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van Breugel M, Bongers F, Norden N, Meave JA, Amissah L, Chanthorn W, Chazdon R, Craven D, Farrior C, Hall JS, Hérault B, Jakovac C, Lebrija-Trejos E, Martínez-Ramos M, Muñoz R, Poorter L, Rüger N, van der Sande M, Dent DH. Feedback loops drive ecological succession: towards a unified conceptual framework. Biol Rev Camb Philos Soc 2024; 99:928-949. [PMID: 38226776 DOI: 10.1111/brv.13051] [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: 06/28/2023] [Revised: 12/29/2023] [Accepted: 12/29/2023] [Indexed: 01/17/2024]
Abstract
The core principle shared by most theories and models of succession is that, following a major disturbance, plant-environment feedback dynamics drive a directional change in the plant community. The most commonly studied feedback loops are those in which the regrowth of the plant community causes changes to the abiotic (e.g. soil nutrients) or biotic (e.g. dispersers) environment, which differentially affect species availability or performance. This, in turn, leads to shifts in the species composition of the plant community. However, there are many other PE feedback loops that potentially drive succession, each of which can be considered a model of succession. While plant-environment feedback loops in principle generate predictable successional trajectories, succession is generally observed to be highly variable. Factors contributing to this variability are the stochastic processes involved in feedback dynamics, such as individual mortality and seed dispersal, and extrinsic causes of succession, which are not affected by changes in the plant community but do affect species performance or availability. Both can lead to variation in the identity of dominant species within communities. This, in turn, leads to further contingencies if these species differ in their effect on their environment (priority effects). Predictability and variability are thus intrinsically linked features of ecological succession. We present a new conceptual framework of ecological succession that integrates the propositions discussed above. This framework defines seven general causes: landscape context, disturbance and land-use, biotic factors, abiotic factors, species availability, species performance, and the plant community. When involved in a feedback loop, these general causes drive succession and when not, they are extrinsic causes that create variability in successional trajectories and dynamics. The proposed framework provides a guide for linking these general causes into causal pathways that represent specific models of succession. Our framework represents a systematic approach to identifying the main feedback processes and causes of variation at different successional stages. It can be used for systematic comparisons among study sites and along environmental gradients, to conceptualise studies, and to guide the formulation of research questions and design of field studies. Mapping an extensive field study onto our conceptual framework revealed that the pathways representing the study's empirical outcomes and conceptual model had important differences, underlining the need to move beyond the conceptual models that currently dominate in specific fields and to find ways to examine the importance of and interactions among alternative causal pathways of succession. To further this aim, we argue for integrating long-term studies across environmental and anthropogenic gradients, combined with controlled experiments and dynamic modelling.
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Affiliation(s)
- Michiel van Breugel
- Department of Geography, National University of Singapore, Arts Link, #03-01 Block AS2, 117570, Singapore
- Yale-NUS College, 16 College Avenue West, Singapore, 138527, Singapore
- Smithsonian Tropical Research Institute, Roosevelt Ave. Tupper Building - 401, Panama City, 0843-03092, Panama
| | - Frans Bongers
- Forest Ecology and Forest Management Group, Wageningen University & Research, PO Box 47, 6700 AA, Wageningen, The Netherlands
| | - Natalia Norden
- Centro de Estudios Socioecológicos y Cambio Global, Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Avenida Circunvalar #16-20, Bogotá, Colombia
| | - Jorge A Meave
- Departamento de Ecología y Recursos Naturales, Facultad de Ciencias, Universidad Nacional Autónoma de México. Circuito Exterior s/n, Ciudad Universitaria, Coyoacán, Ciudad de México, C.P. 04510, Mexico
| | - Lucy Amissah
- CSIR-Forestry Research Institute of Ghana, UPO Box 63, Kumasi, Ghana
| | - Wirong Chanthorn
- Department of Environmental Technology and Management, Faculty of Environment, Kasetsart University, 50 Ngamwongwan Road, Jatujak District, 10900, Thailand
| | - Robin Chazdon
- Forest Research Institute, University of the Sunshine Coast, 90 Sippy Downs Dr, Sippy Downs, Queensland, 4556, Australia
| | - Dylan Craven
- Center for Genomics, Ecology & Environment, Universidad Mayor, Camino La Piramide 5750, Huechuraba, Santiago, 8580745, Chile
| | - Caroline Farrior
