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Kirschbaum MUF, Cowie AL, Peñuelas J, Smith P, Conant RT, Sage RF, Brandão M, Cotrufo MF, Luo Y, Way DA, Robinson SA. Is tree planting an effective strategy for climate change mitigation? THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 909:168479. [PMID: 37951250 DOI: 10.1016/j.scitotenv.2023.168479] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 10/18/2023] [Accepted: 11/08/2023] [Indexed: 11/13/2023]
Abstract
The world's forests store large amounts of carbon (C), and growing forests can reduce atmospheric CO2 by storing C in their biomass. This has provided the impetus for world-wide tree planting initiatives to offset fossil-fuel emissions. However, forests interact with their environment in complex and multifaceted ways that must be considered for a balanced assessment of the value of planting trees. First, one needs to consider the potential reversibility of C sequestration in trees through either harvesting or tree death from natural factors. If carbon storage is only temporary, future temperatures will actually be higher than without tree plantings, but cumulative warming will be reduced, contributing both positively and negatively to future climate-change impacts. Alternatively, forests could be used for bioenergy or wood products to replace fossil-fuel use which would obviate the need to consider the possible reversibility of any benefits. Forests also affect the Earth's energy balance through either absorbing or reflecting incoming solar radiation. As forests generally absorb more incoming radiation than bare ground or grasslands, this constitutes an important warming effect that substantially reduces the benefit of C storage, especially in snow-covered regions. Forests also affect other local ecosystem services, such as conserving biodiversity, modifying water and nutrient cycles, and preventing erosion that could be either beneficial or harmful depending on specific circumstances. Considering all these factors, tree plantings may be beneficial or detrimental for mitigating climate-change impacts, but the range of possibilities makes generalisations difficult. Their net benefit depends on many factors that differ between specific circumstances. One can, therefore, neither uncritically endorse tree planting everywhere, nor condemn it as counter-productive. Our aim is to provide key information to enable appropriate assessments to be made under specific circumstances. We conclude our discussion by providing a step-by-step guide for assessing the merit of tree plantings under specific circumstances.
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Affiliation(s)
- Miko U F Kirschbaum
- Manaaki Whenua - Landcare Research, Private Bag 11052, Palmerston North, New Zealand.
| | - Annette L Cowie
- NSW Department of Primary Industries/University of New England, Armidale, Australia
| | - Josep Peñuelas
- CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Barcelona, Catalonia, Spain; CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, Spain
| | - Pete Smith
- Institute of Biological and Environmental Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK
| | - Richard T Conant
- Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80523, USA
| | - Rowan F Sage
- Department of Ecology and Evolutionary Biology, 25 Willcocks Street, Toronto, Ontario, M5S 3B2, Canada
| | - Miguel Brandão
- KTH Royal Institute of Technology, Department of Sustainable Development, Environmental Science and Engineering, Stockholm 100-44, Sweden
| | - M Francesca Cotrufo
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA
| | - Yiqi Luo
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Danielle A Way
- Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia; Department of Biology, The University of Western Ontario, London, Ontario, Canada; Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
| | - Sharon A Robinson
- Securing Antarctica's Environmental Future & Centre for Sustainable Ecosystem Solutions, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia
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2
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Gayathiri E, Prakash P, Kumaravel P, Jayaprakash J, Ragunathan MG, Sankar S, Pandiaraj S, Thirumalaivasan N, Thiruvengadam M, Govindasamy R. Computational approaches for modeling and structural design of biological systems: A comprehensive review. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 185:17-32. [PMID: 37821048 DOI: 10.1016/j.pbiomolbio.2023.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 08/14/2023] [Accepted: 08/27/2023] [Indexed: 10/13/2023]
Abstract
The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.
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Affiliation(s)
- Ekambaram Gayathiri
- Department of Plant Biology and Plant Biotechnology, Guru Nanak College (Autonomous), Chennai, 42, Tamil Nadu, India
| | - Palanisamy Prakash
- Department of Botany, Periyar University, Periyar Palkalai Nagar, Salem, 636011, Tamil Nadu, India
| | - Priya Kumaravel
- Department of Biotechnology, St. Joseph College (Arts & Science), Kovur, Chennai, Tamil Nadu, India
| | - Jayanthi Jayaprakash
- Department of Advanced Zoology and Biotechnology, Guru Nanak College, Chennai, Tamil Nadu, India
| | | | - Sharmila Sankar
- Department of Advanced Zoology and Biotechnology, Guru Nanak College, Chennai, Tamil Nadu, India
| | - Saravanan Pandiaraj
- Department of Self-Development Skills, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
| | - Natesan Thirumalaivasan
- Department of Periodontics, Saveetha Dental College, and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMTAS), Chennai, 600077, Tamil Nadu, India
| | - Muthu Thiruvengadam
- Department of Applied Bioscience, College of Life and Environmental Sciences, Konkuk University, Seoul, 05029, South Korea
| | - Rajakumar Govindasamy
- Department of Orthodontics, Saveetha Dental College and Hospitals, Saveetha University, Chennai, India.
