skip to main content


Title: Structural diversity as a predictor of ecosystem function
Abstract

Biodiversity is believed to be closely related to ecosystem functions. However, the ability of existing biodiversity measures, such as species richness and phylogenetic diversity, to predict ecosystem functions remains elusive. Here, we propose a new vector of diversity metrics, structural diversity, which directly incorporates niche space in measuring ecosystem structure. We hypothesize that structural diversity will provide better predictive ability of key ecosystem functions than traditional biodiversity measures. Using the new lidar-derived canopy structural diversity metrics on 19 National Ecological Observation Network forested sites across the USA, we show that structural diversity is a better predictor of key ecosystem functions, such as productivity, energy, and nutrient dynamics than existing biodiversity measures (i.e. species richness and phylogenetic diversity). Similar to existing biodiversity measures, we found that the relationships between structural diversity and ecosystem functions are sensitive to environmental context. Our study indicates that structural diversity may be as good or a better predictor of ecosystem functions than species richness and phylogenetic diversity.

 
more » « less
Award ID(s):
1638702
NSF-PAR ID:
10303262
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IOP Publishing
Date Published:
Journal Name:
Environmental Research Letters
Volume:
14
Issue:
11
ISSN:
1748-9326
Page Range / eLocation ID:
Article No. 114011
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Aim

    Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).

    Location

    Eastern USA.

    Time period

    2017–2018.

    Taxa studied

    Trees.

    Methods

    With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics.

    Results

    Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity.

    Main conclusions

    We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

     
    more » « less
  2. Abstract

    Efforts to catalog global biodiversity have often focused on aboveground taxonomic diversity, with limited consideration of belowground communities. However, diversity aboveground may influence the diversity of belowground communities and vice versa. In addition to taxonomic diversity, the structural diversity of plant communities may be related to the diversity of soil bacterial and fungal communities, which drive important ecosystem processes but are difficult to characterize across broad spatial scales. In forests, canopy structural diversity may influence soil microorganisms through its effects on ecosystem productivity and root architecture, and via associations between canopy structure, stand age, and species richness. Given that structural diversity is one of the few types of diversity that can be readily measured remotely (e.g., using light detection and ranging—LiDAR), establishing links between structural and microbial diversity could facilitate the detection of belowground biodiversity hotspots. We investigated the potential for using remotely sensed information about forest structural diversity as a predictor of soil microbial community richness and composition. We calculated LiDAR‐derived metrics of structural diversity as well as a suite of stand and soil properties from 38 forested plots across the central hardwoods region of Indiana, USA, to test whether forest canopy structure is linked with the community richness and diversity of four key soil microbial groups: bacteria, fungi, arbuscular mycorrhizal (AM) fungi, and ectomycorrhizal (EM) fungi. We found that the density of canopy vegetation is positively associated with the taxonomic richness (alpha diversity) of EM fungi, independent of changes in plant taxonomic richness. Further, structural diversity metrics were significantly correlated with the overall community composition of bacteria, EM, and total fungal communities. However, soil properties were the strongest predictors of variation in the taxonomic richness and community composition of microbial communities in comparison with structural diversity and tree species diversity. As remote sensing tools and algorithms are rapidly advancing, these results may have important implications for the use of remote sensing of vegetation structural diversity for management and restoration practices aimed at preserving belowground biodiversity.

     
    more » « less
  3. Globally, biodiversity has declined at an unprecedented rate, challenging the viability of ecosystems, species, and ecological functions and their corresponding services. Payments for ecosystem services (PES) programs have been established and implemented worldwide to combat the degradation or loss of essential ecosystems and ecosystem services with-out sacrificing the well-being of people. With an overarching goal of reducing soil ero-sion, China’s Grain-to-Green program (GTGP) converts cropland to forest or grassland. As one of the largest PES programs in the world, GTGP has great potential to offer biodi-versity conservation co-benefits. To consider how GTGP may influence biodiversity, we measured forest structure and plant and wildlife species diversity at both GTGP forest and natural forest sites in Fangjingshan National Nature Reserve, China. We also evaluated the relationship between canopy cover and biodiversity measures to test whether forest cover, the most commonly measured and reported ecological metric of PES programs, might act as a good proxy for other biodiversity related parameters. We found that forest cover and species diversity increased after GTGP implementation as understory and overstory plant cover, and understory and midstory plant diversity at GTGP sites were similar to natural forest. Our results suggest that GTGP may also have been associated with increased habitat for protected and vulnerable wildlife species including Elliot’s pheasant (Syrmaticus elli-oti), hog badger (Arctonyx collaris), and wild boar (Sus scrofa). Nevertheless, we identi-fied key differences between GTGP forest and natural forest, particularly variation in forest types and heterogeneity of overstory vegetation. As a result, plant overstory diversity and wildlife species richness at GTGP forest were significantly lower than at natural forest. Our findings suggest, while forest cover may be a good proxy for some metrics of forest struc-ture, it does not serve as a robust proxy for many biodiversity parameters. These findings highlight the need for and importance of robust and representative indicators or proxy vari-ables for measuring ecological effects of PES programs on compositional and structural diversity. We demonstrate that PES may lead to biodiversity co-benefits, but changes in program implementation could improve the return on investment of PES programs to sup-port conservation of biodiversity. 
    more » « less
  4. Abstract Aim