- Department of Integrative Biology, University of Texas at Austin, 2415 Speedway, Stop C0930, Austin, Texas, 78705, USA
| | - Jefferson S Hall
- Smithsonian Tropical Research Institute, Roosevelt Ave. Tupper Building - 401, Panama City, 0843-03092, Panama
| | - Bruno Hérault
- CIRAD, UPR Forêts et Sociétés, F-34398 Montpellier, France & Forêts et Sociétés, Univ Montpellier, CIRAD, Montpellier, France
| | - Catarina Jakovac
- Departamento de Fitotecnia, Centro de Ciências Agrárias, Universidade Federal de Santa Catarina, Rod. Admar Gonzaga, 1346, 88034-000, Florianópolis, Brazil
| | - Edwin Lebrija-Trejos
- Department of Biology and Environment, University of Haifa-Oranim, Tivon, 36006, Israel
| | - Miguel Martínez-Ramos
- Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Campus Morelia, Antigua Carretera a Pátzcuaro # 8701, Col. Ex-Hacienda de San José de la Huerta, CP 58190, Morelia, Michoacán, Mexico
| | - Rodrigo Muñoz
- Forest Ecology and Forest Management Group, Wageningen University & Research, PO Box 47, 6700 AA, Wageningen, The Netherlands
| | - Lourens Poorter
- Forest Ecology and Forest Management Group, Wageningen University & Research, PO Box 47, 6700 AA, Wageningen, The Netherlands
| | - Nadja Rüger
- Smithsonian Tropical Research Institute, Roosevelt Ave. Tupper Building - 401, Panama City, 0843-03092, Panama
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstr. 4, 04103, Leipzig, Germany
- Department of Economics, Institute of Empirical Economic Research, University of Leipzig, Grimmaische Str. 12, 04109, Leipzig, Germany
| | - Masha van der Sande
- Forest Ecology and Forest Management Group, Wageningen University & Research, PO Box 47, 6700 AA, Wageningen, The Netherlands
| | - Daisy H Dent
- Smithsonian Tropical Research Institute, Roosevelt Ave. Tupper Building - 401, Panama City, 0843-03092, Panama
- ETH Zürich, Department of Environmental Systems Science, Institute for Integrative Biology, Universitätstrasse 16, 8092, Zürich, Switzerland
- Max Planck Institute for Animal Behavior, Am Obstberg 1, 78315 Radolfzell, Germany
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Eppinga MB, Michaels TK, Santos MJ, Bever JD. Introducing desirable patches to initiate ecosystem transitions and accelerate ecosystem restoration. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2023; 33:e2910. [PMID: 37602903 DOI: 10.1002/eap.2910] [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: 08/18/2022] [Revised: 05/30/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023]
Abstract
Meeting restoration targets may require active strategies to accelerate natural regeneration rates or overcome the resilience associated with degraded ecosystem states. Introducing desired ecosystem patches in degraded landscapes constitutes a promising active restoration strategy, with various mechanisms potentially causing these patches to become foci from which desired species can re-establish throughout the landscape. This study considers three mechanisms previously identified as potential drivers of introduced patch dynamics: autocatalytic nucleation, directed dispersal, and resource concentration. These mechanisms reflect qualitatively different positive feedbacks. We developed an ecological model framework that compared how the occurrence of each mechanism was reflected in spatio-temporal patch dynamics. We then analyzed the implications of these relationships for optimal restoration design. We found that patch expansion accelerated over time when driven by the autocatalytic nucleation mechanism, while patch expansion driven by the directed dispersal or resource concentration mechanisms decelerated over time. Additionally, when driven by autocatalytic nucleation, patch expansion was independent of patch position in the landscape. However, the proximity of other patches affected patch expansion either positively or negatively when driven by directed dispersal or resource concentration. For autocatalytic nucleation, introducing many small patches was a favorable strategy, provided that each individual patch exceeded a critical patch size. Introducing a single patch or a few large patches was the most effective restoration strategy to initiate the directed dispersal mechanism. Introducing many small patches was the most effective strategy for reaching restored ecosystem states driven by a resource concentration mechanism. Our model results suggest that introducing desirable patches can substantially accelerate ecosystem restoration, or even induce a critical transition from an otherwise stable degraded state toward a desired ecosystem state. However, the potential of this type of restoration strategy for a particular ecosystem may strongly depend on the mechanism driving patch dynamics. In turn, which mechanism drives patch dynamics may affect the optimal spatial design of an active restoration strategy. Each of the three mechanisms considered reflects distinct spatio-temporal patch dynamics, providing novel opportunities for empirically identifying key mechanisms, and restoration designs that introduce desired patches in degraded landscapes according to these patch dynamics.