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3
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Yang Y, Cao T. Measurement of carbon effect in land consolidation projects and evaluation of low-carbon promotion paths: a case study of Wudi County, Shandong Province, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:113068-113087. [PMID: 37848794 DOI: 10.1007/s11356-023-30208-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 09/27/2023] [Indexed: 10/19/2023]
Abstract
Against the backdrop of China's "double carbon" objective, the exploration of low-carbon land consolidation has become a prominent area of focus for enhancing the development of ecological civilization. In this study, three typical projects at different time points (2016, 2019, and 2022) in Wudi County were selected to measure the carbon effect of land consolidation from four perspectives: artificial and industrial materials, mechanical shift consumption, land use structure, and farmland ecosystem. Based on the calculation of carbon effect of land consolidation by using carbon emission coefficient method, the changes of land use structure and carbon storage of farmland ecosystem before and after land consolidation were corrected by using GIS tools and net ecosystem productivity (NEP) model based on remote sensing technology, and the carbon emission intensity of each land consolidation project was finally obtained. The study summarized the influencing factors of carbon emissions through the above analysis and uses the fuzzy interpretation structure (FISM) model to provide the hierarchy of influencing factors of carbon emissions, thus proposing a low-carbon promotion path for land consolidation. The findings of this study can serve as a useful reference for low-carbon land consolidation efforts. The results showed that (1) the first, second, and third projects emitted 6140.06 t, 1243.78 t, and 17,604.62 t of carbon, respectively. Among them, the largest contributors to these emissions were labor and industrial materials, followed by mechanical shift; land use structure and farmland ecosystem were the main sources of carbon sinks and have a positive impact on the carbon cycle. (2) The carbon emission intensity of project one, project two, and project three after standardization is 0.26, 0.49, and 0.25, respectively, which are all at a high level. (3) According to the FISM model categorized 15 low-carbon upgrading paths, it was recommended that the government take a leading role in Wudi County by developing a scientific and rational construction plan. Additionally, efforts were made to actively protect farmland and forest land from destruction, reduce energy and material consumption, increase carbon storage in the farmland ecosystem, and promote low carbonization of land consolidation to the fullest extent possible.
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Affiliation(s)
- Yijia Yang
- Institute of Management Engineering, Qingdao University of Technology, Qingdao, 266525, China
| | - Tianyu Cao
- Institute of Management Engineering, Qingdao University of Technology, Qingdao, 266525, China.
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4
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Forster EJ, Healey JR, Newman G, Styles D. Circular wood use can accelerate global decarbonisation but requires cross-sectoral coordination. Nat Commun 2023; 14:6766. [PMID: 37880217 PMCID: PMC10600095 DOI: 10.1038/s41467-023-42499-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 10/12/2023] [Indexed: 10/27/2023] Open
Abstract
Predominantly linear use of wood curtails the potential climate-change mitigation contribution of forestry value-chains. Using lifecycle assessment, we show that more cascading and especially circular uses of wood can provide immediate and sustained mitigation by reducing demand for virgin wood, which increases forest carbon sequestration and storage, and benefits from substitution for fossil-fuel derived products, reducing net greenhouse gas emissions. By United Kingdom example, the circular approach of recycling medium-density fibreboard delivers 75% more cumulative climate-change mitigation by 2050, compared with business-as-usual. Early mitigation achieved by circular and cascading wood use complements lagged mitigation achieved by afforestation; and in combination these measures could cumulatively mitigate 258.8 million tonnes CO2e by 2050. Despite the clear benefits of implementing circular economy principles, we identify many functional barriers impeding the structural reorganisation needed for such complex system change, and propose enablers to transform the forestry value-chain into an effective societal change system and lead to coherent action.
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Affiliation(s)
- Eilidh J Forster
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK.
| | - John R Healey
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Gary Newman
- Woodknowledge Wales Ltd., Ffarm Moelyci, Felin Hen Road, Tregarth, Gwynedd, LL57 4BB, UK
| | - David Styles
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
- School of Biological & Chemical Sciences and Ryan Institute, University of Galway, Galway, H91 TK33, Ireland
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5
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Müller DP, Szemkus N, Hiete M. Carbon balance of plywood from a social reforestation program in Indonesia. Sci Rep 2023; 13:13552. [PMID: 37599336 PMCID: PMC10440339 DOI: 10.1038/s41598-023-40580-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 08/13/2023] [Indexed: 08/22/2023] Open
Abstract
Social reforestation programs plant trees on degraded, uncultivated land in low-income regions to allow the local population to generate income from selling wood products and-in case of agroforestry systems-to grow food. For fundraising it is of interest to demonstrate not only positive social impacts but also environmental ones. Proving negative greenhouse gas (GHG) emissions would allow the programs to enter the market for carbon offsetting projects and liberate further funding. In a case study, a social reforestation program in Kalimantan, Indonesia, is analyzed. GHG emissions (according to ISO 14067, PAS 2050 and EU ILCD Handbook for LCA) of the main product, laminated veneer lumber plywood, are determined as 622 and 21 kg CO2-e/m3 for short-term and long-term (above 100 years) plywood use, respectively. Switching to lignin-based resins and renewable electricity could reduce emissions down to - 363 kg CO2-e/m3 for long-term use. The analyzed agroforestry system produces almost carbon-neutral plywood today and could be climate positive in the mid-term.
