Papers

​Avolio, ML, La Pierre, KJ, Houseman, GR, Koerner, SE, Grman, E, Isbell, F, Johnson, DS, Wilcox, KR. 2015. A framework for quantifying the magnitude and variability of community responses to global change drivers. Ecosphere 6: art280.
  • Global change drivers (GCDs) can drastically affect plant community composition, with consequences for ecosystem function.
  • Typical methods to study community changes condense complex community changes to univariate measures and focus on mean differences among treatments.
  • We suggest studying changes in means and variability of replicates using multivatiate measures, such as dissimilarity metrics, which consider the entire community response to GCDs.
  • Additionally, we suggested using rank abundance curves (RACs) alongside measures of community dissimilarity to understand how the community changed.
  • In such a way, we can improve our ability to predict community responses to global change drivers across a wide variety of systems.
Picture
Global change drivers alter abiotic or biotic conditions that influence a wide range of potential mechanisms that change communities. Using rank abundance curves in conjunction with community dissimilarity measures provides insight into the magnitude and predictability of community change.
Wilcox, KR,  Tredennick, AT, Koerner, SE, Grman, E, Hallett, LM, Avolio, ML, La Pierre, KJ, Houseman, GR, Isbell, F, Johnson, DS, Alatalo, JM, Baldwin, AH, Bork, EW, Boughton, EH, Bowman, WD, Britton, AJ, Cahill JF Jr., Collins, SL, Du, G,  Eskelinen, A, Gough, L, Jentsch, A, Kern, C, Klanderud, K, Knapp, AK, Kreyling, J,  Luo, Y, McLaren, JR, Megonigal, P, Onipchenko, V, Prevéy, J, Price, JN, Robinson, CH, Sala, OE, Smith MD, Soudzilovskaia, NA, Souza, L, Tilman, D, White, SR, Xu, Z, Yahdjian, L, Yu, Q, Zhang, P, Zhang, Y. 2016. Asynchrony among local communities stabilises ecosystem function of metacommunities.  Ecology Letters 20: 1534-1545
  • Stability of ecosystems through time is important for predicting ecosystem services from year to year and for preventing ecosystems from crossing catastrophic thresholds under extreme environmental conditions, such as drought.
  • Stability of entire metacommunities (i.e., large mosaics of different local communities or patches) might be driven by two main factors: 1) how stable individual patches are through time, and 2) asynchrony among patches – or how out-of-sync local patches are with one other through time.
  • First, we found that the stability of metacommunities (gamma stability in the accompanying figure) was indeed strongly correlated with the stability of individual patches (alpha stability).
  • Second, we found very strong effects of patch asynchrony on meta-community stability. This asynchrony enhanced metacommunity stability by as much as 300%.
  • So, to maintain the stability of landscapes, we need to promote and conserve heterogeneity of physical and biotic characteristics. In other words: Patchiness matters!
Langley, AJ,  Chapman, SK, Avolio, ML, Bowman, WD, Johnson, DS, La Pierre, KJ, Isbell, F, Wilcox, KR, Foster, BL, Hovenden, MJ, Knapp, AK, Koerner,  SE, Lortie, C, IN , JP, Newton, P, Reich, PB, Smith, MD, Suttle, B, Tilman D. Ambient changes exceed treatment effects on plant species abundance in global change experiments. Global Change Biology 24: 5668-5679.
  • Global change experiments compare manipulated plots to ambient control plots to understand how plant communities will respond to environmental changes, but these responses have not been compared to plant community changes occurring the background.
  • We used plant species abundance data from 16 long-term experiments (>10 years) to compare the magnitude of treatment effects (CO2, N, P, water, warming) to the rate of change in unmanipulated, control plots (ambient change).
  • We found that the rate of long-term directional change in ambient plots through time is greater than the influence of the treatment on that rate of change for 57% of species.
  • Previous evidence suggests that ongoing environmental change is dramatically altering terrestrial plant communities. Our findings show that these changes may be strongly shifting the baseline by which we gauge conventional treatment effects, and should be considered in experimental design and interpretation. 

Komatsu, KJ, Avolio, ML, Lemoine, NP, Isbell F, Grman, E, Houseman, GR, Koerner, SE, Johnson, DS, Wilcox, KR, et al. Global change effects on plant communities are magnified by time and the number of global change factors imposed. Proceedings of the National Academy of Sciences USA (PNAS): 116: 17867-17873.

  • Humans are currently imposing a wide variety of global change drivers (GCDs) on ecosystems, which could dramatically alter their structure and consequently the services they provide. Yet there are limited broad-scale experimental investigations of the effects of these GCDs on plant community structure.
  • In 438 experimental global change treatments around the world, we show that composition of treated plant communities steadily diverged from control communities through time regardless of the GCD imposed.
  • In contrast richness responses were uncommon and when present relatively weaker than community differences between control and treated plots.
  • Interestingly, we find that the type of global change driver experimentally manipulated does not impact the magnitude or direction of community difference.
  • In the short term (<10 yrs) plant communities are robust to global change manipulations.