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Affiliation(s)
| | - Theo K Michaels
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA
- Kansas Biological Survey, University of Kansas, Lawrence, Kansas, USA
| | - Maria J Santos
- Department of Geography, University of Zurich, Zurich, Switzerland
| | - James D Bever
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA
- Kansas Biological Survey, University of Kansas, Lawrence, Kansas, USA
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3
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Elliott S, Tucker NIJ, Shannon DP, Tiansawat P. The framework species method: harnessing natural regeneration to restore tropical forest ecosystems. Philos Trans R Soc Lond B Biol Sci 2023; 378:20210073. [PMID: 36373920 PMCID: PMC9661958 DOI: 10.1098/rstb.2021.0073] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 09/08/2022] [Indexed: 11/16/2022] Open
Abstract
As interest in restoring tropical forests surges, so does the need for effective methods to ensure success. The framework species method (FSM) restores forest ecosystems by densely planting open sites, close to natural forest, with woody species, indigenous to the reference ecosystem and selected for their ability to accelerate ecological succession. Criteria for selecting framework species include: (i) representative of the reference forest ecosystem, (ii) tolerant of open conditions, (iii) ability to suppress weeds, (iv) attractiveness to seed-dispersing animals and (v) easily propagated. The method is effective where forest remnants and viable populations of seed dispersers remain. The origins and elements of the FSM are discussed. We review its adoption in 12 countries. Adherence to original principles was mostly high, but some misuse of the term was evident. The need for clearer definitions was identified. We place the FSM on a scale of restoration methods, matched with degradation levels and compare its establishment costs with those of other methods. Obstacles to its wider adoption, both technical and socio-economic, are discussed, along with how these might be overcome. Finally, the FSM is more clearly defined to facilitate its use in contributing towards the goals of the UN Decade on Restoration. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.
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Affiliation(s)
- Stephen Elliott
- Forest Restoration Research Unit, Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
- Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Nigel I. J. Tucker
- College of Science and Engineering, James Cook University, Cairns QLD3811, Australia
| | - Dia Panitnard Shannon
- Forest Restoration Research Unit, Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
- Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Pimonrat Tiansawat
- Forest Restoration Research Unit, Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
- Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
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4
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Ngwenya DK, Holmes PM, Geerts S, Esler KJ. Scaling up restoration efforts by simulating the effects of fire to circumvent prescribed burns when preparing restoration sites in South African fynbos ecosystems. AUSTRAL ECOL 2022. [DOI: 10.1111/aec.13258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Duduzile K. Ngwenya
- Department of Conservation Ecology and Entomology Stellenbosch University, Private Bag X1 Matieland South Africa
- Centre of Excellence for Invasion Biology, Department of Botany and Zoology, Natural Sciences Building, Private Bag X1 Stellenbosch University Matieland South Africa
| | - Patricia M. Holmes
- Department of Conservation Ecology and Entomology Stellenbosch University, Private Bag X1 Matieland South Africa
- Centre of Excellence for Invasion Biology, Department of Botany and Zoology, Natural Sciences Building, Private Bag X1 Stellenbosch University Matieland South Africa
| | - Sjirk Geerts
- Centre of Excellence for Invasion Biology, Department of Botany and Zoology, Natural Sciences Building, Private Bag X1 Stellenbosch University Matieland South Africa
- Department of Conservation and Marine Sciences Cape Peninsula University of Technology Cape Town South Africa
| | - Karen J. Esler
- Department of Conservation Ecology and Entomology Stellenbosch University, Private Bag X1 Matieland South Africa
