Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States

Atmospheric nitrogen (N) deposition has been shown to decrease plant species richness along regional deposition gradients in Europe and in experimental manipulations. However, the general response of species richness to N deposition across different vegetation types, soil conditions, and climates remains largely unknown even though responses may be contingent on these environmental factors. We assessed the effect of N deposition on herbaceous richness for 15,136 forest, woodland, shrubland, and grassland sites across the continental United States, to address how edaphic and climatic conditions altered vulnerability to this stressor. In our dataset, with N deposition ranging from 1 to 19 kg N⋅ha−1⋅y−1, we found a unimodal relationship; richness increased at low deposition levels and decreased above 8.7 and 13.4 kg N⋅ha−1⋅y−1 in open and closed-canopy vegetation, respectively. N deposition exceeded critical loads for loss of plant species richness in 24% of 15,136 sites examined nationwide. There were negative relationships between species richness and N deposition in 36% of 44 community gradients. Vulnerability to N deposition was consistently higher in more acidic soils whereas the moderating roles of temperature and precipitation varied across scales. We demonstrate here that negative relationships between N deposition and species richness are common, albeit not universal, and that fine-scale processes can moderate vegetation responses to N deposition. Our results highlight the importance of contingent factors when estimating ecosystem vulnerability to N deposition and suggest that N deposition is affecting species richness in forested and nonforested systems across much of the continental United States.

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The Botanist Effect Revisited: Plant Species Richness, County Area, and Human Population Size in the United States

Conservation Biology ◽

10.1111/j.1523-1739.2007.00760.x ◽

2007 ◽

Vol 21 (5) ◽

pp. 1333-1340 ◽

Cited By ~ 50

Author(s):

MARCO PAUTASSO ◽

MICHAEL L. McKINNEY

Keyword(s):

United States ◽

Species Richness ◽

Population Size ◽

Plant Species ◽

Human Population ◽

Plant Species Richness ◽

The United States

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Comment on Pescott & Jitlal 2020: Failure to account for measurement error undermines their conclusion of a weak impact of nitrogen deposition on plant species richness

10.1101/2020.05.12.091272 ◽

2020 ◽

Author(s):

SM Smart ◽

CJ Stevens ◽

SJ Tomlinson ◽

LC Maskell ◽

PA Henrys

Keyword(s):

Species Richness ◽

Measurement Error ◽

Plant Species ◽

Large Scale ◽

Plant Species Richness ◽

N Deposition ◽

Spatial Gradient ◽

Spatial Gradients ◽

Deposition Effect ◽

Time Substitution

AbstractEstimation of the impacts of atmospheric nitrogen (N) deposition on ecosystems and biodiversity is a research imperative. Analyses of large-scale spatial gradients, where an observed response is correlated with measured or modelled deposition, have been an important source of evidence. A number of problems beset this approach. For example, if responses are spatially aggregated then treating each location as statistically independent can lead to biased confidence intervals and a greater probably of false positive results.Using sophisticated methods that account for residual spatial autocorrelation Pescott & Jitlal (2020) re-analysed two large-scale spatial gradient datasets from Britain where modelled N deposition at 5×5km resolution had been previously correlated with species richness in small quadrats. They found that N deposition effects were weaker than previously demonstrated leading them to conclude that “..previous estimates of Ndep impacts on richness from space-for-time substitution studies are likely to have been over-estimated”. We use a simple simulation study to show that their conclusion is flawed. They failed to recognise that an influential fraction of the residual spatially structured variation could itself be attributable to N deposition. This arises because the covariate used was modelled N deposition at 5×5km resolution leaving open the possibility that measured or modelled N deposition at finer resolutions could explain more variance in the response. Explicitly treating this as spatially auto-correlated error ignores this possibility and leads directly to their unreliable conclusion. We further demonstrate the plausibility of this scenario by showing that significant variation in N deposition at the 1km square resolution is indeed averaged at 5×5km resolution.Further analyses are required to explore whether estimation of the size of the N deposition effect on plant species richness and other measures of biodiversity is indeed dependent on the accuracy and hence measurement error of the N deposition covariate. Until then the conclusions of Pescott & Jitlal (2020) should be considered premature and not proven.

