14 research outputs found

    Long-term thermal sensitivity of Earth’s tropical forests

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    The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

    Conservation and monitoring of wildlife in logged tropical forests: A study in Western Equatorial Africa

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    Tropical forests harbor the largest share of all terrestrial biodiversity, including 62% of all terrestrial vertebrate species. Of the remaining tropical forests, more than one-quarter are designated as logging concessions, potentially putting wildlife at risk. Forest certification systems like the Forest Stewardship Council (FSC) claim that they address threats to biodiversity, but studies have to date not resulted in robust verification of impacts of certified logging on wildlife communities due to limitations in research design and scale. Measuring impact is important for informed decision-making and data-driven policies. For this, reliable population monitoring is a prerequisite. In this thesis the general aims are to assess whether wildlife is more effectively conserved in FSC-certified logging concessions than in non-FSC concessions, and to explore how wildlife populations can best be monitored in tropical forests. I start this thesis by reviewing the applications of the three main monitoring methods to provide guidance on wildlife monitoring in tropical forests. Then, I examine the knowledge gap concerning the impacts of FSC-certified forestry, by assessing whether wildlife is more effectively conserved in FSC-certified logging concessions than in non-FSC concessions. The data were gathered by using camera traps in fourteen forestry concessions in Western Equatorial Africa. I found that FSC-certified forestry benefits mammals when compared to non-FSC forestry, with the most pronounced positive impacts for mammals weighing 10 kg and more. Next, I develop and test two wildlife monitoring methods: the use of sound for primate monitoring, and the use of soundscapes as a proxy for the overall biodiversity in a forest. Species-specific monitoring using sound covers a different species range than camera traps. However, sound monitoring requires automated classification for it to be useful. For soundscapes, interpretation of changes in the soundscape and quantification of individual species’ contributions are the main challenges, as well as interpreting the relationship between the structure of the soundscape and local landscape heterogeneity. Further development and enhancement of wildlife monitoring methods is essential for impact verification and improvement of forest certification. Improved wildlife monitoring methods may also aid the development of biodiversity credit systems, potentially yielding new revenue streams for conservation

    Water table depth modulates productivity and biomass across Amazonian forests

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    Aim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change

    Water table depth modulates productivity and biomass across Amazonian forests

    No full text
    Aim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change

    Water table depth modulates productivity and biomass across Amazonian forests

    No full text
    Aim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change

    Water table depth modulates productivity and biomass across Amazonian forests

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    International audienceAim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change

    Data from Sullivan et al. (2020) Long-term thermal sensitivity of Earth’s tropical forests. Science. DOI: 10.1126/science.aaw7578.

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    ABSTRACT: The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater rate of decline in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

    Long-term thermal sensitivity of Earth's tropical forests

    No full text
    The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per degrees C in the hottest forests (&gt;32.2 degrees C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate.</p

    Long-term thermal sensitivity of Earth’s tropical forests

    No full text
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