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Affiliation(s)
- Daniel Philipp Müller
- Department of Business Chemistry, Ulm University, Helmholtzstr. 18, 89081, Ulm, Germany.
| | - Nadine Szemkus
- Study Programme Sustainable Corporate Management, Ulm University, Helmholtzstr. 18, 89081, Ulm, Germany
| | - Michael Hiete
- Department of Business Chemistry, Ulm University, Helmholtzstr. 18, 89081, Ulm, Germany
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6
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Jones AG, Cridge A, Fraser S, Holt L, Klinger S, McGregor KF, Paul T, Payn T, Scott MB, Yao RT, Dickinson Y. Transitional forestry in New Zealand: re-evaluating the design and management of forest systems through the lens of forest purpose. Biol Rev Camb Philos Soc 2023; 98:1003-1015. [PMID: 36808687 DOI: 10.1111/brv.12941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 02/07/2023] [Accepted: 02/09/2023] [Indexed: 02/21/2023]
Abstract
Forestry management worldwide has become increasingly effective at obtaining high timber yields from productive forests. In New Zealand, a focus on improving an increasingly successful and largely Pinus radiata plantation forestry model over the last 150 years has resulted in some of the most productive timber forests in the temperate zone. In contrast to this success, the full range of forested landscapes across New Zealand, including native forests, are impacted by an array of pressures from introduced pests, diseases, and a changing climate, presenting a collective risk of losses in biological, social and economic value. As the national government policies incentivise reforestation and afforestation, the social acceptability of some forms of newly planted forests is also being challenged. Here, we review relevant literature in the area of integrated forest landscape management to optimise forests as nature-based solutions, presenting 'transitional forestry' as a model design and management paradigm appropriate to a range of forest types, where forest purpose is placed at the heart of decision making. We use New Zealand as a case study region, describing how this purpose-led transitional forestry model can benefit a cross section of forest types, from industrialised forest plantations to dedicated conservation forests and a range of multiple-purpose forests in between. Transitional forestry is an ongoing multi-decade process of change from current 'business-as-usual' forest management to future systems of forest management, embedded across a continuum of forest types. This holistic framework incorporates elements to enhance efficiencies of timber production, improve overall forest landscape resilience, and reduce some potential negative environmental impacts of commercial plantation forestry, while allowing the ecosystem functioning of commercial and non-commercial forests to be maximised, with increased public and biodiversity conservation value. Implementation of transitional forestry addresses tensions that arise between meeting climate mitigation targets and improving biodiversity criteria through afforestation, alongside increasing demand for forest biomass feedstocks to meet the demands of near-term bioenergy and bioeconomy goals. As ambitious government international targets are set for reforestation and afforestation using both native and exotic species, there is an increasing opportunity to make such transitions via integrated thinking that optimises forest values across a continuum of forest types, while embracing the diversity of ways in which such targets can be reached.
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Affiliation(s)
- Alan G Jones
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Andrew Cridge
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Stuart Fraser
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Lania Holt
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Sebastian Klinger
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Kirsty F McGregor
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Thomas Paul
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Tim Payn
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Matthew B Scott
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Richard T Yao
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
| | - Yvette Dickinson
- Scion (New Zealand Forest Research Institute), Titokorangi Drive, Private Bag 3020, Rotorua, 3046, New Zealand
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7
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Nissan A, Alcolombri U, Peleg N, Galili N, Jimenez-Martinez J, Molnar P, Holzner M. Global warming accelerates soil heterotrophic respiration. Nat Commun 2023; 14:3452. [PMID: 37301858 PMCID: PMC10257684 DOI: 10.1038/s41467-023-38981-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
Carbon efflux from soils is the largest terrestrial carbon source to the atmosphere, yet it is still one of the most uncertain fluxes in the Earth's carbon budget. A dominant component of this flux is heterotrophic respiration, influenced by several environmental factors, most notably soil temperature and moisture. Here, we develop a mechanistic model from micro to global scale to explore how changes in soil water content and temperature affect soil heterotrophic respiration. Simulations, laboratory measurements, and field observations validate the new approach. Estimates from the model show that heterotrophic respiration has been increasing since the 1980s at a rate of about 2% per decade globally. Using future projections of surface temperature and soil moisture, the model predicts a global increase of about 40% in heterotrophic respiration by the end of the century under the worst-case emission scenario, where the Arctic region is expected to experience a more than two-fold increase, driven primarily by declining soil moisture rather than temperature increase.
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Affiliation(s)
- Alon Nissan
- Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, 8093, Switzerland.
| | - Uria Alcolombri
- Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, 8093, Switzerland
| | - Nadav Peleg
- Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, 1015, Switzerland
| | - Nir Galili
- Geological Institute, Department of Earth Sciences, ETH Zürich, Zürich, 8092, Switzerland
| | - Joaquin Jimenez-Martinez
- Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, 8093, Switzerland
- Department of Water Resources and Drinking Water, Swiss Federal Institute of Aquatic Science and Technology, EAWAG, Dübendorf, 8600, Switzerland
| | - Peter Molnar
- Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, 8093, Switzerland
| | - Markus Holzner
- Department of Water Resources and Drinking Water, Swiss Federal Institute of Aquatic Science and Technology, EAWAG, Dübendorf, 8600, Switzerland
- Biodiversity and Conservation Biology, Swiss Federal Institute for Forest Snow and Landscape Research, WSL, Birmensdorf, 8903, Switzerland
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8
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Janus J, Ertunç E. Impact of land consolidation on agricultural decarbonization: Estimation of changes in carbon dioxide emissions due to farm transport. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 873:162391. [PMID: 36822421 DOI: 10.1016/j.scitotenv.2023.162391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/06/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Areas used for agriculture are a large source of carbon emissions, but there is great potential for reducing them. Land consolidation, through the comprehensive reorganization of the spatial arrangement of farms, can reduce emissions as a result of reducing fuel consumption. The subjects of this study are the veracity of this statement and the scope of variation in the potential reduction of carbon emissions. The analysis covered six land consolidation projects in Poland and Turkey, for several agricultural models that differ in the level of fuel consumption. Changes in agricultural road layout resulting from the implementation of land consolidation projects and changes in the number of farm plots and their spatial distribution were considered. The study considered several different levels and structures of fuel consumption on farms. The applied methodology is based on analysis of changes in distance to fields resulting from land consolidation projects, which are then expressed as changes in fuel consumption. The obtained emission reduction results for the studied land consolidation projects were diverse and range from 0.3 to 170 kg CO2/ha/year. The reduction in fuel consumption on farms at the level of individual villages reached a maximum of 32 %, while the average value of this reduction in the entire surveyed set was 12.5 %. The proposed approach increases the accuracy of existing methods for estimating the long-term balance of carbon emissions and carbon accumulation related to the implementation of land consolidation projects. The observed emission reduction values can be considered a significant economic and ecological effect because the effects of these projects persist for at least several decades.