- Centre of Excellence for Invasion Biology, Department of Botany and Zoology, Natural Sciences Building, Private Bag X1 Stellenbosch University Matieland South Africa
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5
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Applestein C, Caughlin TT, Germino MJ. Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation. AOB PLANTS 2022; 14:plac045. [PMID: 36380819 PMCID: PMC9661893 DOI: 10.1093/aobpla/plac045] [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: 04/09/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
Plant-population recovery across large disturbance areas is often seed-limited. An understanding of seed dispersal patterns is fundamental for determining natural-regeneration potential. However, forecasting seed dispersal rates across heterogeneous landscapes remains a challenge. Our objectives were to determine (i) the landscape patterning of post-disturbance seed dispersal, and underlying sources of variation and the scale at which they operate, and (ii) how the natural seed dispersal patterns relate to a seed augmentation strategy. Vertical seed trapping experiments were replicated across 2 years and five burned and/or managed landscapes in sagebrush steppe. Multi-scale sampling and hierarchical Bayesian models were used to determine the scale of spatial variation in seed dispersal. We then integrated an empirical and mechanistic dispersal kernel for wind-dispersed species to project rates of seed dispersal and compared natural seed arrival to typical post-fire aerial seeding rates. Seeds were captured across the range of tested dispersal distances, up to a maximum distance of 26 m from seed-source plants, although dispersal to the furthest traps was variable. Seed dispersal was better explained by transect heterogeneity than by patch or site heterogeneity (transects were nested within patch within site). The number of seeds captured varied from a modelled mean of ~13 m-2 adjacent to patches of seed-producing plants, to nearly none at 10 m from patches, standardized over a 49-day period. Maximum seed dispersal distances on average were estimated to be 16 m according to a novel modelling approach using a 'latent' variable for dispersal distance based on seed trapping heights. Surprisingly, statistical representation of wind did not improve model fit and seed rain was not related to the large variation in total available seed of adjacent patches. The models predicted severe seed limitations were likely on typical burned areas, especially compared to the mean 95-250 seeds per m2 that previous literature suggested were required to generate sagebrush recovery. More broadly, our Bayesian data fusion approach could be applied to other cases that require quantitative estimates of long-distance seed dispersal across heterogeneous landscapes.
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Affiliation(s)
| | - T Trevor Caughlin
- Department of Biology, Boise State University, 1910 W University Drive, Boise, ID 83725, USA
| | - Matthew J Germino
- US Geological Survey, Forest and Rangeland Ecosystem Science Center, 230 N Collins Rd, Boise, ID 83702, USA
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6
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Dent DH, Estrada-Villegas S. Uniting niche differentiation and dispersal limitation predicts tropical forest succession. Trends Ecol Evol 2021; 36:700-708. [PMID: 33966918 DOI: 10.1016/j.tree.2021.04.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 03/31/2021] [Accepted: 04/01/2021] [Indexed: 11/16/2022]
Abstract
Tropical secondary forests are increasingly important for carbon sequestration and biodiversity conservation worldwide; yet, we still cannot accurately predict community turnover during secondary succession. We propose that integrating niche differentiation and dispersal limitation will generate an improved theoretical explanation of tropical forest succession. The interaction between seed sources and dispersers regulates seed movement throughout succession, and recent technological advances in animal tracking and molecular analyses enable us to accurately monitor seed movement as never before. We propose a framework to bridge the gap between niche differentiation and dispersal limitation. The Source-Disperser Limitation Framework (SDLF) provides a way to better predict secondary tropical forest succession across gradients of landscape disturbance by integrating seed sources and frugivore behavior.
