Gradient analysis, the next generation: towards more plant-relevant explanatory variables

2005 ◽  
Vol 35 (7) ◽  
pp. 1744-1753 ◽  
Author(s):  
Todd R Lookingbill ◽  
Dean L Urban
Keyword(s):  
Gradient Analysis ◽  
Species Turnover ◽  
Global Climate ◽  
Explanatory Power ◽  
Elevation Gradient ◽  
Forest Community ◽  
Climate Change Scenarios ◽  
Data Set ◽  
Elevation Gradients ◽  
Explanatory Variables

The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. This model is unsatisfying in that elevation is not directly relevant to plants and the ubiquitous "elevation gradient" is composed of multiple intertwined environmental factors. We offer an approach to landscape-scale vegetation analysis that disentangles the elevation gradient into its constituent parts through focused field sampling and statistical analysis. We illustrate the approach for an old-growth watershed in the Oregon Western Cascades. Our initial model of this system supports the common observation that forest community types are highly associated with specific elevation bands. By replacing elevation and other crude environmental proxy variables with estimates of more direct and resource gradients (radiation, temperature, and soil moisture), we create a vegetative model with stronger explanatory power than the proxy model in both cross-validation analysis and validation using an independent data set. The resulting model is also more biologically interpretable, which provides more meaningful insight into potential forest response to environmental change (e.g., global climate change scenarios). Acquiring a better mechanistic understanding of the relationship between plant communities and environmental predictor variables presents the next great challenge to community ecologists conducting gradient studies at landscape scales.

scholarly journals Species richness and β-diversity patterns of macrolichens along elevation gradients across the Himalayan Arc

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Subzar Ahmad Nanda ◽  
Manzoor-ul Haq ◽  
S. P. Singh ◽  
Zafar A. Reshi ◽  
Ranbeer S. Rawal ◽  
...  
Keyword(s):  
Species Richness ◽  
Species Turnover ◽  
Elevation Gradient ◽  
Conservation Strategies ◽  
Elevational Gradients ◽  
Elevation Gradients ◽  
Diversity Patterns ◽  
Β Diversity ◽  
Shaped Pattern ◽  
The Himalaya

AbstractUnderstanding the species richness and β-diversity patterns along elevation gradients can aid in formulating effective conservation strategies particularly in areas where local anthropogenic stresses and climate change are quite significant as in the Himalaya. Thus, we studied macrolichen richness and β-diversity along elevational gradients at three sites, namely Kashmir (2200 to 3800 m a.m.s.l), Uttarakhand (2000–3700 m a.m.s.l) and Sikkim (1700 to 4000 m a.m.s.l) which cover much of the Indian Himalayan Arc. In all, 245 macrolichen species belonging to 77 genera and 26 families were collected from the three sites. Only 11 species, 20 genera and 11 families were common among the three transects. Despite the differences in species composition, the dominant functional groups in the three sites were the same: foliose, fruticose and corticolous forms. The hump-shaped elevation pattern in species richness was exhibited by most of the lichen groups, though an inverse hump-shaped pattern was also observed in certain cases. β-diversity (βsor) based on all pairs of comparisons along an elevation gradient varied from 0.48 to 0.58 in Kashmir, 0.03 to 0.63 in Uttarakhand and 0.46 to 0.77 in Sikkim. The contribution of turnover to β-diversity was more than nestedness at all the three transects. Along elevation β-diversity and its components of turnover and nestedness varied significantly with elevation. While species turnover increased significantly along the elevation in all the three transects, nestedness decreased significantly in Kashmir and Sikkim transects but increased significantly in the Uttarakhand transect. Except for the Kashmir Himalayan elevation transect, stepwise β-diversity and its components of turnover and nestedness did not vary significantly with elevation. The present study, the first of its kind in the Himalayan region, clearly brings out that macrolichen species richness, β-diversity, and its components of turnover and nestedness vary along the elevation gradients across the Himalayan Arc. It also highlights that contribution of turnover to β-diversity is higher in comparison to nestedness at all the three transects. The variations in species richness and diversity along elevation gradients underpin the importance of considering elevational gradients in planning conservation strategies.