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Affiliation(s)
- Jarosław Janus
- Department of Agricultural Land Surveying, Cadastre and Photogrammetry, Faculty of Environmental Engineering and Land Surveying, University of Agriculture in Krakow, ul. Balicka 253a, 30-198 Krakow, Poland.
| | - Ela Ertunç
- Konya Technical University, Faculty of Engineering and Natural Sciences, Department of Geomatics Engineering, Konya, Turkey.
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9
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Gorman CE, Torsney A, Gaughran A, McKeon CM, Farrell CA, White C, Donohue I, Stout JC, Buckley YM. Reconciling climate action with the need for biodiversity protection, restoration and rehabilitation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159316. [PMID: 36228799 DOI: 10.1016/j.scitotenv.2022.159316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Globally, we are faced with a climate crisis that requires urgent transition to a low-carbon economy. Simultaneously, the biodiversity crisis demands equally urgent action to prevent further species loss and promote restoration and rehabilitation of ecosystems. Climate action itself must prevent further pressures on biodiversity and options for synergistic gains for both climate and biodiversity change mitigation and adaptation need to be explored and implemented. Here, we review the key potential impacts of climate mitigation measures in energy and land-use on biodiversity, including the development of renewable energy such as offshore and onshore wind, solar, and bioenergy. We also assess the potential impacts of climate action driven afforestation and native habitat rehabilitation and restoration. We apply our findings to Ireland as a unique case-study as the government develops a coordinated response to climate and biodiversity change through declaration of a joint climate and biodiversity emergency and inclusion of biodiversity in key climate change legislation and the national Climate Action Plan. However, acknowledgement of these intertwined crises is only a first step; implementation of synergistic solutions requires careful planning. We demonstrate how synergy between climate and biodiversity action can be gained through explicit consideration of the effects of climate change mitigation strategies, such as energy infrastructure development and land-use change, on biodiversity. We identify several potential "win-win" strategies for both climate mitigation and biodiversity conservation. For Ireland, these include increasing offshore wind capacity, rehabilitating natural areas surrounding onshore wind turbines, and limiting the development of solar photovoltaics to the built environment. Ultimately, climate mitigation should be implemented in a "Right Action, Right Place" framework to maximise positive biodiversity benefits. This review provides one of the first examples of how national climate actions can be implemented in a biodiversity-conscious way to initiate discussion about synergistic solutions for both climate and biodiversity.
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Affiliation(s)
- Courtney E Gorman
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland.
| | - Andrew Torsney
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
| | | | - Caroline M McKeon
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
| | | | - Cian White
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
| | - Ian Donohue
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
| | - Jane C Stout
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
| | - Yvonne M Buckley
- School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
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10
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Certini G, Scalenghe R. The crucial interactions between climate and soil. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:159169. [PMID: 36206907 DOI: 10.1016/j.scitotenv.2022.159169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/25/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
Since the birth of soil science, climate has been recognized as a soil-forming factor, along with parent rock, time, topography, and organisms (from which humans were later kept distinct), often prevalent on the other factors on the very long term. But the climate is in turns affected by soils and their management. This paper describes the interrelationships between climate - and its current change - and soil, focusing on each single factor of its formation. Parent material governs, primarily through the particle size distribution, the capacity of soil to retain water and organic matter, which are two main soil-related drivers of the climate. Time is the only unmanageable soil-forming factor; however, extreme climatic phenomena can upset the soil or even dismantle it, so as to slow down the pathway of pedogenesis or even make it start from scratch. Topography, which drives the pedogenesis mostly controlling rainfall distribution - with repercussions also on the climate - is not anymore a given factor because humans have often become a shaper of it. Indeed humans now play a key role in affecting in a plethora of ways those soil properties that most deal with climate. The abundance and diversity of the other organisms are generally positive to soil quality and as a buffer for climate, but there are troubling evidences that climate change is decreasing soil biodiversity. The corpus of researches on mutual feedback between climate and soil has essentially demonstrated that the best soil management in terms of climate change mitigation must aim at promoting vegetation growth and maximizing soil organic matter content and water retention. Some ongoing virtuous initiatives (e.g., the Great Green Wall of Africa) and farming systems (e.g., the conservation agriculture) should be extended as much as possible worldwide to enable the soil to make the greatest contribution to climate change mitigation.
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Affiliation(s)
- Giacomo Certini
- Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali (DAGRI), Università degli Studi di Firenze, 50144 Firenze, Italy.
| | - Riccardo Scalenghe
- Dipartimento di Scienze Agrarie, Alimentari e Forestali (SAAF), Università degli Studi di Palermo, 90128 Palermo, Italy.
