Projected Effects of Climate Change on Patterns of Vertebrate and Tree Species Richness in the Conterminous United States

Ecosystems ◽  
2001 ◽  
Vol 4 (3) ◽  
pp. 216-225 ◽  
Author(s):  
David J. Currie
2021 ◽  
Author(s):  
Florian Schnabel ◽  
Xiaojuan Liu ◽  
Matthias Kunz ◽  
Kathryn E. Barry ◽  
Franca J. Bongers ◽  
...  

AbstractExtreme climatic events threaten forests and their climate mitigation potential globally. Understanding the drivers promoting ecosystems stability is therefore considered crucial to mitigate adverse climate change effects on forests. Here, we use structural equation models to explain how tree species richness, asynchronous species dynamics and diversity in hydraulic traits affect the stability of forest productivity along an experimentally manipulated biodiversity gradient ranging from 1 to 24 tree species. Tree species richness improved stability by increasing species asynchrony. That is at higher species richness, inter-annual variation in productivity among tree species buffered the community against stress-related productivity declines. This effect was mediated by the diversity of species’ hydraulic traits in relation to drought tolerance and stomatal control, but not the community-weighted means of these traits. Our results demonstrate important mechanisms by which tree species richness stabilizes forest productivity, thus emphasizing the importance of hydraulically diverse, mixed-species forests to adapt to climate change.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6781
Author(s):  
Youngsang Kwon ◽  
Taesoo Lee ◽  
Alison Lang ◽  
Dorian Burnette

The southeastern region of the United States exhibits an unusual trend of decreasing tree species richness (TSR) from higher to lower latitudes over the Florida peninsula. This trend contradicts the widely marked latitudinal diversity gradient where species richness is highest in tropical zones and decreases towards extratropical regions. This study aims to assess the environmental factors that prompt this atypical inverse latitudinal gradient seen in TSR using the USDA Forest Service’s Forest Inventory and Analysis (FIA) database. Fifteen variables under four categories of forested area, groundwater, soil properties, and climate groups were examined to model TSR in the region. Generalized linear models (GLMs) with Poisson distributions first assessed individual variables to test explanatory power then the LASSO regularization method was utilized to extract two subsets of the most influential variables to predict TSR. Forest area and four climate variables (mean annual temperature, precipitation seasonality, mean temperature of coldest quarter, and mean precipitation of driest quarter) were the top five variables during the initial GLM assessment implying their potential individual influence in regulating TSR. Two subsets of LASSO models contained seven and three predictor variables, respectively. Frist subset includes seven predictors, presented in highest to low standardized coefficient, mean temperature of coldest quarter, forested area, precipitation seasonality, mean precipitation of driest quarter, water table depth, spodosol, and available water storage. The other subset further excluded four lowest influential variables from the first set, leaving the top three variables from the first subset. The first subset of the LASSO model predicted TSR with 63.4% explained deviance while the second subset reproduced 60.2% of deviance explained. With only three variables used, the second model outperformed the first model evaluated by the AIC value. We conclude that forest patch area, mean temperature of coldest quarter, and precipitation seasonality are the highly influential variables of TSR among environmental factors in the southeastern region of U.S., but evolutionary or historic cause should be further incorporated to fully understand tree species diversity pattern in this region.


2019 ◽  
Vol 29 (3) ◽  
pp. 799-815
Author(s):  
Victor P. Zwiener ◽  
André A. Padial ◽  
Márcia C. M. Marques

2018 ◽  
Vol 9 (2) ◽  
pp. 322-330
Author(s):  
Rong Sun ◽  
Xiaojie Luo ◽  
Xiangyu Meng ◽  
Yan Wang

Abstract The streams in a watershed form a hierarchical network system. From the perspective of the river continuum, this classification system is the result of gradual increase in traffic. This study analyzed the riparian species richness, diversity and environmental factors along a six-order hierarchical mountain river in the Donghe watershed, China. A total of 34 sampling sites were sampled to study the spatial distribution of riparian plants among different stream orders. The results showed: Environmental factors among stream orders had significant differences. Among stream order, species richness showed remarkable differences. The species richness rose firstly and dropped afterwards except for tree species richness; tree species richness decreased while stream order increased. The same is true for shrub quadrat species richness. Shannon-Wiener diversity, Simpson dominance and Pielou uniformity showed significant difference among stream orders; Shannon-Wiener diversity rose firstly then dropped afterwards. For integrated environmental factors and community characteristics, we found the changes of stream orders had a significant impact on riparian habitats and riparian vegetation. Further analysis showed that riparian vegetation experienced different types and degrees of disturbance in different stream orders. This meant that a hierarchical management strategy should be applied to riparian vegetation management.


2021 ◽  
Vol 11 (1) ◽  
pp. 73-83
Author(s):  
MAHEDI HASAN LIMON ◽  
SAIDA HOSSAIN ARA ◽  
MOHAMMAD GOLAM KIBRIA

Natural regeneration is an indicator of a healthy forest, hence, understanding the influence of site factors on natural regeneration is a significant concern for ecologists. This work aimed to assess the impact of site factors on natural tree regeneration at Khadimnagar National Park (KNP). Biotic factors (tree density, tree species richness, and basal area), physical factors (elevation, canopy openness), and soil properties (bulk density, moisture content, soil pH, organic matter, sand, silt, and clay) data were investigated from 71 sample plots to examine their effects on natural regeneration density and richness in KNP. Stepwise multiple linear regression analysis was done to predict both regeneration density and regeneration richness. The results showed that soil pH (p<0.001), canopy openness (p<0.001), tree species richness (p<0.01), and bulk density (p<0.01) had a significant effect on regeneration density, explaining 42% of the total variation. Regeneration richness was driven by four factors: tree species richness (p<0.01), soil pH (p<0.001), elevation (p<0.01), and canopy openness (p<0.01) with a model that explained 60% of the total variation. This study observed that soil pH, tree species richness, and canopy openness are the main controlling factors that influenced both the density and richness of regenerating species in KNP. Therefore, these findings have implications for natural resource management, especially in selecting suitable silvicultural systems in a tropical forest under protected area management where enhanced tree cover and conservation of biodiversity are needed.


Ecology ◽  
2019 ◽  
Vol 100 (4) ◽  
pp. e02653 ◽  
Author(s):  
Lionel R. Hertzog ◽  
Roschong Boonyarittichaikij ◽  
Daan Dekeukeleire ◽  
Stefanie R. E. de Groote ◽  
Irene M. van Schrojenstein Lantman ◽  
...  

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