Brian J. McGill

Warming experiments underpredict plant phenological responses to climate change

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

A test of the unified neutral theory of biodiversity

One of the fundamental questions of ecology is what controls biodiversity. Recent theory suggests that biodiversity is controlled predominantly by neutral drift of species abundances. This theory has generated considerable controversy, because it claims that many mechanisms that have long been studied by ecologists (such as niches) have little involvement in structuring communities. The theory predicts that the species abundance distribution within a community should follow a zero-sum multinomial distribution (ZSM), but this has not, so far, been rigorously tested. Specifically, it remains to be shown that the ZSM fits the data significantly better than reasonable null models. Here I test whether the ZSM fits several empirical data sets better than the lognormal distribution. It does not. Not only does the ZSM fail to fit empirical data better than the lognormal distribution 95% of the time, it also fails to fit empirical data better even a majority of the time. This means that there is no evidence that the ZSM predicts abundances better than the much more parsimonious null hypothesis.

How do traits vary across ecological scales? A case for trait-based ecology

Despite the increasing importance of functional traits for the study of plant ecology, we do not know how variation in a given trait changes across ecological scales, which prevents us from assessing potential scale-dependent aspects of trait variation. To address this deficiency, we partitioned the variance in two key functional traits (leaf mass area and leaf dry matter content) across six nested ecological scales (site, plot, species, tree, strata and leaf) in lowland tropical rainforests. In both traits, the plot level shows virtually no variance despite high species turnover among plots and the size of within-species variation (leaf + strata + tree) is comparable with that of species level variation. The lack of variance at the plot level brings substantial support to the idea that trait-based environmental filtering plays a central role in plant community assembly. These results and the finding that the amount of within-species variation is comparable with interspecific variation support a shift of focus from species-based to trait-based ecology.

Assemblage time series reveal biodiversity change but not systematic loss

Changing Assemblages Although the rate of species extinction has increased markedly as a result of human activity across the biosphere, conservation has focused on endangered species rather than on shifts in assemblages. Dornelas et al. (p. 296; see the Perspective by Pandolfi and Lovelock), using an extensive set of biodiversity time series of species occurrences in both marine and terrestrial habitats from the past 150 years, find species turnover above expected but do not find evidence of systematic biodiversity loss. This result could be caused by homogenization of species assemblages by invasive species, shifting distributions induced by climate change, and asynchronous change across the planet. All of which indicates that it is time to review conservation priorities. Ecological communities are experiencing changes in species composition rather than unidirectional loss. [Also see Perspective by Pandolfi and Lovelock] The extent to which biodiversity change in local assemblages contributes to global biodiversity loss is poorly understood. We analyzed 100 time series from biomes across Earth to ask how diversity within assemblages is changing through time. We quantified patterns of temporal α diversity, measured as change in local diversity, and temporal β diversity, measured as change in community composition. Contrary to our expectations, we did not detect systematic loss of α diversity. However, community composition changed systematically through time, in excess of predictions from null models. Heterogeneous rates of environmental change, species range shifts associated with climate change, and biotic homogenization may explain the different patterns of temporal α and β diversity. Monitoring and understanding change in species composition should be a conservation priority.

Empirical evaluation of neutral theory.

We describe a general framework for testing neutral theory. We summarize similarities and differences between ten different versions of neutral theory. Two central predictions of neutral theory are that species abundance distributions will follow a zero-sum multinomial distribution and that community composition will change over space due to dispersal limitation. We review all published empirical tests of neutral theory. With the exception of one type of test, all tests fail to support neutral theory. We identify and perform several new tests. Specifically, we develop a set of best practices for testing the fit of the zero-sum multinomial (ZSM) vs. a lognormal null hypothesis and apply this to a data set, concluding that the lognormal outperforms neutral theory on robust tests. We explore whether a priori parameterization of neutral theory is possible, and we conclude that it is not. We show that non-curve-fitting predictions readily derived from neutral theory are easily falsifiable. In toto, there is a current overwhelming weight of evidence against neutral theory. We suggest some next steps for neutral theory.