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11
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Moreno J, Van de Ven DJ, Sampedro J, Gambhir A, Woods J, Gonzalez-Eguino M. Assessing synergies and trade-offs of diverging Paris-compliant mitigation strategies with long-term SDG objectives. GLOBAL ENVIRONMENTAL CHANGE : HUMAN AND POLICY DIMENSIONS 2023; 78:102624. [PMID: 36846829 PMCID: PMC9941755 DOI: 10.1016/j.gloenvcha.2022.102624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 10/07/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
The Sustainable Development Goals (SDGs) and the Paris Agreement are the two transformative agendas, which set the benchmarks for nations to address urgent social, economic and environmental challenges. Aside from setting long-term goals, the pathways followed by nations will involve a series of synergies and trade-offs both between and within these agendas. Since it will not be possible to optimise across the 17 SDGs while simultaneously transitioning to low-carbon societies, it will be necessary to implement policies to address the most critical aspects of the agendas and understand the implications for the other dimensions. Here, we rely on a modelling exercise to analyse the long-term implications of a variety of Paris-compliant mitigation strategies suggested in the recent scientific literature on multiple dimensions of the SDG Agenda. The strategies included rely on technological solutions such as renewable energy deployment or carbon capture and storage, nature-based solutions such as afforestation and behavioural changes in the demand side. Results for a selection of energy-environment SDGs suggest that some mitigation pathways could have negative implications on food and water prices, forest cover and increase pressure on water resources depending on the strategy followed, while renewable energy shares, household energy costs, ambient air pollution and yield impacts could be improved simultaneously while reducing greenhouse gas emissions. Overall, results indicate that promoting changes in the demand side could be beneficial to limit potential trade-offs.
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Affiliation(s)
- Jorge Moreno
- Basque Centre for Climate Change (BC3), Leioa, Spain
- Centre for Environmental Policy, Imperial College London, London SW7 2AZ, United Kingdom
| | | | - Jon Sampedro
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
| | - Ajay Gambhir
- Grantham Institute for Climate Change and the Environment, Imperial College London, London, United Kingdom
| | - Jem Woods
- Centre for Environmental Policy, Imperial College London, London SW7 2AZ, United Kingdom
| | - Mikel Gonzalez-Eguino
- Basque Centre for Climate Change (BC3), Leioa, Spain
- University of the Basque Country, Bilbao, Spain
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12
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Multi-model approach to integrate climate change impact on carbon sequestration potential of afforestation scenarios in Quebec, Canada. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.110144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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13
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Brook R, Forster E, Styles D, Mazzetto AM, Arndt C, Esquivel MJ, Chadwick D. Silvopastoral systems for offsetting livestock emissions in the tropics: a case study of a dairy farm in Costa Rica. AGRONOMY FOR SUSTAINABLE DEVELOPMENT 2022; 42:101. [PMID: 36254245 PMCID: PMC9560984 DOI: 10.1007/s13593-022-00834-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
UNLABELLED Ways are being sought to reduce the environmental impact of ruminant livestock farming. Integration of trees into farming systems has been advocated as a measure to deliver ecosystem services, inter alia climate regulation and adaptation, water quality regulation, provisioning of fibre, fuel and habitats to support biodiversity. Despite the rapid expansion of cattle farming in the tropics, notably in Latin America, there is little robust evidence on the extent to which trees are able to mitigate the effects of cattle farming in this ecological zone. This article describes a case study conducted on a large, specialised dairy farm in Costa Rica, where two-thirds of the field boundaries are live tree fences. For the first time, this study quantifies the offset potential of trees by estimating rate of carbon sequestration in a silvopastoral system (SPS) in the tropics. It was found that over a 30-month interval, trees sequestered 1.43 Mg C ha-1 year-1 above and below ground. Attributional life cycle assessment (LCA) (cradle to farm gate) was applied to calculate the carbon footprint of milk produced on the farm for the years 2016 to 2018. Trees in live fences offset 21-37% of milk footprints, resulting in residual net footprints of 0.75±0.25 to 0.84±0.26 kg CO2 eq. kg-1 milk. Exclusion of life cycle emissions that may not fall within national emission inventory accounting (e.g. fertiliser manufacture and feed production) increased the mean offset from 27 to 34% of gross milk footprint. Although based on temporally limited data (30 months), our findings indicate that a live fence SPS could play an important role in short- to medium-term climate mitigation from livestock production, buying time for deployment of long-term mitigation and adaptation planning. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s13593-022-00834-z.