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Comment on Pescott & Jitlal 2020: Failure to account for measurement error undermines their conclusion of a weak impact of nitrogen deposition on plant species richness

PeerJ ◽

10.7717/peerj.10632 ◽

2021 ◽

Vol 9 ◽

pp. e10632

Author(s):

Simon M. Smart ◽

Carly J. Stevens ◽

Sam J. Tomlinson ◽

Lindsay C. Maskell ◽

Peter A. Henrys

Keyword(s):

Species Richness ◽

Measurement Error ◽

Plant Species ◽

Large Scale ◽

Plant Species Richness ◽

N Deposition ◽

Spatial Gradient ◽

Spatial Gradients ◽

Deposition Effect ◽

Time Substitution

Estimation of the impacts of atmospheric nitrogen (N) deposition on ecosystems and biodiversity is a research imperative. Analyses of large-scale spatial gradients, where an observed response is correlated with measured or modelled deposition, have been an important source of evidence. A number of problems beset this approach. For example, if responses are spatially aggregated then treating each location as statistically independent can lead to biased confidence intervals and a greater probably of false positive results. Using methods that account for residual spatial autocorrelation, Pescott & Jitlal (2020) re-analysed two large-scale spatial gradient datasets from Britain where modelled N deposition at 5 × 5 km resolution had been previously correlated with species richness in small quadrats. They found that N deposition effects were weaker than previously demonstrated leading them to conclude that “previous estimates of Ndep impacts on richness from space-for-time substitution studies are likely to have been over-estimated”. We use a simulation study to show that their conclusion is unreliable despite them recognising that an influential fraction of the residual spatially structured variation could itself be attributable to N deposition. This arises because the covariate used was modelled N deposition at 5 × 5 km resolution leaving open the possibility that measured or modelled N deposition at finer resolutions could explain more variance in the response. Explicitly treating this as spatially auto-correlated error ignores this possibility and leads directly to their unreliable conclusion. We further demonstrate the plausibility of this scenario by showing that significant variation in N deposition at the 1 km square resolution is indeed averaged at 5 × 5 km resolution. Further analyses are required to explore whether estimation of the size of the N deposition effect on plant species richness and other measures of biodiversity is indeed dependent on the accuracy and hence measurement error of the N deposition covariate. Until then the conclusions of Pescott & Jitlal (2020) should be considered premature.

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Plant species richness, identity and productivity differentially influence key groups of microbes in grassland soils of contrasting fertility

Biology Letters ◽

10.1098/rsbl.2010.0575 ◽

2010 ◽

Vol 7 (1) ◽

pp. 75-78 ◽

Cited By ~ 90

Author(s):

Gerlinde B. De Deyn ◽

Helen Quirk ◽

Richard D. Bardgett

Keyword(s):

Species Richness ◽

Plant Species ◽

Mycorrhizal Fungi ◽

Plant Biomass ◽

Phospholipid Fatty Acid ◽

Plant Species Richness ◽

Plant Production ◽

Soil Conditions ◽

High Fertility ◽

Per Se

The abundance of microbes in soil is thought to be strongly influenced by plant productivity rather than by plant species richness per se . However, whether this holds true for different microbial groups and under different soil conditions is unresolved. We tested how plant species richness, identity and biomass influence the abundances of arbuscular mycorrhizal fungi (AMF), saprophytic bacteria and fungi, and actinomycetes, in model plant communities in soil of low and high fertility using phospholipid fatty acid analysis. Abundances of saprophytic fungi and bacteria were driven by larger plant biomass in high diversity treatments. In contrast, increased AMF abundance with larger plant species richness was not explained by plant biomass, but responded to plant species identity and was stimulated by Anthoxantum odoratum . Our results indicate that the abundance of saprophytic soil microbes is influenced more by resource quantity, as driven by plant production, while AMF respond more strongly to resource composition, driven by variation in plant species richness and identity. This suggests that AMF abundance in soil is more sensitive to changes in plant species diversity per se and plant species composition than are abundances of saprophytic microbes.

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