Sensing Forests Directly: The Power of Permanent Plots
Abstract
:1. Introduction
The Nature of Plots
2. Achievements and Contributions
3. Threats Faced
4. Tackling the Challenges, Unleashing the Opportunities
5. Recommendations and Conclusions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Forest Science Domain | Theme | Examples | Plot Criticality |
---|---|---|---|
Composition | Understanding local and regional floristic variation | Amazon community floristics and its drivers [4] | Essential: discovered with plots, unknowable without them |
Understanding floristic variation within and across biomes | Neotropical dry forest species and differentiation [5] | Essential: discovered with plots, unknowable without them | |
Diversity | Understanding variation in species richness, diversity and dominance | North-west Amazon and Andean forests are the global epicentre of arboreal diversity [6,7] | Essential: discovered with plots, unknowable without them |
Revealing 15,000 tree species in Amazonia [8] | Essential: discovered with plots, unknowable without them | ||
Predicting 73,000 tree species worldwide [9] | Essential: discovered with plots, unknowable without them | ||
Ecosystem Processes | Productivity | Primary productivity and its large-scale climate and edaphic controls [10] | Essential complement: independent, direct bottom-up measure |
Respiration, Allocation | Tracking C fluxes and photosynthate allocation within ecosystems [11] | Essential: discovered with plots, unknowable without them | |
Biomass Carbon | Estimating and Mapping biomass | Species composition controls local to continent-wide biomass via taxon-dependent wood density [12,13] | Essential: impact of species on forest AGB is discovered with plots, unknowable without them |
Global biomass mapping with radar and airborne LiDAR needs plots (diameter, volume, species) [14,15,16] | Complements: parameterise or validate Earth Observation-informed modelling | ||
Buried Carbon | Mapping carbon hotspots | Quantifying Congo Basin peatland carbon [17] | Complements: validation of EO-informed modelling |
Forest Peoples’ Cultural Influence | Understanding where and how indigenous people managed forests | Legacies of indigenous forest domestication and management in Amazonia [18] | Essential: discovered with plots, unknowable without them |
Soils | Revealing how soils drive forest ecology | Soil physical and chemical conditions control forest biomass, productivity and dynamics [19] | Essential: discovered with plots, unknowable without them |
Topography and water table depth controls on forest ecology [20] | Complements: provides long-term ecology to compare with remote-sensing | ||
Soil interactions with climate and biota | Climate-sensitive mycorrhizal impacts on global forest ecology [21] | Essential: discovered with plots, unknowable without them | |
Forest Change and Global Change Drivers | Changing forest structure and carbon | Discovering the carbon sink in mature forests [22] | Essential: discovered with plots |
Measuring change within intact forests [23,24,25] | Essential: measured with plots, largely invisible from space | ||
Changing forest dynamics | Baseline and change in Amazon forest growth, recruitment, mortality, residence times [26] | Essential: discovered with plots, largely invisible from space | |
Attributing drivers of dynamic changes | Attributing climate, CO2 and residence time controls of continental changes in biomass, growth and mortality [27] | Essential: discovered with plots, largely invisible from space | |
Changing forest diversity and composition | Thermophilization of Andean forests [28] | Essential: discovered with plots, unknowable without them | |
Xerophilization of Amazon forest composition [29] | Essential: discovered with plots, unknowable without them | ||
Impacts of extreme drought events | Drought and thermal sensitivity of forest growth, mortality, biomass [30,31] | Essential: discovered with plots, unknowable without them | |
Predicting climate-change induced future forest change | Long-term climate sensitivity of tropical forests [32] | Essential: predicted with plots, provides ground constraints for dynamic climate-vegetation models | |
Defaunation impacts on forest demography and composition | Massive changes in tree species regeneration in “empty forests” [33] | Essential: measured with plots, invisible from space | |
Making Models of Nature | Initiating and Calibrating Models | Predicting future defaunation-induced carbon losses when large vertebrate fruit-dispersers are removed [34] | Essential: plots predict and constrain models of past and future changes which are invisible from space |
Establishing robust individual- and trait-based models of forest function [35] | Essential: provides in situ traits and long-term, species- and stand-level state, dynamics and change | ||
Establishing hydraulic-models of forest function [36] | Complements: provides ecosystem state, dynamics and change | ||
Validating models | Validating DGVM estimate of CO2-induced biomass gains in forests [37] | Complements: provide actual long-term stand-level state, dynamics and change | |
Showing how variation in species’ hydraulic traits affects the long-term carbon balance of forests [38] | Essential: provides in situ trait measurements and long-term biomass growth, mortality, dynamics records | ||
Managing Forests | Characterizing key species | Determining the diversity, abundance, frequency, distribution and vulnerability of timber tree species [39] | Essential: provides long-term, species abundance, frequency, distribution, reproduction across forest domain |
Improving sustainability | Establishing sustainable logging limits and size-class thresholds for forests [40] | Essential: direct validation of which management strategies work, which don’t | |
Biodiversity Recovery | Revealing how species richness recovers fast but species composition very slowly in secondary forests [41] | Essential: long-term, ground-measured biodiversity and composition only possible via ground ID | |
Carbon Sequestration | Establishing IPCC Tier I defaults for nation states to estimate their carbon uptake in secondary forests and intact forest growth [42] | Essential: long-term, ground-measured biomass changes and forest management |
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Phillips, O.L. Sensing Forests Directly: The Power of Permanent Plots. Plants 2023, 12, 3710. https://doi.org/10.3390/plants12213710
Phillips OL. Sensing Forests Directly: The Power of Permanent Plots. Plants. 2023; 12(21):3710. https://doi.org/10.3390/plants12213710
Chicago/Turabian StylePhillips, Oliver L. 2023. "Sensing Forests Directly: The Power of Permanent Plots" Plants 12, no. 21: 3710. https://doi.org/10.3390/plants12213710