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Affiliation(s)
- Robert Brook
- School of Natural Sciences, Bangor University, Bangor, LL57 2UW UK
- CATIE-Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica
| | - Eilidh Forster
- School of Natural Sciences, Bangor University, Bangor, LL57 2UW UK
| | - David Styles
- School of Natural Sciences, Bangor University, Bangor, LL57 2UW UK
- School of Engineering, University of Limerick, Limerick, Ireland
- Ryan Institute, School of Biological & Chemical Sciences, University of Galway, Galway, Ireland
| | - André Mancebo Mazzetto
- School of Natural Sciences, Bangor University, Bangor, LL57 2UW UK
- AgResearch Limited, Lincoln, New Zealand
| | - Claudia Arndt
- CATIE-Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica
- Mazangira Centre, International Livestock Research Institute (ILRI), P.O. Box 30709-00100, Nairobi, Kenya
| | - M. Jimena Esquivel
- CATIE-Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica
- Institute of Environmental Sciences, Faculty of Sciences, Leiden University, Leiden, The Netherlands
- Department of Animal Sciences, Wageningen University, Wageningen, The Netherlands
| | - David Chadwick
- School of Natural Sciences, Bangor University, Bangor, LL57 2UW UK
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14
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Zhang D, Tang Y, Zhang C, Huhe F, Wu B, Gong X, Chuang SSC, Zheng J. Formulating Zwitterionic, Responsive Polymers for Designing Smart Soils. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2022; 18:e2203899. [PMID: 35996809 DOI: 10.1002/smll.202203899] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/28/2022] [Indexed: 06/15/2023]
Abstract
The design of new remediation strategies and materials for treating saline-alkaline soils is of fundamental and practical importantance for many applications. Conventional soil remediation strategies mainly focus on the development of fertilizers or additives for water, nutrient, and heavy metal managements in soils, but they often overlook a soil sensing function for early detection of salinization/alkalization levels toward optimal and timely soil remediation. Here, new smart soils, structurally consisting of the upper signal soil and the bottom hygroscopic bed and chemically including zwitterionic, thermo-responsive poly(NIPAM-co-VPES) and poly(NIPAM-co-SBAA) aerogels in each soil layer are formulated. Upon salinization, the resultant smart soils exhibit multiple superior capacities for reducing the soil salinity and alkalinity through ion exchange, controlling the water cycling, modulating the degradation of pyridine-base ligands into water-soluble, nitrogenous salts-rich ingredients for soil fertility, and real-time monitoring salinized soils via pH-induced allochroic color changes. Further studies of plant growth in smart soils with or without salinization treatments confirm a synergy effect of soil remediation and soil sensing on facilitating the growth of plants and increasing the saline-alkaline tolerance of plants. The esign concept of smart soils can be further expanded for soil remediation and assessment.
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Affiliation(s)
- Dong Zhang
- Department of Chemical, Biomolecular, and Corrosion Engineering, The University of Akron, Akron, OH, 44325, USA
| | - Yijing Tang
- Department of Chemical, Biomolecular, and Corrosion Engineering, The University of Akron, Akron, OH, 44325, USA
| | - Chang Zhang
- Ningbo Institute of Material Technology and Engineering, Chinese Academy of Sciences, Zhongguan West Road 1219, Ningbo, 315201, China
| | - Fnu Huhe
- School of Polymer Science and Polymer Engineering, The University of Akron, 170 University Avenue, Akron, OH, 44325, USA
| | - Baoyi Wu
- Ningbo Institute of Material Technology and Engineering, Chinese Academy of Sciences, Zhongguan West Road 1219, Ningbo, 315201, China
| | - Xiong Gong
- School of Polymer Science and Polymer Engineering, The University of Akron, 170 University Avenue, Akron, OH, 44325, USA
| | - Steven S C Chuang
- School of Polymer Science and Polymer Engineering, The University of Akron, 170 University Avenue, Akron, OH, 44325, USA
| | - Jie Zheng
- Department of Chemical, Biomolecular, and Corrosion Engineering, The University of Akron, Akron, OH, 44325, USA
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15
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Kobayashi Y, Seidl R, Rammer W, Suzuki KF, Mori AS. Identifying effective tree planting schemes to restore forest carbon and biodiversity in Shiretoko National Park, Japan. Restor Ecol 2022. [DOI: 10.1111/rec.13681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Yuta Kobayashi
- Faculty of Environment and Information Sciences Yokohama National University 79‐7 Tokiwadai, Hodogaya, Yokohama Kanagawa 240‐8501 Japan
- Research Center for Advanced Science and Technology the University of Tokyo 4‐6‐1 Komaba Meguro Tokyo 153‐8904 Japan
| | - Rupert Seidl
- Ecosystem Dynamics and Forest Management Group, School of Life Sciences Technical University of Munich Hans‐Carl‐von‐Carlowitz‐Platz 2, Freising Germany
- Berchtesgaden National Park Berchtesgaden Doktorberg 6, 83471 Germany
| | - Werner Rammer
- Ecosystem Dynamics and Forest Management Group, School of Life Sciences Technical University of Munich Hans‐Carl‐von‐Carlowitz‐Platz 2, Freising Germany
| | - Kureha F. Suzuki
- Graduate School of Environment and Information Sciences Yokohama National University 79‐7 Tokiwadai, Hodogaya, Yokohama Kanagawa 240‐8501 Japan
| | - Akira S. Mori
- Faculty of Environment and Information Sciences Yokohama National University 79‐7 Tokiwadai, Hodogaya, Yokohama Kanagawa 240‐8501 Japan
- Research Center for Advanced Science and Technology the University of Tokyo 4‐6‐1 Komaba Meguro Tokyo 153‐8904 Japan
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16
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Keith H, Mackey B, Kun Z, Mikoláš M, Svitok M, Svoboda M. Evaluating the mitigation effectiveness of forests managed for conservation versus commodity production using an Australian example. Conserv Lett 2022. [DOI: 10.1111/conl.12878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Heather Keith
- Griffith Climate Action Beacon Griffith University Gold Coast Queensland Australia
| | - Brendan Mackey
- Griffith Climate Action Beacon Griffith University Gold Coast Queensland Australia
| | - Zoltan Kun
- European Department Frankfurt Zoological Society Frankfurt‐am‐Main Germany
| | - Martin Mikoláš
- Department of Forest Ecology Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Suchdol Czech Republic
| | - Marek Svitok
- Department of Biology and General Ecology Faculty of Ecology and Environmental Sciences Technical University in Zvolen Zvolen Slovakia
| | - Miroslav Svoboda
- Department of Forest Ecology Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Suchdol Czech Republic
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17