scholarly journals Turnover of Lecanoroid Mycobionts and Their Trebouxia Photobionts Along an Elevation Gradient in Bolivia Highlights the Role of Environment in Structuring the Lichen Symbiosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Ian D. Medeiros ◽  
Edyta Mazur ◽  
Jolanta Miadlikowska ◽  
Adam Flakus ◽  
Pamela Rodriguez-Flakus ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Species Turnover ◽  
Elevation Gradient ◽  
Single Species ◽  
High Elevation ◽  
Regional Patterns ◽  
Elevation Gradients ◽  
Clade C ◽  
Community Shifts ◽  
Molecular Dataset

Shifts in climate along elevation gradients structure mycobiont–photobiont associations in lichens. We obtained mycobiont (lecanoroid Lecanoraceae) and photobiont (Trebouxia alga) DNA sequences from 89 lichen thalli collected in Bolivia from a ca. 4,700 m elevation gradient encompassing diverse natural communities and environmental conditions. The molecular dataset included six mycobiont loci (ITS, nrLSU, mtSSU, RPB1, RPB2, and MCM7) and two photobiont loci (ITS, rbcL); we designed new primers to amplify Lecanoraceae RPB1 and RPB2 with a nested PCR approach. Mycobionts belonged to Lecanora s.lat., Bryonora, Myriolecis, Protoparmeliopsis, the “Lecanora” polytropa group, and the “L.” saligna group. All of these clades except for Lecanora s.lat. occurred only at high elevation. No single species of Lecanoraceae was present along the entire elevation gradient, and individual clades were restricted to a subset of the gradient. Most Lecanoraceae samples represent species which have not previously been sequenced. Trebouxia clade C, which has not previously been recorded in association with species of Lecanoraceae, predominates at low- to mid-elevation sites. Photobionts from Trebouxia clade I occur at the upper extent of mid-elevation forest and at some open, high-elevation sites, while Trebouxia clades A and S dominate open habitats at high elevation. We did not find Trebouxia clade D. Several putative new species were found in Trebouxia clades A, C, and I. These included one putative species in clade A associated with Myriolecis species growing on limestone at high elevation and a novel lineage sister to the rest of clade C associated with Lecanora on bark in low-elevation grassland. Three different kinds of photobiont switching were observed, with certain mycobiont species associating with Trebouxia from different major clades, species within a major clade, or haplotypes within a species. Lecanoraceae mycobionts and Trebouxia photobionts exhibit species turnover along the elevation gradient, but with each partner having a different elevation threshold at which the community shifts completely. A phylogenetically defined sampling of a single diverse family of lichen-forming fungi may be sufficient to document regional patterns of Trebouxia diversity and distribution.

scholarly journals Changes in the stoichiometry of Castanopsis fargesii along an elevation gradient in a Chinese subtropical forest

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11553
Author(s):  
Danping Liu ◽  
Dexiang Zheng ◽  
Yaoyao Xu ◽  
Yifei Chen ◽  
Hesong Wang ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Ecological Stoichiometry ◽  
Forest Ecosystems ◽  
Global Climate ◽  
Elevation Gradient ◽  
Biogeochemical Cycle ◽  
Elevation Gradients ◽  
Castanopsis Fargesii ◽  
Leaf P ◽  
Leaf N

Elevation is important for determining the nutrient biogeochemical cycle in forest ecosystems. Changes in the ecological stoichiometry of nutrients along an elevation gradient can be used to predict how an element cycle responds in the midst of global climate change. We investigated changes in concentrations of and relationships between nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) in the leaves and roots of the dominant tree species, Castanopsis fargesii, along an elevation gradient (from 500 to 1,000 m above mean sea level) in a subtropical natural forest in China. We analyzed correlations between C. fargesii’s above-ground biomass and stoichiometry with environmental factors. We also analyzed the soil and plant stoichiometry of this C. fargesii population. Our results showed that leaf N decreased while leaf K and Ca increased at higher elevations. Meanwhile, leaf P showed no relationship with elevation. The leaf N:P indicated that C. fargesii was limited by N. Elevation gradients contributed 46.40% of the total variance of ecological stoichiometry when assessing environmental factors. Our research may provide a theoretical basis for the biogeochemical cycle along with better forest management and fertilization for this C. fargesii population.