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Affiliation(s)
- Daisy H Dent
- Biological and Environmental Sciences, University of Stirling, Stirling, Scotland, UK; Smithsonian Tropical Research Institute, Balboa, Panama; Max Planck Institute for Animal Behavior, Konstanz, Germany.
| | - Sergio Estrada-Villegas
- Smithsonian Tropical Research Institute, Balboa, Panama; Yale School of the Environment, Yale University, New Haven, CT, USA
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7
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Caughlin TT, Barber C, Asner GP, Glenn NF, Bohlman SA, Wilson CH. Monitoring tropical forest succession at landscape scales despite uncertainty in Landsat time series. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e02208. [PMID: 32627902 DOI: 10.1002/eap.2208] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
Forecasting rates of forest succession at landscape scales will aid global efforts to restore tree cover to millions of hectares of degraded land. While optical satellite remote sensing can detect regional land cover change, quantifying forest structural change is challenging. We developed a state-space modeling framework that applies Landsat satellite data to estimate variability in rates of natural regeneration between sites in a tropical landscape. Our models work by disentangling measurement error in Landsat-derived spectral reflectance from process error related to successional variability. We applied our modeling framework to rank rates of forest succession between 10 naturally regenerating sites in Southwestern Panama from about 2001 to 2015 and tested how different models for measurement error impacted forecast accuracy, ecological inference, and rankings of successional rates between sites. We achieved the greatest increase in forecasting accuracy by adding intra-annual phenological variation to a model based on Landsat-derived normalized difference vegetation index (NDVI). The best-performing model accounted for inter- and intra-annual noise in spectral reflectance and translated NDVI to canopy height via Landsat-lidar fusion. Modeling forest succession as a function of canopy height rather than NDVI also resulted in more realistic estimates of forest state during early succession, including greater confidence in rank order of successional rates between sites. These results establish the viability of state-space models to quantify ecological dynamics from time series of space-borne imagery. State-space models also provide a statistical approach well-suited to fusing high-resolution data, such as airborne lidar, with lower-resolution data that provides better temporal and spatial coverage, such as the Landsat satellite record. Monitoring forest succession using satellite imagery could play a key role in achieving global restoration targets, including identifying sites that will regain tree cover with minimal intervention.
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Affiliation(s)
- T Trevor Caughlin
- Biological Sciences, Boise State University, Boise, Idaho, 83725, USA
| | - Cristina Barber
- Biological Sciences, Boise State University, Boise, Idaho, 83725, USA
| | - Gregory P Asner
- Center for Global Discovery and Conservation Science, Arizona State University, Hilo, Hawaii, 96720, USA
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, 85287, USA
| | - Nancy F Glenn
- Department of Geosciences, Boise State University, Boise, Idaho, 83725, USA
- School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, Australia
| | - Stephanie A Bohlman
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida, 32611, USA
| | - Chris H Wilson
- Agronomy Department, University of Florida, Gainesville, Florida, 32611, USA
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8
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Smith CC, Espírito-Santo FDB, Healey JR, Young PJ, Lennox GD, Ferreira J, Barlow J. Secondary forests offset less than 10% of deforestation-mediated carbon emissions in the Brazilian Amazon. GLOBAL CHANGE BIOLOGY 2020; 26:7006-7020. [PMID: 32969561 DOI: 10.1111/gcb.15352] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 09/01/2020] [Indexed: 06/11/2023]
Abstract
Secondary forests are increasing in the Brazilian Amazon and have been cited as an important mechanism for reducing net carbon emissions. However, our understanding of the contribution of secondary forests to the Amazonian carbon balance is incomplete, and it is unclear to what extent emissions from old-growth deforestation have been offset by secondary forest growth. Using MapBiomas 3.1 and recently refined IPCC carbon sequestration estimates, we mapped the age and extent of secondary forests in the Brazilian Amazon and estimated their role in offsetting old-growth deforestation emissions since 1985. We also assessed whether secondary forests in the Brazilian Amazon are growing in conditions favourable for carbon accumulation in relation to a suite of climatic, landscape and local factors. In 2017, the 129,361 km2 of secondary forest in the Brazilian Amazon stored 0.33 ± 0.05 billion Mg of above-ground carbon but had offset just 9.37% of old-growth emissions since 1985. However, we find that the majority of Brazilian secondary forests are situated in contexts that are less favourable for carbon accumulation than the biome average. Our results demonstrate that old-growth forest loss remains the most important factor determining the carbon balance in the Brazilian Amazon. Understanding the implications of these findings will be essential for improving estimates of secondary forest carbon sequestration potential. More accurate quantification of secondary forest carbon stocks will support the production of appropriate management proposals that can efficiently harness the potential of secondary forests as a low-cost, nature-based tool for mitigating climate change.
