers of global biodiversity change and ensure that research includes all ecosystems that are functionally important for global ecosystem services.

This new generation of research will largely take place in complex landscapes, which have been altered by humans and are naturally variable in their environment. The biology of the systems may also be structurally complex and include long lifehistories. Experiments will have to be more large-scale and long-term to capture these complex spatial and temporal dynamics (Scherer-Lorenzen 2014). Carrying out these new experiments will determine the utility of biodiversity-functioning for the management of real-world ecosystems, from ecological restoration to the provision of ecosystem services like carbon storage (Mori et al. 2016).

From mechanisms to applications

The outlook for future research put forward by Cardinale et al. (2012), and others, can be summarised as one with two frontiers: the mechanisms and the applications. We need the mechanisms to understand the causes of biodiversity effects on ecosystem functioning. And we need the applications to understand the relevance of this work in a world of global change. Here, I will present four specific studies which follow the broad scope that has been laid out.

I will begin in chapter 2 by studying interactions between plant species, the main deterministic force that structures plant communities (Rees et al. 2001). The strength of interactions within and between species determines the types and number of species that stably coexist in diverse communities, and also the relative abundances of each species. Species interactions drive effects of diversity on ecosystem functioning by altering the per capita performance of species within the community (Loreau & Hector 2001). So, to develop a predictive understanding of how plant diversity influences the functioning of real-world ecosystems, we need a predictive understanding of species interactions in natural plant communities. In chapter 2, I will test the predictive accuracy of the foremost method for predicting the effect of species interactions in natural communities (Mack & Harper 1977; Pacala & Silander 1990; Rees et al. 1996; Martorell & Freckleton 2014).

The method has predominantly been used to study competitive interactions, but it can be applied to other types of interactions as well. Observational data are collected for co-occurring species, which are then used to predict how each species would respond to the removal of interacting species (see chapter 2). The test I will present is the first of its kind, whereby I apply this observational method to experimental species mixtures (i.e. polycultures). Monocultures of each species, where they are grown in isolation, provide an independent test of the method’s prediction. The experimental community is composed of sand-dune annual species, which are simple to observe and provide multiple generations. These species communities are known to be structured by competition, which is mediated by seed size (Rees 1995; Turnbull et al. 1999, 2004). This prior knowledge will help verify whether the method has realistically captured dynamics between these species. I will then compare the method’s predictions with our test to understand whether this method can be used to infer how natural plant communities are structured.

In chapter 3, I will mathematically model the growth of species which interact in diverse communities, in order to understand what mechanisms can drive positive effects of plant diversity on productivity. The biological processes that underlie diversity effects are still not fully understood (Cardinale et al. 2012). Modelling can help to formalise trait-based mechanisms into testable hypotheses, which can then be tested using experimental data. We need these mechanistic models to understand whether diversity effects can be explained by resource partitioning among species, positive interactions, different natural enemies, or any other cause (Turnbull et al. 2013). I will focus on identifying what mechanisms can generate the most definitive evidence of positive diversity effects: when mixtures of species are more productive than any one species could achieve in isolation, a phenomenon known as transgressive overyielding.

I will begin with a model published by Turnbull et al. (2013), whereby species grow throughout a season by competing for one shared limiting resource. Species differ in their resource consumption as defined by a trait-based functional trade-off, between their ability to capture resources quickly and their ability to access a large pool of resources. This trade-off can allow species to stably coexist and also generate a complementarity effect of diversity (see chapter 3). But it is not sufficient for transgressive overyielding to occur. I will propose a mechanism for transgressive overyielding, by assuming that a fixed proportion of the remaining resources not yet locked up in plant tissue is lost over time via environmental leaching. I hypothesise that species mixtures will achieve a greater envelope of resource capture throughout the season and as a result capture more and leach fewer resources than the best component monoculture.

