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Climate Change Impact on Plant Ecology
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Climate Change Impact on Plant Ecology

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 13187

Special Issue Editors

Dr. Marcello Vitale

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Guest Editor
Department of Environmental Biology, Sapienza University of Rome (UNIROMA1), Piazzale Aldo Moro, 5, I-00185 Rome, Italy
Interests: forest ecology; forest growth and carbon-water balances; stress physiology; adaptation–mitigation of forests to global change and air pollution; process-based and statistical modeling; litter decomposition
Special Issues, Collections and Topics in MDPI journals
Dr. Alessio Collalti

E-Mail Website
Guest Editor
Forest Modelling Lab., Institute for Agriculture and Forestry Systems in the Mediterranean, National Research Council of Italy (CNR-ISAFOM), Via Madonna Alta 128, 06128 Perugia, Italy
Interests: forest modeling; climate change; climate change impacts; forest management scenario; carbon cycle; nitrogen cycle; climate change adaptation; climate change mitigation; forest ecology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Global climate varies naturally over time scales from decades to thousands of years and longer. These natural variations can originate from internal fluctuations that exchange energy, water, and carbon among the atmosphere, oceans, and land, and from external influences, including variations in the energy received from the sun and the effects of volcanic eruptions. Human activities can also influence climate by altering atmospheric CO2 concentrations, and other greenhouse gases including aerosols and the reflectivity of Earth’s surface by changing land cover. Climate change is projected to affect ecosystems and valuable services at multiple scales. Factors at different scales could be interacting, and separately assessing these impacts may lead to mismatches of potential management interventions with processes that affect ecosystem services. Viewing forests as complex adaptive systems can provide insights into ecosystem processes and hierarchical interactions. The main purpose of this Special Issue is to define methodological approaches aimed at evaluating the impacts of climate change on the structural and functional processes of forests throughout the cross-scale interactions. A special focus is on elaboration of conceptual models and predictive algorithms on the effects of climate change on functional processes—such as carbon assimilation and plant respiration—and keeping of ecosystem services and biodiversity.

Prof. Dr. Marcello Vitale 
Dr. Alessio Collalti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Climate is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climatic scenarios
  • greenhouse gases
  • modeling
  • primary production
  • system complexity

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Published Papers (4 papers)

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Editorial

Jump to: Research

3 pages, 181 KiB  
Editorial
Preface: Climate Change Impact on Plant Ecology
by Marcello Vitale and Alessio Collalti
Climate 2020, 8(5), 59; https://doi.org/10.3390/cli8050059 - 25 Apr 2020
Cited by 1 | Viewed by 3247
Abstract
Climate change likely represents the major modifying agents of functional and structural processes in terrestrial and marine ecosystems [...] Full article
(This article belongs to the Special Issue Climate Change Impact on Plant Ecology)