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Affiliation(s)
| | - Fernando D B Espírito-Santo
- Leicester Institute of Space and Earth Observation, Centre for Landscape and Climate Research, School of Geography, Geology and Environment, University of Leicester, Leicester, UK
| | - John R Healey
- School of Natural Sciences, College of Environmental Sciences and Engineering, Bangor University, Bangor, UK
| | - Paul J Young
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
- Centre of Excellence for Environmental Data Science, Lancaster University, Lancaster, UK
| | - Gareth D Lennox
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | | | - Jos Barlow
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
- Federal University of Lavras, Minas Gerais, Brazil
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9
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Holmes PM, Esler KJ, van Wilgen BW, Richardson DM. Ecological restoration of ecosystems degraded by invasive alien plants in South African Fynbos: Is spontaneous succession a viable strategy? ACTA ACUST UNITED AC 2020. [DOI: 10.1080/0035919x.2020.1781291] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Patricia M. Holmes
- Centre for Invasion Biology, Department of Conservation Ecology and Entomology, Stellenbosh University, Private Bag X1, Matieland, 7602, South Africa
| | - Karen J. Esler
- Centre for Invasion Biology, Department of Conservation Ecology and Entomology, Stellenbosh University, Private Bag X1, Matieland, 7602, South Africa
| | - Brian W. van Wilgen
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
| | - David M. Richardson
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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10
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Requena-Mullor JM, Maguire KC, Shinneman DJ, Caughlin TT. Integrating anthropogenic factors into regional-scale species distribution models-A novel application in the imperiled sagebrush biome. GLOBAL CHANGE BIOLOGY 2019; 25:3844-3858. [PMID: 31180605 DOI: 10.1111/gcb.14728] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 05/10/2019] [Indexed: 06/09/2023]
Abstract
Species distribution models (SDMs) that rely on regional-scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local-scale anthropogenic variables, including wildfire history, land-use change, invasive species, and ecological restoration practices can override regional-scale variables to drive patterns of species distribution. Incorporating these human-induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human-induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field-sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI: -6.9%, 0.6%) when one fire occurs and cover decreases by 44.7% (95% CI: -47.9%, -41.3%) if at least one fire occurred over the 36 year period of record. Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land-use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species.
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Affiliation(s)
| | - Kaitlin C Maguire
- Forest and Rangeland Ecosystem Science Center, U.S. Geological Survey, Boise, Idaho
| | - Douglas J Shinneman
- Forest and Rangeland Ecosystem Science Center, U.S. Geological Survey, Boise, Idaho
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11
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Plant Attributes that Drive Dispersal and Establishment Limitation in Tropical Agricultural Landscapes. FORESTS 2018. [DOI: 10.3390/f9100620] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Factors that influence tropical-forest regeneration have been of interest across the tropics. We tested the degree of dispersal and establishment limitation of pioneer and non-pioneer tree species with different dispersal modes and seed sizes, using data on both seed fall and seedling establishment in primary forest, secondary forest, and pasture excluded from livestock. The study took place in a lowland tropical rain forest in southeastern Mexico. To calculate dispersal and establishment limitation, we used a density-weighted index that considers: (1) whether a seed or seedling of a given species has arrived in the sample area; and (2) the fraction of seeds or seedlings contributed by a given species relative to the total number of seeds or seedlings arriving at a sampling station. Dispersal limitation of non-pioneer species and animal-dispersed species decreased with succession. The secondary forest had less dispersal limitation for wind-dispersed pioneers than pasture, resulting in a dense aggregation of species with seeds dispersed by wind. Overall, establishment limitation differed between animal-dispersed and wind-dispersed species in the primary forest, and was negatively correlated with seed size. The low capacity of most species to arrive, germinate, and establish as seedlings in pastures slows succession back to forest. To overcome barriers to natural succession in pastures, transplanting seedlings of non-pioneer species is suggested because most of them show high dispersal and establishment limitation.