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Githumbi E, Pirzamanbein B, Lindström J, Poska A, Fyfe R, Mazier F, Nielsen AB, Sugita S, Trondman AK, Woodbridge J, Gaillard MJ. Pollen-Based Maps of Past Regional Vegetation Cover in Europe Over 12 Millennia—Evaluation and Potential. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.795794] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Realistic and accurate reconstructions of past vegetation cover are necessary to study past environmental changes. This is important since the effects of human land-use changes (e.g. agriculture, deforestation and afforestation/reforestation) on biodiversity and climate are still under debate. Over the last decade, development, validation, and application of pollen-vegetation relationship models have made it possible to estimate plant abundance from fossil pollen data at both local and regional scales. In particular, the REVEALS model has been applied to produce datasets of past regional plant cover at 1° spatial resolution at large subcontinental scales (North America, Europe, and China). However, such reconstructions are spatially discontinuous due to the discrete and irregular geographical distribution of sites (lakes and peat bogs) from which fossil pollen records have been produced. Therefore, spatial statistical models have been developed to create continuous maps of past plant cover using the REVEALS-based land cover estimates. In this paper, we present the first continuous time series of spatially complete maps of past plant cover across Europe during the Holocene (25 time windows covering the period from 11.7 k BP to present). We use a spatial-statistical model for compositional data to interpolate REVEALS-based estimates of three major land-cover types (LCTs), i.e., evergreen trees, summer-green trees and open land (grasses, herbs and low shrubs); producing spatially complete maps of the past coverage of these three LCTs. The spatial model uses four auxiliary data sets—latitude, longitude, elevation, and independent scenarios of past anthropogenic land-cover change based on per-capita land-use estimates (“standard” KK10 scenarios)—to improve model performance for areas with complex topography or few observations. We evaluate the resulting reconstructions for selected time windows using present day maps from the European Forest Institute, cross validate, and compare the results with earlier pollen-based spatially-continuous estimates for five selected time windows, i.e., 100 BP-present, 350–100 BP, 700–350 BP, 3.2–2.7 k BP, and 6.2–5.7 k BP. The evaluations suggest that the statistical model provides robust spatial reconstructions. From the maps we observe the broad change in the land-cover of Europe from dominance of naturally open land and persisting remnants of continental ice in the Early Holocene to a high fraction of forest cover in the Mid Holocene, and anthropogenic deforestation in the Late Holocene. The temporal and spatial continuity is relevant for land-use, land-cover, and climate research.
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18
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Xie X, Zhang X, Shen J, Du K. Poplar's Waterlogging Resistance Modeling and Evaluating: Exploring and Perfecting the Feasibility of Machine Learning Methods in Plant Science. FRONTIERS IN PLANT SCIENCE 2022; 13:821365. [PMID: 35222479 PMCID: PMC8874143 DOI: 10.3389/fpls.2022.821365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
Floods, as one of the most common disasters in the natural environment, have caused huge losses to human life and property. Predicting the flood resistance of poplar can effectively help researchers select seedlings scientifically and resist floods precisely. Using machine learning algorithms, models of poplar's waterlogging tolerance were established and evaluated. First of all, the evaluation indexes of poplar's waterlogging tolerance were analyzed and determined. Then, significance testing, correlation analysis, and three feature selection algorithms (Hierarchical clustering, Lasso, and Stepwise regression) were used to screen photosynthesis, chlorophyll fluorescence, and environmental parameters. Based on this, four machine learning methods, BP neural network regression (BPR), extreme learning machine regression (ELMR), support vector regression (SVR), and random forest regression (RFR) were used to predict the flood resistance of poplar. The results show that random forest regression (RFR) and support vector regression (SVR) have high precision. On the test set, the coefficient of determination (R2) is 0.8351 and 0.6864, the root mean square error (RMSE) is 0.2016 and 0.2780, and the mean absolute error (MAE) is 0.1782 and 0.2031, respectively. Therefore, random forest regression (RFR) and support vector regression (SVR) can be given priority to predict poplar flood resistance.
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Affiliation(s)
- Xuelin Xie
- College of Sciences, Huazhong Agricultural University, Wuhan, China
| | | | - Jingfang Shen
- College of Sciences, Huazhong Agricultural University, Wuhan, China
| | - Kebing Du
- College of Horticulture and Forestry Sciences, Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agricultural University, Wuhan, China
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19
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Alivand MS, Mazaheri O, Wu Y, Zavabeti A, Stevens GW, Scholes CA, Mumford KA. Water-Dispersible Nanocatalysts with Engineered Structures: The New Generation of Nanomaterials for Energy-Efficient CO 2 Capture. ACS APPLIED MATERIALS & INTERFACES 2021; 13:57294-57305. [PMID: 34812613 DOI: 10.1021/acsami.1c17678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The high energy demand of CO2 absorption-desorption technologies has significantly inhibited their industrial utilization and implementation of the Paris Climate Accord. Catalytic solvent regeneration is of considerable interest due to its low operating temperature and high energy efficiency. Of the catalysts available, heterogeneous catalysts have exhibited relatively poor performances and are hindered by other challenges, which have slowed their large-scale deployment. Herein, we report a facile and eco-friendly approach for synthesizing water-dispersible Fe3O4 nanocatalysts coated with a wide range of amino acids (12 representative molecules) in aqueous media. The acidic properties of water-dispersible nanocatalysts can be easily tuned by introducing different functional groups during the hydrothermal synthesis procedure. We demonstrate that the prepared nanocatalysts can be used in energy-efficient CO2 capture plants with ease-of-use, at very low concentrations (0.1 wt %) and with extra-high efficiencies (up to ∼75% energy reductions). They can be applied in a range of solutions, including amino acids (i.e., short-chain, long-chain, and cyclic) and amines (i.e., primary, tertiary, and primary-tertiary mixture). Considering the superiority of the presented water-dispersible nanocatalysts, this technology is expected to provide a new pathway for the development of energy-efficient CO2 capture technologies.
