Climate change effects on red spruce decline mitigated by reduction in air pollution within its shrinking habitat range

Koo, Kyung Ah; Patten, Bernard C.; Teskey, Robert O.; Creed, Irena F.

doi:10.1016/j.ecolmodel.2014.07.017

Cited by 18 publications

(32 citation statements)

References 64 publications

(89 reference statements)

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“…In this and our other studies of red spruce in GSMNP [12][13][14]46], GIS treatment of many within-and across-scale interactions in ARIM.HAB, through ARIM.SIM operating at the pixel level, has served to clarify the many mechanisms involved in translating global-scale climate change effects into local-scale habitat suitability. ARIM.HAB consists of spatially-distributed GIS cells implemented by a non-spatial simulation model, ARIM.SIM.…”

Section: Discussionmentioning

confidence: 99%

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Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

Koo

Patten

Madden

2015

Forests

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Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species' distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable OPEN ACCESSForests 2015, 6 1209 habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low-and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.

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Section: Discussionmentioning

confidence: 99%

“…ARIM.SIM simulated red spruce growth from 2080 to 2099 for each cell in ARIM.HAB under climate change and the three previously indicated air pollution scenarios: 10% increase, 0% change and 10% decrease [46]. Then, the 20-year simulated growth was averaged for spatial projection.…”

Section: Prediction Of Red Spruce Habitat Suitability Under Climate Cmentioning

confidence: 99%

Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

Koo

Patten

Madden

2015

Forests

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“…Understanding responses of forest canopy tree species to changing climate is particularly important because trees are foundational organisms (cf., Ellison et al, 2005) affecting emergent ecosystem properties such as nutrient cycling (Likens et al, 1970), productivity (Beck et al, 2011), or microclimate (Dov ciak & Brown, 2014, and they provide habitats for other species (Halpern et al, 2014). However, responses of tree species distributions to climate warming are variable (Lenoir et al, 2010;Zhu et al, 2012) and often modified by moisture stress (Pederson et al, 2015), land-use legacies (Lenoir et al, 2010;Nowacki & Abrams, 2015), soil conditions (Lafleur et al, 2010), atmospheric deposition (Koo et al, 2014), and migration lags (Renwick & Rocca, 2015;Wu et al, 2015) factors that should be included in studies of climate change impacts on plant distributions.…”

Section: Introductionmentioning

confidence: 99%

Tree demography suggests multiple directions and drivers for species range shifts in mountains of Northeastern United States

Wason

Dovčiak

2016

Global Change Biology

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Climate change is expected to lead to upslope shifts in tree species distributions, but the evidence is mixed partly due to land-use effects and individualistic species responses to climate. We examined how individual tree species demography varies along elevational climatic gradients across four states in the northeastern United States to determine whether species elevational distributions and their potential upslope (or downslope) shifts were controlled by climate, land-use legacies (past logging), or soils. We characterized tree demography, microclimate, land-use legacies, and soils at 83 sites stratified by elevation (~500 to ~1200 m above sea level) across 12 mountains containing the transition from northern hardwood to spruce-fir forests. We modeled elevational distributions of tree species saplings and adults using logistic regression to test whether sapling distributions suggest ongoing species range expansion upslope (or contraction downslope) relative to adults, and we used linear mixed models to determine the extent to which climate, land use, and soil variables explain these distributions. Tree demography varied with elevation by species, suggesting a potential upslope shift only for American beech, downslope shifts for red spruce (more so in cool regions) and sugar maple, and no change with elevation for balsam fir. While soils had relatively minor effects, climate was the dominant predictor for most species and more so for saplings than adults of red spruce, sugar maple, yellow birch, cordate birch, and striped maple. On the other hand, logging legacies were positively associated with American beech, sugar maple, and yellow birch, and negatively with red spruce and balsam fir - generally more so for adults than saplings. All species exhibited individualistic rather than synchronous demographic responses to climate and land use, and the return of red spruce to lower elevations where past logging originally benefited northern hardwood species indicates that land use may mask species range shifts caused by changing climate.

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“…To quantify CSIs, there is a need for multithematic data sets that span potentially extensive spatial and/or temporal scales, depending on the ecological phenomena of interest (Koo et al. , Soranno et al. , Keane et al.…”

Section: Introductionmentioning

confidence: 99%

The statistical power to detect cross‐scale interactions at macroscales

et al. 2016

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Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land‐use change operate at large spatial and temporal scales. Cross‐scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large‐scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

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Climate change effects on red spruce decline mitigated by reduction in air pollution within its shrinking habitat range

Cited by 18 publications

References 64 publications

Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

Tree demography suggests multiple directions and drivers for species range shifts in mountains of Northeastern United States

The statistical power to detect cross‐scale interactions at macroscales

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