    Canopy structural complexity, which describes the degree of heterogeneity in vegetation density, is strongly tied to a number of ecosystem functions, but the community and structural characteristics that give rise to variation in complexity at site to subcontinental scales are poorly defined. We investigated how woody plant taxonomic and phylogenetic diversity, maximum canopy height, and leaf area index (LAI) relate to canopy rugosity, a measure of canopy structural complexity that is correlated with primary production, light capture, and resource‐use efficiency.

    Location

    Our analysis used 122 plots distributed across 10 ecologically and climatically variable forests spanning a > 1,500 km latitudinal gradient within the National Ecological Observatory Network (NEON) of the USA.

    Time period

    2016–2018.

    Taxa studied

    Woody plants.

    Methods

    We used univariate and multivariate modelling to examine relationships between canopy rugosity, and community and structural characteristics hypothesized to drive site and subcontinental variation in complexity.

    Results

    Spatial variation in canopy rugosity within sites and across the subcontinent was strongly and positively related to maximum canopy height (r2 = .87 subcontinent‐wide), with the addition of species richness in a multivariate model resolving another 2% of the variation across the subcontinent. Individually, woody plant species richness and phylogenetic diversity (r2 = .17 to .44, respectively) and LAI (r2 = .16) were weakly to moderately correlated with canopy rugosity at the subcontinental scale, and inconsistently explained spatial variation in canopy rugosity within sites.

    Main conclusions

    We conclude that maximum canopy height is a substantially stronger predictor of complexity than diversity or LAI within and across forests of eastern North America, suggesting that canopy volume places a primary constraint on the development of structural complexity. Management and land‐use practices that encourage and sustain tall temperate forest canopies may support greater complexity and associated increases in ecosystem functioning.

     
    more » « less
  5. Abstract

    Phylogenetic and species‐based taxonomic descriptions of community structure may provide complementary information about the mechanisms driving community assembly across different environments. Environmental filtering may have similar effects on taxonomic and phylogenetic diversity under the assumption of niche conservatism, whereas competitive exclusion could produce contrasting patterns in these diversity metrics. In grassland restorations, these diversity patterns might then reveal potential assembly mechanisms underlying the impacts of restoration and management conditions on community structure.

    We compared plant community structure (alpha diversity, composition, and within‐site beta diversity) from both phylogenetic and taxonomic perspectives. Using surveys from 120 tallgrass prairie restorations in four regions of the Midwestern United States, we examined the effects of four potential drivers or environmental gradients: precipitation in the first year of restoration, seed mix richness, time since last prescribed fire, and restoration age, and included soil conditions as a covariate.

    First‐year precipitation influenced taxonomic community structure, but had weak effects on phylogenetic diversity and composition. Similarly, greater seed mix richness increased taxonomic diversity but did not influence phylogenetic diversity. Taxonomic, but not phylogenetic, diversity generally was lower in older restorations and those with a longer time since the last prescribed fire. These drivers consistently explained more variation in taxonomic than phylogenetic diversity and composition, perhaps in part because species turnover was largely among related species, producing weak impacts on phylogenetic community measures.

    An impact of precipitation on taxonomic but not phylogenetic diversity suggests that there may not be large differences in drought tolerance among clades that would cause phylogenetic patterns to arise from this environmental filter. Declining taxonomic diversity but not phylogenetic diversity is consistent with competitive exclusion as an assembly mechanism when competition is strongest between related species.

    Synthesis. This research shows how studying taxonomic and phylogenetic diversity of ecosystem restorations can inform plant community ecology and help natural resource managers better predict the outcomes of restoration actions and management.

     
    more » « less