Avolio, ML, Carroll, IT, Collins, SL, Houseman, GR, Hallett, LM, Isbell, F, Koerner, SE, Komatsu, KJ, Smith, MD, Wilcox, KR. A comprehensive approach to analyzing community dynamics using rank abundance curves. Ecosphere 10: e02881

  • Univariate and multivariate methods are commonly used to explore the spatial and temporal dynamics of ecological communities. Both, however, have limitations, including oversimplification or abstraction of communities. Rank abundance curves are potentially a key approach to integrating these existing methodologies.
  • We develop new methods for studying temporal changes and spatial differences in rank abundance curves and introduce these metrics as functions in an update to the R package library (“codyn”), alongside other new functions to calculate univariate and multivariate metrics of community dynamics. ​

Avolio, ML, Wilcox, KR, Komatsu, KJ, Lemoine, N,  Bowman, WD, Collins, SL, Knapp, AK, Koerner, SE, Smith MD, et al. Temporal variability in production is not consistently affected by global change drivers across herbaceous-dominated ecosystems. In press in Oecologia

  • Understanding how global change drivers (GCDs) affect aboveground net primary production (ANPP) through time is essential to predicting the reliability and maintenance of ecosystem function and services in the future.
  • We found that GCD treatments increased mean ANPP. However, GCD manipulations both increased and decreased temporal variability of ANPP (24% of comparisons), with no net effect overall.
  • These inconsistent effects on temporal variation in ANPP can, in part, be attributed to site characteristics, such as mean annual precipitation and temperature as well as plant community evenness. 

Wilcox, KR, Komatsu, KJ, Avolio, ML, C2E. Improving collaborations between empiricists and modelers to advance grassland community dynamics in ecosystem models. In press at New Phytologist.

  • Incorporating plant community dynamics into ecosystem models is critical for accurate forecasting of ecosystem responses to global change. Yet, current ecosystem modeling approaches to forecast plant community change
    are from studies of forested systems and are either too coarse to capture fine-scale community dynamics or too complex to be used at large spatial scales.
  • To better represent community dynamics in ecosystem models, scientists must identify (1) how physiological and morphological traits of plant species or functional types, and their diversity, can drive changes in community structure, and (2) how community dynamics alter the distribution of traits across the entire community, which will
    lead to (3) improved ability to simulate shifts in community structure and their concurrent effects on ecosystem functioning .

In Preparation

Investigating the underlying mechanisms of plant community responses to global change
Lead authors: Meghan Avolio, Kimberly Komatsu, Kevin Wilcox, Andrew Tredennick, Emily Grman, Sally Koerner.
  • We contend there are five important ways a community can change over time. There can be a change in evenness, ranks (reordering of species within the community) and species gains and losses, which often, but not necessarily co-occurs with a change in richness. 
  • Only 45% of the time (out of 233 control - treatment comparisons) did the composition of the plant community change - but when the community did change, all aspects of the community change. There were changes in richness, evenness ranks and gains and losses of species. Additionally, community composition is change occurs more often with with CO2 and N+P than other global change drivers.

Relating plant community responses to global change drivers to productivity responses
Lead authors: Kimberly Komatsu, Meghan Avolio, Kevin Wilcox, Forest Isbell, Alan Knapp, Sally Koerner, Melinda Smith, Andrew Tredennick
  •  We have previously found that plant communities respond systematically to global change drivers around the world, however the consequences for functional differences have yet to be investigated in a large-scale synthesis.
  • Here we find that productivity responses to experimental global change drivers are initially driven by physiological responses of the existing plant community, followed by reordering of species within a community, and finally species turnover (losses and immigration). This result provides support for the Hierarchical Response Framework (Smith et al 2009).

Guidance for improving herbaceous community dynamics in Earth System Models.
Lead authors: Kevin Wilcox, Kimberly Komatsu, Meghan Avolio
  • Earth system models (ESM) are powerful tools to predict ecosystem functioning. However, few ESMs incorporate vegetation change, and those that do, only capture coarse changes.
  • Here we demonstrate that current approaches of representing community change into Earth system models often do not match observations, particularly for grasslands, using an example from a long-term resource manipulation experiment in tallgrass prairie. We also discuss commonalities in empiricist and process-based modeler goals and differences in approaches to obtain these goals. Finally, we present a roadmap for better incorporation of occurrences and impacts of community changes into ESMs.​

Global change drivers alter stability of meta-communities by synchronizing or de-synchronizing plant populations. 
Lead authors: Kevin Wilcox, Kimberly Komatsu, Sally Koerner, Meghan Avolio, Yann Hautier, Shaopeng Wang
  • Ecosystem stability is important for maintaining ecosystem services and are likely to be impacted by global change drivers. We are investigating how global change drivers alter meta-community (beta) diversity, which then scales up impact two important contributors to ecosystem (gamma) stability.
  • We find that beta-diversity is a strong driver of population synchrony . This effect is consistent across a wide array of global change drivers.

Grassland plant communities with high rates of background change show greater change with GCDs
Lead authors: Sally Koerner, Kimberly Komatsu, Meghan Avolio
  • Plant communities are continuously changing over time. These background rates of change are poorly understood and can have large impacts on system response to global change drivers.
  • Some plant communities exhibit higher rates of background change than others, and these communities were more responsive to global change treatment manipulations.

Do tradeoffs among plant species control response to different global change treatments? 
Lead authors: Adam Langley, Emily Grman
  • If plants are subject to tradeoffs among strategies to acquire different resources and to tolerate differing conditions, then we would expect plant species to exhibit differential competitive responses to different global change drivers. We used a database of global change experiments manipulating resources and conditions such as CO2, nitrogen, phosphorus, water, temperature, and disturbance to answer the question: Does plant species response to one global change treatment relate to its response to another treatment?
  •  We found minimal evidence of negative relationships among treatment effects. Instead, we found high levels of correspondence, i.e. species responses to different global change treatments tended to be more positively related than would be expected from the simulated, null dataset. That pattern was driven by species that responded negatively to any two treatments (losers), rather than those that responded positively (winners).
  • If plants species are subject to tradeoffs in the ability to respond positively to different treatments, the effects are not strong or consistent enough to elicit clear patterns across a wide variety of ecosystem types. Instead, our results suggest that most plant species are likely to respond negatively to global change, while a few winners will proliferate.