In chapter 4, I will begin looking at the applications of biodiversity-function research. I will propose a mechanism by which species diversity could stabilise ecosystem functioning in selectively logged tropical forests, and show whether this could improve the ecological restoration of these forest ecosystems. Large areas of South East Asian tropical forest have been selectively logged, which has depleted populations of the dominant dipterocarp trees and threatened the ecosystem’s plant diversity more widely (Sodhi et al. 2010; Maycock et al. 2012). These tropical forest ecosystems are important for a range of globally and locally valuable ecosystem services, such as carbon storage (Saner et al. 2012). Efforts to restore dipterocarp populations, and the complex canopy structures they produce, have involved replanting the logged species back into the degraded forest (Kettle 2010).

But replanting has only been implemented using low diversity stands, and the effectiveness of this restoration method has gone untested. These three factors—the diversity loss that has occurred, the functional importance of these ecosystems, and the opportunity for restoration—make the tropical forests of South East Asia a useful setting for taking 1.18 biodiversity-function experiments into real-world ecosystems. Furthermore, the complexity of these ecosystems has so far inhibited biodiversity-function study in the region. Extending research into this ecosystem will improve our understanding of the generality of biodiversity-function relationships. It will also inform how biodiversity change in these human-altered ecosystems impacts the ecosystem services they provide.

In chapter 4, I present the initial results from the first large-scale long-term biodiversity experiment in these tropical forests: the Sabah Biodiversity Experiment (Hector et al. 2011b). In this experiment, dipterocarps have been replanted into the selectively logged forest at varying levels of species diversity. We can then ask how species diversity of the replanted species impacts the effectiveness of this restoration technique. I analyse the first decade of the survival and growth of these replanted species to understand: (i) how the species differ in functionally important traits, (ii) how species differ in their responses to the heterogeneous environment across this complex landscape, and finally (iii) how these factors might create a spatial insurance effect of diversity, whereby diverse mixtures show less variable performance and ensure successful restoration throughout the complex landscape.

In chapter 5, I investigate the scale of diversity loss within real-world ecosystems, focusing on agricultural landscapes by comparing the biodiversity impacts of organic and conventional farming. In order to place biodiversity-function experiments within the context of realistic diversity loss, and to understand the ecosystem-level consequences of that loss, we need to first understand how biodiversity is changing in real-world ecosystems. In an age when virtually nowhere is untouched by human impacts, this means understanding how human activity drives biodiversity loss. Agriculture has the greatest impact of all human activities, as it 1.19 already covers more than a third of Earth’s ice-free land (Ellis & Ramankutty 2008).

Not only could agriculture be impacting biodiversity across vast areas of the planet, but there could be knock-on effects for ecosystem functioning worldwide. Furthermore, agricultural systems themselves depend on many services provided by the ecosystems in which they are situated. These ecosystem services could include provision of pollination, natural pest control, and enhanced soil nutrient cycling. Before we can study the ecosystem-level consequences of different farming strategies we should know how they impact farmland biodiversity. In chapter 5, I will conduct a global metaanalysis of published biodiversity studies that compared organic and conventional farms. There is an ongoing debate on the relative merits of these two farming strategies for biodiversity conservation in the context of increasing global food demands (Tilman et al. 2011).

I will use these studies to estimate the relative effects of organic and conventional practices across a broad range of taxa, environments and geographical regions. I will also investigate the importance of landscape-scale context, by regressing these estimated relative effects against metrics of land-use intensity. This work will inform environmental management policies and help devise strategies for agricultural development that minimise biodiversity loss. It will also lay the groundwork for future biodiversity-function studies that can link farmland biodiversity to ecosystem services across entire agricultural landscapes.

Finally, I will conclude by synthesising the results from these four studies. I will discuss each study’s contribution to the next generation of biodiversity-function research. I will then describe some of the future work that would help progress our understanding of the mechanisms and applications of biodiversity-functioning, including some emerging techniques that will facilitate this progress.

Next Page – Ch 2: Observational Methods Underestimate The Strength Of Competition Among Plant Species

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