Research

Jump to: Editorial

19 pages, 1253 KiB  
Article
Data-Driven Analysis of Forest–Climate Interactions in the Conterminous United States
by Olga Rumyantseva and Nikolay Strigul
Climate 2021, 9(7), 108; https://doi.org/10.3390/cli9070108 - 30 Jun 2021
Cited by 1 | Viewed by 2426
Abstract
A predictive understanding of interactions between vegetation and climate has been a grand challenge in terrestrial ecology for over 200 years. Developed in recent decades, continental-scale monitoring of climate and forest dynamics enables quantitative examination of vegetation–climate relationships through a data-driven paradigm. Here, [...] Read more.
A predictive understanding of interactions between vegetation and climate has been a grand challenge in terrestrial ecology for over 200 years. Developed in recent decades, continental-scale monitoring of climate and forest dynamics enables quantitative examination of vegetation–climate relationships through a data-driven paradigm. Here, we apply a data-intensive approach to investigate forest–climate interactions across the conterminous USA. We apply multivariate statistical methods (stepwise regression, principal component analysis) including machine learning to infer significant climatic drivers of standing forest basal area. We focus our analysis on the ecoregional scale. For most ecoregions analyzed, both stepwise regression and random forests indicate that factors related to precipitation are the most significant predictors of forest basal area. In almost half of US ecoregions, precipitation of the coldest quarter is the single most important driver of basal area. The demonstrated data-driven approach may be used to inform forest-climate envelope modeling and the forecasting of large-scale forest dynamics under climate change scenarios. These results have important implications for climate, biodiversity, industrial forestry, and indigenous communities in a changing world. Full article
(This article belongs to the Special Issue Climate Change Impact on Plant Ecology)
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14 pages, 2578 KiB  
Article
Air Pollution and Climate Drive Annual Growth in Ponderosa Pine Trees in Southern California
by Hillary S. Jenkins
Climate 2021, 9(5), 82; https://doi.org/10.3390/cli9050082 - 13 May 2021
Cited by 1 | Viewed by 2939
Abstract
The ponderosa pine (Pinus ponderosa, Douglas ex C. Lawson) is a climate-sensitive tree species dominant in the mixed conifer stands of the San Bernardino Mountains of California. However, the close proximity to the city of Los Angeles has resulted in extremely [...] Read more.
The ponderosa pine (Pinus ponderosa, Douglas ex C. Lawson) is a climate-sensitive tree species dominant in the mixed conifer stands of the San Bernardino Mountains of California. However, the close proximity to the city of Los Angeles has resulted in extremely high levels of air pollution. Nitrogen (N) deposition, resulting from nitrous oxides emitted from incomplete combustion of fossil fuels, has been recorded in this region since the 1980s. The impact of this N deposition on ponderosa pine growth is complex and often obscured by other stressors including climate, bark beetle attack, and tropospheric ozone pollution. Here I use a 160-year-long (1855–2015) ponderosa pine tree ring chronology to examine the annual response of tree growth to both N deposition and climate in this region. The chronology is generated from 34 tree cores taken near Crestline, CA. A stepwise multiple regression between the tree ring chronology and various climate and air pollution stressors indicates that drought conditions at the end of the rainy season (March) and NO2 pollution during the water year (pOct-Sep) exhibit primary controls on growth (r2-adj = 0.65, p < 0.001). The direct correlation between NO2 and tree growth suggests that N deposition has a positive impact on ponderosa pine bole growth in this region. However, it is important to note that ozone, a known stressor to ponderosa pine trees, and NO2 are also highly correlated (r = 0.84, p < 0.05). Chronic exposure to both ozone and nitrogen dioxide may, therefore, have unexpected impacts on tree sensitivity to climate and other stressors in a warming world. Full article
(This article belongs to the Special Issue Climate Change Impact on Plant Ecology)
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18 pages, 2554 KiB  
Article
Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka
by Champika S. Kariyawasam, Lalit Kumar, Benjamin Kipkemboi Kogo and Sujith S. Ratnayake
Climate 2021, 9(2), 31; https://doi.org/10.3390/cli9020031 - 9 Feb 2021
Cited by 8 | Viewed by 3192
Abstract
Climate variability can influence the dynamics of aquatic invasive alien plants (AIAPs) that exert tremendous pressure on aquatic systems, leading to loss of biodiversity, agricultural wealth, and ecosystem services. However, the magnitude of these impacts remains poorly known. The current study aims to [...] Read more.
Climate variability can influence the dynamics of aquatic invasive alien plants (AIAPs) that exert tremendous pressure on aquatic systems, leading to loss of biodiversity, agricultural wealth, and ecosystem services. However, the magnitude of these impacts remains poorly known. The current study aims to analyse the long-term changes in the spatio-temporal distribution of AIAPs under the influence of climate variability in a heavily infested tank cascade system (TCS) in Sri Lanka. The changes in coverage of various features in the TCS were analysed using the supervised maximum likelihood classification of ten Landsat images over a 27-year period, from 1992 to 2019 using ENVI remote sensing software. The non-parametric Mann–Kendall trend test and Sen’s slope estimate were used to analyse the trend of annual rainfall and temperature. We observed a positive trend of temperature that was statistically significant (p value < 0.05) and a positive trend of rainfall that was not statistically significant (p values > 0.05) over the time period. Our results showed fluctuations in the distribution of AIAPs in the short term; however, the coverage of AIAPs showed an increasing trend in the study area over the longer term. Thus, this study suggests that the AIAPs are likely to increase under climate variability in the study area. Full article
(This article belongs to the Special Issue Climate Change Impact on Plant Ecology)
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