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12
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Trevor Caughlin T, Peña‐Domene M, Martínez‐Garza C. Demographic costs and benefits of natural regeneration during tropical forest restoration. Ecol Lett 2018; 22:34-44. [DOI: 10.1111/ele.13165] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 07/12/2018] [Accepted: 08/29/2018] [Indexed: 01/30/2023]
Affiliation(s)
- T. Trevor Caughlin
- Department of Biological Sciences and Program in Ecology, Evolution, and Behavior Boise State University Boise ID USA
| | - Marinés Peña‐Domene
- Centro de Investigación en Biodiversidad y Conservación Universidad Autónoma del Estado de Morelos Cuernavaca, Morelos Mexico
| | - Cristina Martínez‐Garza
- Centro de Investigación en Biodiversidad y Conservación Universidad Autónoma del Estado de Morelos Cuernavaca, Morelos Mexico
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Reid JL, Fagan ME, Zahawi RA. Positive site selection bias in meta-analyses comparing natural regeneration to active forest restoration. SCIENCE ADVANCES 2018; 4:eaas9143. [PMID: 29774239 PMCID: PMC5955619 DOI: 10.1126/sciadv.aas9143] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 03/28/2018] [Indexed: 05/07/2023]
Abstract
Several recent meta-analyses have aimed to determine whether natural regeneration is more effective at recovering tropical forests than active restoration (for example, tree planting). We reviewed this literature and found that comparisons between strategies are biased by positive site selection. Studies of natural forest regeneration are generally conducted at sites where a secondary forest was already present, whereas tree planting studies are done in a broad range of site conditions, including non-forested sites that may not have regenerated in the absence of planting. Thus, a level of success in forest regeneration is guaranteed for many studies representing natural regeneration, but not for those representing active restoration. The complexity of optimizing forest restoration is best addressed by paired experimentation at the same site, replicated across landscapes. Studies that have taken this approach reach different conclusions than those arising from meta-analyses; the results of paired experimental comparisons emphasize that natural regeneration is a highly variable process and that active restoration and natural regeneration are complementary strategies.
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Affiliation(s)
- J. Leighton Reid
- Center for Conservation and Sustainable Development, Missouri Botanical Garden, 4344 Shaw Boulevard, St. Louis, MO 63110, USA
- Corresponding author.
| | - Matthew E. Fagan
- Department of Geography and Environmental Systems, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
| | - Rakan A. Zahawi
- Lyon Arboretum, University of Hawaii at Mānoa, 3860 Mānoa Road, Honolulu, HI 96822, USA
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14
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Maréchaux I, Chave J. An individual-based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications. ECOL MONOGR 2017. [DOI: 10.1002/ecm.1271] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Isabelle Maréchaux
- CNRS; Université Toulouse 3 Paul Sabatier; ENFA; UMR5174 EDB (Laboratoire Évolution & Diversité Biologique); 118 route de Narbonne F-31062 Toulouse France
- AgroParisTech-ENGREF; 19 avenue du Maine F-75015 Paris France
| | - Jérôme Chave
- CNRS; Université Toulouse 3 Paul Sabatier; ENFA; UMR5174 EDB (Laboratoire Évolution & Diversité Biologique); 118 route de Narbonne F-31062 Toulouse France
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15
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Brudvig LA, Barak RS, Bauer JT, Caughlin TT, Laughlin DC, Larios L, Matthews JW, Stuble KL, Turley NE, Zirbel CR. Interpreting variation to advance predictive restoration science. J Appl Ecol 2017. [DOI: 10.1111/1365-2664.12938] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Lars A. Brudvig
- Department of Plant Biology and Program in Ecology, Evolutionary Biology and Behavior Michigan State University 612 Wilson Rd Room 368 East Lansing MI 48824 USA
| | - Rebecca S. Barak
- Program in Plant Biology and Conservation Northwestern University O.T. Hogan Hall Room 6‐140B 2205 Tech Drive Evanston IL 60208 USA
- Plant Science and Conservation Chicago Botanic Garden 1000 Lake Cook Road Glencoe IL 60022 USA
| | | | - T. Trevor Caughlin
- School of Forest Resources and Conservation University of Florida Gainesville FL 32601 USA
| | - Daniel C. Laughlin
