Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

Seabloom, Eric W.; Borer, Elizabeth T.; Buckley, Yvonne M.; Cleland, Elsa E.; Davies, Kendi F.; Firn, Jennifer; Harpole, W. Stanley; Hautier, Yann; Lind, Eric M.; MacDougall, Andrew S.; Orrock, John L.; Prober, Suzanne M.; Adler, Peter B.; Alberti, Juan; Anderson, T. Michael; Bakker, Jonathan D.; Biederman, Lori A.; Blumenthal, Dana M.; Brown, Cynthia S.; Brudvig, Lars A.; Caldeira, María C.; Chu, Chengjin; Crawley, Michael J.; Daleo, Pedro; Damschen, Ellen I.; D’Antonio, Carla M.; DeCrappeo, Nicole M.; Dickman, Chris R.; Du, Guozhen; Fay, Philip A.; Frater, Paul N.; Gruner, Daniel S.; Hagenah, Nicole; Hector, Andrew; Helm, Aveliina; Hillebrand, Helmut; Hofmockel, Kirsten; Humphries, Hope C.; Iribarne, Oscar; Jin, Virginia L.; Kay, Adam; Kirkman, Kevin; Klein, Julia A.; Knops, Johannes M. H.; Pierre, Kimberly J. La; Ladwig, Laura M.; Lambrinos, John G.; Leakey, Andrew D. B.; Li, Qi; Wei, Li; McCulley, Rebecca L.; Melbourne, Brett A.; Mitchell, Charles E.; Moore, Joslin L.; Morgan, John; Mortensen, Brent; O’Halloran, Lydia R.; Pärtel, Meelis; Pascual, Jesús; Pyke, David A.; Risch, Anita C.; Salguero‐Gómez, Roberto; Sankaran, Mahesh; Schuetz, Martin; Simonsen, Anna K.; Smith, Melinda D.; Stevens, Carly J.; Sullivan, Lauren K.; Wardle, Glenda M.; Wolkovich, Elizabeth M.; Wragg, Peter D.; Wright, Justin P.; Yang, Louie H.

doi:10.1111/gcb.12370

Cited by 77 publications

(94 citation statements)

References 67 publications

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“…The four fields studied at the Blandy Experimental Farm differ in land use history [1] and in soil characteristics. Therefore, it is important to take land use history into account when studying invaded systems [55,56] and secondary successional systems [54,57]. Additionally, species composition can influence soil characteristics by mechanically changing the soil, affecting nutrient cycling, altering soil biota, and by changing herbivore community compositions [5,58].…”

Section: Other Considerationsmentioning

confidence: 99%

Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Aneece

Epstein

2015

Remote Sensing

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Abandoned agricultural fields have recently become more abundant in the U.S. and remain susceptible to species invasions after cultivation disturbance. As invasive species become more widespread with increases in anthropogenic activities, we need more effective ways to use limited resources for conservation of native ecosystems. Remote sensing can help us monitor the spread and effects of invasive species, and thus determine the species and locations to target for conservation. To examine this potential, we studied plant communities dominated by exotic invasive plant species in secondary successional fields in northern Virginia using ground-level hyperspectral data. Within these communities, ordination analyses of vegetation surveys revealed differences in species compositions among plots and fields. These differences among communities were also observed in the spectral data. Stepwise multiple linear regression analyses to determine which species influenced the ordination axes revealed that many of the influential species are considered invasive, again underscoring the influence of invasive species on community properties. Stepwise regression analyses also revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from the visible to the near-infrared regions. A discriminant analysis using wavelengths selected with a principal components analysis demonstrated that different plant communities were separable using spectral data. These spectrally observable differences suggest that we can use hyperspectral data to distinguish among invasive-dominated successional plant communities in this region.

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Section: Other Considerationsmentioning

confidence: 99%

Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Aneece

Epstein

2015

Remote Sensing

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“…Understanding relationships between the diversity and abundance of native versus exotic plant species (hereafter native-exotic relationships), and the factors that regulate these relationships, are thus fundamental to management of native and exotic species (Hobbs and Huenneke 1992;Suding and Gross 2006;Seabloom et al 2013;MacDougall et al 2014). Ecological theory predicts positive, neutral or negative relationships (Shea and Chesson 2002;Fridley et al 2007;Seabloom et al 2013), depending on the underlying drivers of native versus exotic diversity or abundance.…”

Section: Introductionmentioning

confidence: 99%

“…Ecological theory predicts positive, neutral or negative relationships (Shea and Chesson 2002;Fridley et al 2007;Seabloom et al 2013), depending on the underlying drivers of native versus exotic diversity or abundance.…”

Section: Introductionmentioning

confidence: 99%

“…We focused on native plant species richness at the plot scale as a key component of diversity (the number of taxa and their abundance; Whittaker 1972) relevant to biodiversity conservation. Although earlier analyses have often focused on exotic richness, recent studies highlight exotic abundance as the more effective measure of the extent of plant invasions and associated management success (Suding and Gross 2006;Seabloom et al 2013); consequently we focused on exotic cover in our analysis (noting similar although weaker results were obtained using exotic richness). Our experiments involved replicated burning, mowing and grazing regimes at two sites with contrasting management histories (frequent-burnt versus long-unburnt) and variable inter-annual rainfall.…”

