Active Plants, Animals & Ecology Climate, Earth & Environment

Predicting the functional resilience of tropical forests to extreme climate events through their above and below-ground functional composition

In plain English

AI plain-English summary

El Niño droughts have already killed millions of trees across tropical forests, and scientists do not know which forests will survive the next one. Current resilience models only look at what is above ground—leaves, trunks, canopy height—while ignoring the soil microbes that help trees access water and nutrients. This project fills that gap by analysing 150 permanent vegetation plots across nine tropical countries, linking the functional traits of both plants and soil microbiota to forest recovery after drought. The researchers will test whether forests with higher below- and above-ground functional diversity, including mycorrhizal fungi and nitrogen-fixing bacteria, bounce back faster. If successful, the project will produce the first pantropical map of forest functional resilience, built from satellite data calibrated against real ground measurements. This would allow conservation agencies and land managers to identify which forests are most vulnerable to climate-driven drought and prioritise protection accordingly. The work also advances the fundamental science of ecological remote sensing, a field that could eventually underpin early-warning systems for ecosystem collapse—though that application remains years away.

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Some of the most pressing questions in ecology focus on how communities of organisms respond to global environmental change and how biodiversity influences ecosystem resilience to such change. Biodiversity approaches for understanding ecosystem resilience have a long-standing history in ecosystem ecology and, more recently, have been extended to include ecosystem stability and productivity approaches. Nevertheless, most studies have concentrated on small spatial scales in low-diversity ecosystems and restricted to aboveground functions. This narrow focus has led to the oversight of the intricate interplay between belowground microbiota and aboveground vegetation functional composition, neglecting the critical synergy that confers resilience to the ecosystem. By analysing the impacts of El Niño extreme droughts in 150 permanent vegetation plots across nine tropical countries, this project addresses the core challenge of comprehensively quantifying how tropical forest resilience to a changing climate depends on below- (soil microbiota) and above-ground (vegetation) functional composition. To date, we simply do not have the appropriate data to address this challenge and to quantify and explain these patterns at scale. Therefore, collecting and analysing such data under a common methodology and functional composition approach is the core aim of this proposal. This project also has the potential to yield major advances in a novel and powerful field of ecology, 'ecological remote sensing', which can reveal fundamental new insights into the resilience of tropical forest ecosystems. Here, we focus on responding to the overarching question: How does above and below-ground functional composition influence tropical forest resilience to extreme drought events? We hypothesise that: i) the functional composition of plants and soil microbiota will be influenced by environmental conditions selecting for specific traits adapted to the local environment (objectives O1 and O2); ii) forest resilience will be largely driven by the forest position across water availability gradients (O3); iii) tropical forests with greater below and above-ground functional diversity, coupled with soil microbiota with proficient nutrient cycling and facilitation of nutrient acquisition by plants (e.g., mycorrhizae/nitrogen-fixing bacteria), will demonstrate higher resilience (O3); iv) Spectral and structural remote sensing can accurately map forest functional resilience at scale (O4). Objectives: O1) Uncover whether responses to droughts bring parallel changes in plant taxonomic and functional composition along environmental gradients; O2) Measure the strength of the, yet unknown, plant-soil microbiota functional composition relationship across tropical forests; O3) Assess and quantify the dependence of forest resilience to extreme droughts and plant and soil microbiota functional composition; O4) Map the tropical forest resilience to extreme droughts based on above and belowground functional composition. Potential Applications and Benefits: Scientific Advancements: We will create the first pantropical model of soil microbiota composition, the baseline of the plant-soil microbiota functional composition, and will show how this impacts forest resilience. This can be used in further research, such as ecosystem models and macroecological functional analyses. We will advance the field of ecological remote sensing by providing a novel methodology to model forest functional resilience.

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Researchers

Erika Berenguer (Co-Investigator)Jesús Aguirre Gutiérrez (Principal Investigator)Laura M. Suz (Co-Investigator)Yadvinder Malhi (Co-Investigator)

Related Research

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NSFDEB-NERC: Understanding drought and post-drought legacy effects in tropical forest
Tropical forests responses to a changing climate: a quest at the interface between trait-based ecology, forest dynamics and remote sensing
Explaining niche separation in tropical forests: feedbacks between root-fungal symbioses and soil phosphorus partitioning
Integrating and predicting responses of natural systems to disturbances
Uniting Forest Inventory and Remote Sensing Data to Assess Forest Composition and Structure in Tropical Mountain Regions

Original classification

Research and Innovation

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