Metacommunity structure of tropical forest along an elevation gradient in Puerto Rico

2008 ◽  
Vol 24 (05) ◽  
pp. 525-534 ◽  
Author(s):  
John A. Barone ◽  
John Thomlinson ◽  
Pedro Anglada Cordero ◽  
Jess K. Zimmerman
Keyword(s):  
Puerto Rico ◽  
Tropical Forests ◽  
Environmental Gradients ◽  
Species Turnover ◽  
Elevation Gradient ◽  
Community Change ◽  
Free Standing ◽  
Elevation Gradients ◽  
Species Ranges ◽  
Metacommunity Structure

Abstract:The development of metacommunity theory, which suggests that the diversity and composition of communities is influenced by interactions with other communities, has produced new tools for evaluating patterns of community change along environmental gradients. These techniques were used to examine how plant communities changed along elevation gradients in montane tropical forests. Two transects of 0.1-ha vegetation plots were established every 50 m in elevation in the mountains of eastern Puerto Rico. The transects ranged from 300 m to 1000 m asl and 400 m to 900 m. In each plot, all free-standing woody stems greater than 1 cm in diameter at 130 cm in height were marked, measured and identified. Additional data on three similar transects were taken from the literature. The upper or lower boundaries of species ranges were significantly clumped along all five transects. Coherence, a measure of the number of gaps in species distributions, was also significant across all transects, and three transects showed significant, albeit low, nestedness. Four sites had significant species turnover. These results suggest that metacommunity techniques can be useful in searching for patterns of community change present in montane tropical forests.

scholarly journals Silicon Effects on the Root System of Diverse Crop Species Using Root Phenotyping Technology

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 885
Author(s):  
Pooja Tripathi ◽  
Sangita Subedi ◽  
Abdul Latif Khan ◽  
Yong-Suk Chung ◽  
Yoonha Kim
Keyword(s):  
Root System ◽  
Root Morphology ◽  
Morphological Traits ◽  
Crop Production ◽  
Spatial Configuration ◽  
Global Climate ◽  
Learning Technologies ◽  
Climate Change Scenarios ◽  
Crop Species ◽  
Wide Range

Roots play an essential function in the plant life cycle, as they utilize water and essential nutrients to promote growth and plant productivity. In particular, root morphology characteristics (such as length, diameter, hairs, and lateral growth) and the architecture of the root system (spatial configuration in soil, shape, and structure) are the key elements that ensure growth and a fine-tuned response to stressful conditions. Silicon (Si) is a ubiquitous element in soil, and it can affect a wide range of physiological processes occurring in the rhizosphere of various crop species. Studies have shown that Si significantly and positively enhances root morphological traits, including root length in rice, soybean, barley, sorghum, mustard, alfalfa, ginseng, and wheat. The analysis of these morphological traits using conventional methods is particularly challenging. Currently, image analysis methods based on advanced machine learning technologies allowed researchers to screen numerous samples at the same time considering multiple features, and to investigate root functions after the application of Si. These methods include root scanning, endoscopy, two-dimensional, and three-dimensional imaging, which can measure Si uptake, translocation and root morphological traits. Small variations in root morphology and architecture can reveal different positive impacts of Si on the root system of crops, with or without exposure to stressful environmental conditions. This review comprehensively illustrates the influences of Si on root morphology and root architecture in various crop species. Furthermore, it includes recommendations in regard to advanced methods and strategies to be employed to maintain sustainable plant growth rates and crop production in the currently predicted global climate change scenarios.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Regulation of Seed Dormancy and Germination Mechanisms in a Changing Environment

2021 ◽  
Vol 22 (3) ◽  
pp. 1357
Author(s):  
Ewelina A. Klupczyńska ◽  
Tomasz A. Pawłowski
Keyword(s):  
Climate Change ◽  
Seed Germination ◽  
Seed Dormancy ◽  
Environmental Conditions ◽  
Global Climate ◽  
Plant Evolution ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Adaptation Mechanism ◽  
Seed Dormancy And Germination