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Affiliation(s)
- Masood S Alivand
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Omid Mazaheri
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
- School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Yue Wu
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Ali Zavabeti
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Geoffrey W Stevens
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Colin A Scholes
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Kathryn A Mumford
- Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
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20
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Wang F, Harindintwali JD, Yuan Z, Wang M, Wang F, Li S, Yin Z, Huang L, Fu Y, Li L, Chang SX, Zhang L, Rinklebe J, Yuan Z, Zhu Q, Xiang L, Tsang DC, Xu L, Jiang X, Liu J, Wei N, Kästner M, Zou Y, Ok YS, Shen J, Peng D, Zhang W, Barceló D, Zhou Y, Bai Z, Li B, Zhang B, Wei K, Cao H, Tan Z, Zhao LB, He X, Zheng J, Bolan N, Liu X, Huang C, Dietmann S, Luo M, Sun N, Gong J, Gong Y, Brahushi F, Zhang T, Xiao C, Li X, Chen W, Jiao N, Lehmann J, Zhu YG, Jin H, Schäffer A, Tiedje JM, Chen JM. Technologies and perspectives for achieving carbon neutrality. Innovation (N Y) 2021; 2:100180. [PMID: 34877561 PMCID: PMC8633420 DOI: 10.1016/j.xinn.2021.100180] [Citation(s) in RCA: 112] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 10/27/2021] [Indexed: 12/17/2022] Open
Abstract
Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.
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Affiliation(s)
- Fang Wang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jean Damascene Harindintwali
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhizhang Yuan
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Wang
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Faming Wang
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
- Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sheng Li
- Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhigang Yin
- Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Huang
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Yuhao Fu
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Li
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Scott X. Chang
- Department of Renewable Resources, University of Alberta, Edmonton, AB T6G 2E3, Canada
| | - Linjuan Zhang
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jörg Rinklebe
- Department of Soil and Groundwater Management, Bergische Universität Wuppertal, Wuppertal 42285, Germany
| | - Zuoqiang Yuan
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Liaoning 110016, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qinggong Zhu
- Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leilei Xiang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Daniel C.W. Tsang
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Liang Xu
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Jiang
- CAS Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jihua Liu
- Institute of Marine Science and Technology, Shandong University, Qingdao 266273, China
| | - Ning Wei
- Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430000, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Matthias Kästner
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research – UFZ, Leipzig 04318, Germany
| | - Yang Zou
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Jianlin Shen
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dailiang Peng
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Zhang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Damià Barceló
- Catalan Institute for Water Research ICRA-CERCA, Girona 17003, Spain
| | - Yongjin Zhou
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaohai Bai
- Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Boqiang Li
- CAS Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bin Zhang
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ke Wei
- The Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hujun Cao
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhiliang Tan
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liu-bin Zhao
- Department of Chemistry, School of Chemistry and Chemical Engineering, Southwest University, Chongqing, 400715, China
| | - Xiao He
- Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinxing Zheng
- Institute of Plasma Physics, Chinese Academy of Sciences, Anhui 230031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nanthi Bolan
- School of Agriculture and Environment, Institute of Agriculture, University of Western Australia, Crawley 6009, Australia
| | - Xiaohong Liu
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changping Huang
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sabine Dietmann
- Institute for Informatics (I), Washington University, St. Louis, MO 63110-1010, USA
| | - Ming Luo
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nannan Sun
- Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jirui Gong
- Key Laboratory of Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yulie Gong
- CAS Key Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ferdi Brahushi
- Department of Agro-environment and Ecology, Agricultural University of Tirana, Tirana 1029, Albania
| | - Tangtang Zhang
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Cunde Xiao
- Key Laboratory of Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xianfeng Li
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenfu Chen
- Shenyang Agricultural University, Shenyang 110866, China
| | - Nianzhi Jiao
- Joint Laboratory for Ocean Research and Education at Dalhousie University, Shandong University and Xiamen University, Halifax, NS, B3H 4R2, Canada, Qingdao 266237, China, and, Xiamen 361005, China
- Institute of Marine Microbes and Ecospheres, Xiamen University, Xiamen 361101, China
- State Key Laboratory of Marine Environmental Science and College of Ocean and Earth Sciences, Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen 361005, China
| | - Johannes Lehmann
- School of Integrative Plant Science, Section of Soil and Crop Sciences, Cornell University, Ithaca, NY 14853, USA
- Institute for Advanced Studies, Technical University Munich, Garching 85748, Germany
| | - Yong-Guan Zhu
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, 361021, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongguang Jin
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Andreas Schäffer
- Institute for Environmental Research, RWTH Aachen University, Aachen 52074, Germany
| | - James M. Tiedje
- Center for Microbial Ecology, Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Jing M. Chen
- Department of Geography and Planning, University of Toronto, Ontario, Canada, M5S 3G3
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