Section: Introductionmentioning

confidence: 99%

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Competing drivers lead to non-linear native–exotic relationships in endangered temperate grassy woodlands

2016

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Relationships between the diversity and abundance of native versus exotic species underpin management of disturbance regimes for conservation. Theory predicts negative, positive or neutral relationships depending on respective drivers, with greatest potential benefit when natives and exotics show opposing responses to management. We examined drivers of exotic plant cover and relationships with native plant richness using 12-year burning, mowing and grazing experiments in two representative temperate grassy eucalypt woodlands with contrasting histories of frequent versus infrequent disturbance. We hypothesized that disturbance and high resources favour exotics, and assessed whether natives and exotics covary positively due to common external drivers or negatively due to contrasting external drivers and/or competition. Positive relationships with rainfall and disturbance explained [80 % of the variation in exotic cover at both sites, supporting our first hypothesis. Native-exotic relationships were nonlinear, with native richness first increasing rapidly with increasing exotic cover, then levelling and beginning to decrease. Common external drivers, particularly inter-annual rainfall, explained initial positive relationships, highlighting a prevalence of positive relationships at long temporal (as well as large spatial) scales. At the historically frequently-burnt site, a concomitant increase in native richness and exotic cover after fire contributed to the positive relationship, indicating a management trade-off. At the long-unburnt site, exotics increased but natives decreased with fire, suggesting dual benefits of low fire frequency. We conclude that relationships between exotic cover and native richness emerge from interactions among external drivers and competitive responses, with responses to external drivers dominating at low resources and negative interactions gaining importance as resources increase.Electronic supplementary material The online version of this article (

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“…The four fields studied at the Blandy Experimental Farm differ in land use history (Wang et al, 2010) and in soil characteristics. Therefore, it is important to take land use history into account when studying invaded systems (Rooney and Rogers, 2011;Seabloom et al, 2013) and secondary successional systems (Arroyo-Mora et al, 2005;Riedel and Epstein, 2005). Additionally, species composition can influence soil characteristics by mechanically changing the soil, affecting nutrient cycling, altering soil biota, and by changing herbivore community compositions (DeMeester and deB.…”

Section: Other Considerationsmentioning

confidence: 99%

Assessing the Role of Invasive Species in Successional Plant Communities Using Hyperspectral Remote Sensing

Aneece¹

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I AbstractBiodiversity has been correlated with ecosystem stability and function. Invasive species can decrease biodiversity and cause ecological and economical damage. These species are especially prevalent in abandoned agricultural fields, and can disrupt secondary successional dynamics. Although field surveys are used to assess the impacts of these species, remote sensing can be more efficient, especially at large spatial extents. I examined the ability to use ground-level hyperspectral remote sensing to study invasive species and their effects on community properties at the Blandy Experimental Farm (BEF) in north-central Virginia. Their effects on ecosystem properties could not be assessed using ground-level remote sensing in this system; thus, I used leaf and soil measurements to assess their effects on secondary succession.I found that remote sensing can be used to differentiate among plant communities.The most influential species to community discriminability are considered invasive, suggesting that these species can strongly influence species compositions and other community properties. The most influential wavelengths for discrimination were distributed throughout the spectral profile and corresponded with plant physiological and structural elements.Thus, spectral differences across species were large enough to be used in aggregate to differentiate plant communities. Additionally, these differences were large enough to differentiate individual species, but discriminability varied by species. The two thistle species that are similar phylogenetically and structurally were readily distinguished amongst each other. However, the shrubby buckthorn was difficult to distinguish from the oriental bittersweet vine despite phylogenetic distance and differences in structure. This was likely due to physical overlap in the field and thus the difficulty in obtaining pure signatures for discrimination. Discriminability also differed by the spectral region examined. Buckthorn and oriental bittersweet were least discriminable in the 550-599 nm and 650-699 nm regions, due 2 to greater intraspecific variability of spectral data in these regions.Additionally, remote sensing can be used to estimate higher order community properties like species diversity, and thus assess the effects of invasive species on plant diversity.However, correlations between species diversity and spectral diversity varied by the spectral transformation technique used and the spectral region examined. There was a strong positive correlation between the two in the visible region when band depth was used and in the near-infrared region when first derivatives were used. There were no strong correlations in the red edge, due to high intraspecific variability in chlorophyll content.Lastly, I assessed the effects of these exotic invasive species on ecosystem properties, specifically secondary succession, using leaf and soil data. Differences in soil characteristics were larger across fields and stages than across species. However, there were species-level ...

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Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

Cited by 77 publications

References 67 publications

Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Competing drivers lead to non-linear native–exotic relationships in endangered temperate grassy woodlands

Assessing the Role of Invasive Species in Successional Plant Communities Using Hyperspectral Remote Sensing

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