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• Assessing water stress dynamics of the Amazonian rainforest through rootzone storage capacity

  2019. Chandrakant Singh (et al.). Geophysical Research Abstracts 21

  Artikel

  Extended exposure to change in rainfall patterns and permanent land-use change (LUC) have reduced the capability of the forests to withstand any external stresses, also defined as forest resilience loss. Major parts of the Amazon forest is under threat of tipping towards a treeless savanna state due to these changes in rainfall patterns and LUC. This loss in forest resilience thus also prevents the forest to return to its pre-disturbed state of the natural cycle and makes the forest more prone to tipping. Yet, this change in natural cycle is not sudden and involves a certain time lag for the forest system to respond. Previous studies determined the forest resilience, but have only considered precipitation or climatological drought to be the key influencing factor. However, neither are a direct measure of the water stress of the forest and thus do not fully reflect the hydrological dynamics underlying forest resilience loss. This study addresses the research questions: (i) do change in climatic patterns have a significant effect on forest resilience?, (ii) how does the change in rainfall patterns orLUC affect the environmental dynamics of the forest over time?, (iii) whether the quantification of rainfall, rootzone storage capacity and LUC patterns at a temporal scale better for understanding the resilience loss of the forest?

  The present study aims at understanding the complex dynamics of the resilience of the forest system using a time-series approach. Advanced remote sensing resources allow us to determine and understand patterns in the tipping behaviour at a temporal scale as well as to understand the hydrological dynamics and environmental triggers. For this, we combined precipitation data, root zone storage capacity and satellite-based forest cover and LUC data analyzed along a time-series. This is to better represent the resilience loss of the forest towards hydrological interactions and also provide a better understanding of the hydrological process for the forest tipping rather than a statistical relation. Landsat-7 data is ideal for determining the forest change, due to its regional time-series availability from early 2000’s until today. This study provides a better understanding of the hydrological dynamics of the rainforest by utilizing a time-series approach. Root zone storage capacity represents the water stored in the roots of the forest (a.k.a., water available to the forest) and it is a much better representation for assessing water stress of the Amazonian rainforest than precipitation. Thus, also a better parameter for evaluating forest resilience loss over time.

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• Rootzone storage capacity reveals drought coping strategies along rainforest-savanna transitions

  2020. Chandrakant Singh (et al.). Environmental Research Letters 15 (12)

  Artikel

  Climate change and deforestation have increased the risk of drought-induced forest-to-savanna transitions across the tropics and subtropics. However, the present understanding of forest-savanna transitions is generally focused on the influence of rainfall and fire regime changes, but does not take into account the adaptability of vegetation to droughts by utilizing subsoil moisture in a quantifiable metric. Using rootzone storage capacity (Sr), which is a novel metric to represent the vegetation's ability to utilize subsoil moisture storage and tree cover (TC), we analyze and quantify the occurrence of these forest-savanna transitions along transects in South America and Africa. We found forest-savanna transition thresholds to occur around a Sr of 550–750 mm for South America and 400–600 mm for Africa in the range of 30%–40% TC. Analysis of empirical and statistical patterns allowed us to classify the ecosystem's adaptability to droughts into four classes of drought coping strategies: lowly water-stressed forest (shallow roots, high TC), moderately water-stressed forest (investing in Sr, high TC), highly water-stressed forest (trade-off between investments in Sr and TC) and savanna-grassland regime (competitive rooting strategy, low TC). The insights from this study are useful for improved understanding of tropical eco-hydrological adaptation, drought coping strategies, and forest ecosystem regime shifts under future climate change.

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• Forest-savanna transitions: Understanding adaptation and resilience of the tropical forest ecosystems using remote sensing

  2022. Chandrakant Singh.

  Avhandling (Lic)

  Climate and deforestation-induced changes in precipitation drive tropical forest-savanna transitions. However, precipitation alone provides a superficial understanding of the underlying mechanism behind these transitions. This is because our knowledge of how vegetation responds to changes in hydroclimate is fragmented. Under a rapidly changing climate, it is increasingly important to understand forest adaptation to predict future forest-savanna transition risks. However, there are two major bottlenecks to achieving this: (i) there is no universal metric that represents forest adaptation, and (ii) at continental scale, empirical evidence to ecosystem response under changing climate is still lacking. This thesis uses remote sensing-derived root zone storage capacity – a novel metric representing the vegetation's capacity to utilise subsoil moisture storage - and above-ground tree cover structure to provide empirical evidence to ecosystems’ response under changing hydroclimate and the influence of hydroclimatic adaptation on the resilience of tropical forests. The results reveal a non-linear relationship between ecosystem’s above-ground structure and subsoil moisture storage capacity. Furthermore, the ecosystem’s capacity to utilise subsoil moisture is much more dynamic and reflective of their transient conditions under changing precipitation than above-ground structure; thereby highlighting its application as an early warning signal. Ignoring this adaptive capacity can undermine forest resilience. The result from this thesis also emphasises the applicability of remote sensing in inferring and assessing ecosystem adaptation under rapid hydroclimatic change and can assist in strengthening management and conservation efforts across the continents.

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• Hydroclimatic adaptation critical to the resilience of tropical forests

  2022. Chandrakant Singh (et al.). Global Change Biology

  Artikel

  Forest and savanna ecosystems naturally exist as alternative stable states. The maximum capacity of these ecosystems to absorb perturbations without transitioning to the other alternative stable state is referred to as ‘resilience’. Previous studies have determined the resilience of terrestrial ecosystems to hydroclimatic changes predominantly based on space-for-time substitution. This substitution assumes that the contemporary spatial frequency distribution of ecosystems’ tree cover structure holds across time. However, this assumption is problematic since ecosystem adaptation over time is ignored. Here we empirically study tropical forests’ stability and hydroclimatic adaptation dynamics by examining remotely sensed tree cover change (ΔTC; aboveground ecosystem structural change) and root zone storage capacity (S_r; buffer capacity towards water-stress) over the last two decades. We find that ecosystems at high (>75%) and low (<10%) tree cover adapt by instigating considerable subsoil investment, and therefore experience limited ΔTC—signifying stability. In contrast, unstable ecosystems at intermediate (30%–60%) tree cover are unable to exploit the same level of adaptation as stable ecosystems, thus showing considerable ΔTC. Ignoring this adaptive mechanism can underestimate the resilience of the forest ecosystems, which we find is largely underestimated in the case of the Congo rainforests. The results from this study emphasise the importance of the ecosystem's temporal dynamics and adaptation in inferring and assessing the risk of forest-savannah transitions under rapid hydroclimatic change. 

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