Matters of Scale

Recognition of the scale dependence of ecological processes helps explain the distribution and abundance of organisms. In 1687, Newton reported that the same laws could describe Galileos data on balls rolling down ramps and Brahes data on planets moving around the Sun (1). This observation implied that a finite list of principles could explain our infinite universe. And it inspired a leap across scales: The rules at human scales are not unique. Newtons laws of motion are still the dominant explanatory tool across scales ranging from a few atoms to solar systems. However, over the past 25 years, ecologists have come to realize that, unlike physics, ecology is scale-dependent (2–4). In a recent paper, Gotelli, Graves, and Rahbek (5) highlight the importance of this scale dependence: They show that a process that occurs at small spatial scales, namely competition between individuals, plays an important role even at the large scale of an entire country.

Fifteen forms of biodiversity trend in the Anthropocene

Humans are transforming the biosphere in unprecedented ways, raising the important question of how these impacts are changing biodiversity. Here we argue that our understanding of biodiversity trends in the Anthropocene, and our ability to protect the natural world, is impeded by a failure to consider different types of biodiversity measured at different spatial scales. We propose that ecologists should recognize and assess 15 distinct categories of biodiversity trend. We summarize what is known about each of these 15 categories, identify major gaps in our current knowledge, and recommend the next steps required for better understanding of trends in biodiversity.

Towards a unification of unified theories of biodiversity

A unified theory in science is a theory that shows a common underlying set of rules that regulate processes previously thought to be distinct. Unified theories have been important in physics including the unification of electricity and magnetism and the unification of the electromagnetic with the weak nuclear force. Surprisingly, ecology, specifically the subfields of biodiversity and macroecology, also possess not one but at least six unified theories. This is problematic as only one unified theory is desirable. Superficially, the six unified theories seem very different. However, I show that all six theories use the same three rules or assertions to describe a stochastic geometry of biodiversity. The three rules are: (1) intraspecifically individuals are clumped together; (2) interspecifically global or regional abundance varies according to a hollow curve distribution; and (3) interspecifically individuals are placed without regard to individuals of other species. These three rules appear sufficient to explain local species abundance distributions, species-area relationships, decay of similarity of distance and possibly other patterns of biodiversity. This provides a unification of the unified theories. I explore implications of this unified theory for future research.

Functional trait space and the latitudinal diversity gradient

Significance We present a conceptual framework for testing theories for the latitudinal gradient of species richness in terms of variation in functional diversity at the alpha, beta, and gamma scales. We compared ecological community theory with large-scale observational data of tree species richness and functional diversity. We found that the patterns of functional trait diversity are not consistent with any one theory of species diversity. These conflicting results indicate that none of the broad classes of biodiversity theory considered here is alone able to explain the latitudinal gradient of species diversity in terms of functional trait space. The processes causing the latitudinal gradient in species richness remain elusive. Ecological theories for the origin of biodiversity gradients, such as competitive exclusion, neutral dynamics, and environmental filtering, make predictions for how functional diversity should vary at the alpha (within local assemblages), beta (among assemblages), and gamma (regional pool) scales. We test these predictions by quantifying hypervolumes constructed from functional traits representing major axes of plant strategy variation (specific leaf area, plant height, and seed mass) in tree assemblages spanning the temperate and tropical New World. Alpha-scale trait volume decreases with absolute latitude and is often lower than sampling expectation, consistent with environmental filtering theory. Beta-scale overlap decays with geographic distance fastest in the temperate zone, again consistent with environmental filtering theory. In contrast, gamma-scale trait space shows a hump-shaped relationship with absolute latitude, consistent with no theory. Furthermore, the overall temperate trait hypervolume was larger than the overall tropical hypervolume, indicating that the temperate zone permits a wider range of trait combinations or that niche packing is stronger in the tropical zone. Although there are limitations in the data, our analyses suggest that multiple processes have shaped trait diversity in trees, reflecting no consistent support for any one theory.

Quantifying temporal change in biodiversity: challenges and opportunities

Growing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series—lack of physical boundaries, uni-dimensionality, autocorrelation and directionality—that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.