- Department of Botany University of Wyoming 1000 University Ave Laramie WY 82071 USA
| | - Loralee Larios
- Department of Botany & Plant Sciences University of California 2140 Bachelor Hall Riverside CA 92521 USA
| | - Jeffrey W. Matthews
- Department of Natural Resources and Environmental Sciences University of Illinois at Urbana‐Champaign 1102 South Goodwin Avenue Urbana IL 61801 USA
| | | | - Nash E. Turley
- Department of Plant Biology and Program in Ecology, Evolutionary Biology and Behavior Michigan State University 612 Wilson Rd Room 368 East Lansing MI 48824 USA
| | - Chad R. Zirbel
- Department of Plant Biology and Program in Ecology, Evolutionary Biology and Behavior Michigan State University 612 Wilson Rd Room 368 East Lansing MI 48824 USA
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16
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Holm JA, Kueppers LM, Chambers JQ. Novel tropical forests: response to global change. THE NEW PHYTOLOGIST 2017; 213:988-992. [PMID: 28079931 DOI: 10.1111/nph.14407] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Affiliation(s)
- Jennifer A Holm
- Climate and Ecosystems Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Lara M Kueppers
- Climate and Ecosystems Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Jeffrey Q Chambers
- Climate and Ecosystems Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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17
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Caughlin TT, Graves SJ, Asner GP, van Breugel M, Hall JS, Martin RE, Ashton MS, Bohlman SA. A hyperspectral image can predict tropical tree growth rates in single-species stands. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2016; 26:2367-2373. [PMID: 27907255 DOI: 10.1002/eap.1436] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 09/01/2016] [Indexed: 06/06/2023]
Abstract
Remote sensing is increasingly needed to meet the critical demand for estimates of forest structure and composition at landscape to continental scales. Hyperspectral images can detect tree canopy properties, including species identity, leaf chemistry and disease. Tree growth rates are related to these measurable canopy properties but whether growth can be directly predicted from hyperspectral data remains unknown. We used a single hyperspectral image and light detection and ranging-derived elevation to predict growth rates for 20 tropical tree species planted in experimental plots. We asked whether a consistent relationship between spectral data and growth rates exists across all species and which spectral regions, associated with different canopy chemical and structural properties, are important for predicting growth rates. We found that a linear combination of narrowband indices and elevation is correlated with standardized growth rates across all 20 tree species (R2 = 53.70%). Although wavelengths from the entire visible-to-shortwave infrared spectrum were involved in our analysis, results point to relatively greater importance of visible and near-infrared regions for relating canopy reflectance to tree growth data. Overall, we demonstrate the potential for hyperspectral data to quantify tree demography over a much larger area than possible with field-based methods in forest inventory plots.
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Affiliation(s)
- T Trevor Caughlin
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32601, USA
| | - Sarah J Graves
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32601, USA
| | - Gregory P Asner
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, USA
| | - Michiel van Breugel
- Yale-NUS College, Singapore, Singapore
- Smithsonian Tropical Research Institute, Apartado, Panama, 0843-03092 Panama
| | - Jefferson S Hall
- Smithsonian Tropical Research Institute, Apartado, Panama, 0843-03092 Panama
| | - Roberta E Martin
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, USA
| | - Mark S Ashton
- Yale School of Forestry & Environmental Studies, New Haven, Connecticut 06511, USA
| | - Stephanie A Bohlman
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32601, USA
- Smithsonian Tropical Research Institute, Apartado, Panama, 0843-03092 Panama
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18
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Elliott S. The potential for automating assisted natural regeneration of tropical forest ecosystems. Biotropica 2016. [DOI: 10.1111/btp.12387] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Stephen Elliott
- Forest Restoration Research Unit; Chiang Mai University (FORRU-CMU); Chiang Mai Thailand
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