The Role of Plant-Soil Feedbacks in Shaping Regenerating Tropical Forests


Reforestation offers an effective mechanism for climate mitigation, and the global momentum for reforestation has never been stronger [1]. Ambitious goals set by the Bonn Challenge in 2011 aim to reforest 350 million hectares of degraded land by 20301. Reforestation in tropical regions offers the biggest gains in ecosystem services and biodiversity, but active reforestation is costly [2]. However, forests also naturally regenerate with no active management [3] or economic input on abandoned farmland across the tropics. Today more than 50% of remaining tropical forests are secondary and degraded3. These naturally regenerating secondary forests could be harnessed to meet large-scale reforestation targets. The problem is that natural reforestation rates and trajectories are unpredictable and therefore not integrated into national reforestation strategies [4].

Theories to explain successional change in tropical forests have focused on how shifting abiotic resources (e.g. light) drive changes in tree communities over time [5,6]. In contrast, the role of biotic factors (e.g. pathogenic and mutualistic fungi) in determining succession has largely been ignored, and yet studies have shown that interactions between plants and soil fungi play a critical role in shaping plant communities in undisturbed tropical forests [7,8]. Plant-soil feedbacks (PSF) can be driven by soil pathogens and/ or mutualistic mycorrhizal fungi [8,9] and may shape regenerating tree communities in a variety of ways. For example, host-specific pathogens may accumulate under host trees over time resulting in greater seedling mortality [10]. In this way, plant-pathogen interactions may drive ecological succession, causing shifts in species composition over time as different plant species rise and fall in abundance due to pathogen pressure. In contrast, mycorrhizal fungal associations may have a protective effect on recruiting tree seedlings; increasing growth and reducing susceptibility to drought and disease [11]. However, the composition and abundance of soil fungal communities can shift following forest disturbance [12,13] and suitable mycorrhizal fungi may be absent or present in insufficient densities to enable seedling establishment limiting recruitment of late successional tree species [11].

Changes in abiotic environment and tree communities during tropical forest succession are well described but by comparison we know very little about soil microbe communities in secondary forests or their impacts throughout succession. This project will describe microbial communities in secondary forest soils and experimentally test the role of plant soil feedbacks in shaping the composition and rate of change in tree communities over secondary succession. The project will address the following questions:
1. How do microbial communities in forest soils change after disturbance and during succession?
2. How do plant-soil feedbacks shape the speed and trajectory of succession?
3. What are the relative roles of plant-soil feedbacks and abiotic environment in determining successional change?

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Image Captions

DJI_0163.jpg – Danum Valley Conservation Area, Malaysia


We propose to utilise two existing tropical forest study sites 1. Danum Valley Conservation Area, Malaysia (DVCA; and surrounding logged forest, and 2. Barro Colorado Nature Monument, Panama (BCNM; Both sites have long-term forest monitoring plots in undisturbed forest and a chronosequence of plots in regenerating forests. Undisturbed forest in DVCA supports a highly diverse tree community with a high proportion of species that form ectomycorrhizal associations. In BCNM, undisturbed forests support a lower diversity of trees and shrubs, and very few species maintain ectomycorrhizal associations. The two sites also have different disturbance histories; in DVCA regenerating forests are recovering after selective logging, whereas in BCNM regenerating forests grow on land that was completely cleared for agriculture and pasture. At both sites we have detailed census data for species composition of tree and seedling communities, and extensive functional trait datasets.

The student will use a combination of methods to address the project aims, including analysis of existing forest census data, soil microbial analysis, seedling monitoring and transplantation experiments. Given the availability of existing data and access to field sites, there is flexibility for the student to develop the study alongside the supervisory team.

Project Timeline

Year 1

Literature review, training, planning and completion of first field season

Year 2

Laboratory work, completion of second field season, data analysis, and skills training

Year 3

Data analysis, skills training, manuscript development & thesis write-up. Presentation of results at academic conference and submission of first manuscript.

Year 3.5

Data analysis, manuscript development & thesis write-up. Submission of second manuscript.

& Skills

The PhD training will have three main components:
1. Fieldwork and experimental design. Training in the required field skills (e.g. development of greenhouse experiments, seedling census techniques, plant identification), and sampling design.
2. Laboratory analysis. Training in laboratory skills (e.g. DNA extraction from soil samples and meta-barcoding approaches). The student will attend formal training in bioinformatics and will learn extraction and sequencing techniques from working alongside collaborators in the Smithsonian Tropical research Institute Microbial Ecology Laboratory.
3. Numeracy, data analysis, ecological modeling & informatics. These skills will be gained primarily through interaction with supervisors and targeted training courses within the IAPETUS consortium (e.g. Programming and Analysis of Environmental Data in R, GIS & Remote Sensing for Environmental Managers).
4. Complementary training in transferable skills. Training in core scientific skills (data management, analysis, presentations, paper writing).

References & further reading

1. Bonn Challenge;
2. Brancalion et al. 2010. Biol. Cons 240: 108274.
3. F.A.O. Forest Resources Assessment. 2020. Food and Agriculture Organization of the United Nations, Italy, Rome.
4. Norden et al. 2015. PNAS. 112: 8013-8018.
5. Guariguata & Ostertag. 2001. For. Ecol. Manage. 148: 185-206.
6. Chazdon. 2014. Second growth. University of Chicago Press.
7. Mangan et al. 2010. Nature. 466: 752-752.
8. Comita. et al. 2010. Science. 329: 330-332.
9. Barberan et al. 2015. Ecology letters. 18: 1397-1405.
10. Augspurger. 1988. In: Pests, pathogens and plant communities. Burdon & Leather (Eds.).
11. Brearley. 2014. Biotropica. 44 (5): 637-648.
12. McGuire et al. Microbial Ecology. 69: 733-747.
13. Bachelot et al. 2016. Ecological Applications. 26: 1881-1895.

Further Information

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