Environmental conditions are the basis of plant reproduction and are the critical factors controlling seed dormancy and germination. Global climate change is currently affecting environmental conditions and changing the reproduction of plants from seeds. Disturbances in germination will cause disturbances in the diversity of plant communities. Models developed for climate change scenarios show that some species will face a significant decrease in suitable habitat area. Dormancy is an adaptive mechanism that affects the probability of survival of a species. The ability of seeds of many plant species to survive until dormancy recedes and meet the requirements for germination is an adaptive strategy that can act as a buffer against the negative effects of environmental heterogeneity. The influence of temperature and humidity on seed dormancy status underlines the need to understand how changing environmental conditions will affect seed germination patterns. Knowledge of these processes is important for understanding plant evolution and adaptation to changes in the habitat. The network of genes controlling seed dormancy under the influence of environmental conditions is not fully characterized. Integrating research techniques from different disciplines of biology could aid understanding of the mechanisms of the processes controlling seed germination. Transcriptomics, proteomics, epigenetics, and other fields provide researchers with new opportunities to understand the many processes of plant life. This paper focuses on presenting the adaptation mechanism of seed dormancy and germination to the various environments, with emphasis on their prospective roles in adaptation to the changing climate.

scholarly journals Multi-Year NDVI Values as Indicator of the Relationship between Spatiotemporal Vegetation Dynamics and Environmental Factors in the Qaidam Basin, China

2021 ◽  
Vol 13 (7) ◽  
pp. 1240
Author(s):  
Junpeng Lou ◽  
Guoyin Xu ◽  
Zhongjing Wang ◽  
Zhigang Yang ◽  
Sanchuan Ni
Keyword(s):  
Environmental Factors ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Qaidam Basin ◽  
Elevation Gradient ◽  
Practical Significance ◽  
Elevation Gradients ◽  
Relative Contribution ◽  
Significant Difference ◽  
Different Altitudes

The Qaidam Basin is a unique and complex ecosystem, wherein elevation gradients lead to high spatial heterogeneity in vegetation dynamics and responses to environmental factors. Based on the remote sensing data of Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS), we analyzed the spatiotemporal variations of vegetation dynamics and responses to precipitation, accumulative temperature (AT) and soil moisture (SM) in the Qaidam Basin from 2001 to 2016. Moreover, the contribution of those factors to vegetation dynamics at different altitudes was analyzed via an artificial neural network (ANN) model. The results indicated that the Normalized Difference Vegetation Index (NDVI) values in the growing season showed an overall upward trend, with an increased rate of 0.001/year. The values of NDVI in low-altitude areas were higher than that in high-altitude areas, and the peak values of NDVI appeared along the elevation gradient at 4400–4600 m. Thanks to the use of ANN, we were able to detect the relative contribution of various environmental factors; the relative contribution rate of AT to the NDVI dynamic was the most significant (35.17%) in the low-elevation region (< 2900 m). In the mid-elevation area (2900–3900 m), precipitation contributed 44.76% of the NDVI dynamics. When the altitude was higher than 3900 m, the relative contribution rates of AT (39.50%) and SM (38.53%) had no significant difference but were significantly higher than that of precipitation (21.97%). The results highlight that the different environmental factors have various contributions to vegetation dynamics at different altitudes, which has important theoretical and practical significance for regulating ecological processes.

scholarly journals Improving prediction and assessment of global fires using multilayer neural networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaideep Joshi ◽  
Raman Sukumar
Keyword(s):  
Global Climate ◽  
Grid Cell ◽  
Temporal Correlation ◽  
Environmental Drivers ◽  
Future Climate Change ◽  
Burned Area ◽  
Climate Change Scenarios ◽  
Data Driven Approach ◽  
Climate Interactions ◽  
Fire Climate Interactions

AbstractFires determine vegetation patterns, impact human societies, and are a part of complex feedbacks into the global climate system. Empirical and process-based models differ in their scale and mechanistic assumptions, giving divergent predictions of fire drivers and extent. Although humans have historically used and managed fires, the current role of anthropogenic drivers of fires remains less quantified. Whereas patterns in fire–climate interactions are consistent across the globe, fire–human–vegetation relationships vary strongly by region. Taking a data-driven approach, we use an artificial neural network to learn region-specific relationships between fire and its socio-environmental drivers across the globe. As a result, our models achieve higher predictability as compared to many state-of-the-art fire models, with global spatial correlation of 0.92, monthly temporal correlation of 0.76, interannual correlation of 0.69, and grid-cell level correlation of 0.60, between predicted and observed burned area. Given the current socio-anthropogenic conditions, Equatorial Asia, southern Africa, and Australia show a strong sensitivity of burned area to temperature whereas northern Africa shows a strong negative sensitivity. Overall, forests and shrublands show a stronger sensitivity of burned area to temperature compared to savannas, potentially weakening their status as carbon sinks under future climate-change scenarios.

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