skip to main content


Title: Vegetation demographics in Earth System Models: A review of progress and priorities
Abstract

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics inESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real‐world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first‐generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter‐disciplinary communication.

 
more » « less
NSF-PAR ID:
10045664
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  more » ;  ;  ;  ;  ;  ;  ;  ;   « less
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Global Change Biology
Volume:
24
Issue:
1
ISSN:
1354-1013
Format(s):
Medium: X Size: p. 35-54
Size(s):
p. 35-54
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the originalESMinto one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically‐resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standardCLM4.5 across different spatial‐temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts ofCO2fertilization on litter andSOCdynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin‐up, permit thorough parametric sensitivity tests, enable pool‐based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.

     
    more » « less
  2. Abstract

    In semiarid regions, vegetation constraints on plant growth responses to precipitation (PPT) are hypothesized to place an upper limit on net primary productivity (NPP), leading to predictions of future shifts from currently defined linear to saturatingNPPPPTrelationships as increases in both dry and wetPPTextremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing seasonPPT(GSP,n = 11 levels,n = 4 replicates), ranging from the driest to wettest conditions in the 75‐yr climate record, within a semiarid grassland. We focused on responses of two key ecosystem processes: abovegroundNPP(ANPP) and soil respiration (Rs).ANPPandRsboth exhibited greater relative responses to wet vs. dryGSPextremes, with a linear relationship consistently best explaining the response of both processes toGSP. However, this responsiveness toGSPpeaked at moderate levels of extremity for both processes, and declined at the most extremeGSPlevels, suggesting that greater sensitivity ofANPPandRsto wet vs. dry conditions may diminish under increased magnitudes ofGSPextremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover asGSPtransitioned to extreme wet conditions. This compositional shift increased the magnitude ofANPPresponses to wetGSPextremes, as well as the slope and variability explained in theANPPGSPrelationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes inGSPextremes.

     
    more » « less
  3. Abstract Aims

    Bryophytes can cover three quarters of the ground surface, play key ecological functions, and increase biodiversity in mesic high‐elevation conifer forests of the temperate zone. Forest gaps affect species coexistence (and ecosystem functions) as suggested by the gap and gap‐size partitioning hypotheses (GPH,GSPH). Here we test these hypotheses in the context of high‐elevation forest bryophyte communities and their functional attributes.

    Study Site

    Spruce–fir forests on Whiteface Mountain, NY,USA.

    Methods

    We characterized canopy openness, microclimate, forest floor substrates, vascular vegetation cover, and moss layer (cover, common species, and functional attributes) in three canopy openness environments (gap, gap edge, forest canopy) across 20 gaps (fir waves) (n = 60); the functional attributes were based on 16 morphologic, reproductive, and ecological bryophyte plant functional traits (PFTs). We testedGPHandGSPHrelative to bryophyte community metrics (cover, composition), traits, and trait functional sensitivity (functional dispersion;FDis) using indicator species analysis, ordination, and regression.

    Results

    Canopy openness drove gradients in ground‐level temperature, substrate abundance and heterogeneity (beta diversity), and understory vascular vegetation cover. TheGPHwas consistent with (a) the abundance patterns of forest canopy indicator species (Dicranum fuscescens,Hypnum imponens, andTetraphis pellucida), and (b)FDisbased on threePFTs (growth form, fertility, and acidity), both increasing with canopy cover. We did not find support forGPHin the remaining species or traits, or forGSPHin general; gap width (12–44 m) was not related to environmental or bryophyte community gradients.

    Conclusions

    The observed lack of variation in most bryophyte metrics across canopy environments suggests high resistance of the bryophyte layer to natural canopy gaps in high‐elevation forests. However, responses of forest canopy indicator species suggest that canopy mortality, potentially increased by changing climate or insect pests, may cause declines in some forest canopy species and consequently in the functional diversity of bryophyte communities.

     
    more » « less
  4. Abstract

    Environmental gradients have played a pivotal role in the history and development of plant ecology and are useful for testing ecological and evolutionary theory. Área de Conservación Guanacaste is a spatio‐temporal mosaic of forests that have evolved continuously across elevation, topography, soil types, succession, and annual and inter‐annual climatic change. Studies of plant ecology across diverse gradients ofACGhave shaped functional ecology, successional theory, community assembly, plant–herbivore interactions, among many other fields. In this review, we synthesize the, perhaps overlooked, role plant ecological studies ofACGhave had on our understanding of tropical forest dynamics. We outline present‐day processes that will have major impacts on forest dynamics ofACGin the future and highlight howACGwill continue to shape future research priorities in plant ecology.

    Abstract in Spanish is available with online material.

     
    more » « less
  5. Abstract

    This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of theSanakArchipelago in theEasternAleutianIslands,Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two‐thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power‐law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling.

     
    more » « less