ORCID Profile
0000-0002-8308-5307
Current Organisations
University of Exeter
,
University of Oxford
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Publisher: Routledge
Date: 16-10-2015
Publisher: Wiley
Date: 21-02-2018
DOI: 10.1111/GCB.14068
Abstract: Tropical forests play a major role in the carbon cycle of the terrestrial biosphere. Recent field studies have provided detailed descriptions of the carbon cycle of mature tropical forests, but logged or secondary forests have received much less attention. Here, we report the first measures of total net primary productivity (NPP) and its allocation along a disturbance gradient from old-growth forests to moderately and heavily logged forests in Malaysian Borneo. We measured the main NPP components (woody, fine root and canopy NPP) in old-growth (n = 6) and logged (n = 5) 1 ha forest plots. Overall, the total NPP did not differ between old-growth and logged forest (13.5 ± 0.5 and 15.7 ± 1.5 Mg C ha
Publisher: Wiley
Date: 05-12-2021
Abstract: Tropical forests are the most productive terrestrial ecosystems, fixing over 40 Pg of carbon from the atmosphere each year. A substantial portion of this carbon is allocated below‐ground to roots and root‐associated micro‐organisms. However, there have been very few empirical studies on the dynamics of this below ground transfer, especially in tropical forests where carbon allocation processes are influenced by high plant species ersity. We used a whole‐stand girdling experiment to halt the below‐ground transfer of recent photosynthates in a lowland tropical forest in Borneo. By girdling 209 large trees in a 0.48 ha plot, we determined: (a) the contribution of recent photosynthate to root‐rhizosphere respiration and (b) the relationships among the disruption of this below‐ground carbon supply, tree species composition and mortality. Mortality of the 209 trees was 62% after 370 days, with large variation among species and particularly high mortality within the Dipterocarpaceae (99%) and Fagaceae (100%) families. We also observed a higher risk of mortality following girdling for species with lower wood density. Soil CO 2 emissions declined markedly (36 ± 5%) over ~50 days following girdling in three of six monitored subplots. In the other three subplots there was either a marginal decline or no response of soil CO 2 emissions to girdling. The decrease in soil CO 2 efflux was larger in subplots with dominance of Dipterocarpaceae. Synthesis . Our results indicate high spatial variation in the coupling of below‐ground carbon allocation and root‐rhizosphere respiration in this tropical forest, with a closer coupling in forest dominated by Dipterocarpaceae. Our findings highlight the implications of tree species composition of tropical forests in affecting the dynamics of below‐ground carbon transfer and its release to the atmosphere.
Publisher: Cold Spring Harbor Laboratory
Date: 18-12-2022
DOI: 10.1101/2022.12.15.520573
Abstract: Tropical forests are threatened by degradation and deforestation but the consequences for these ecosystems are poorly understood, particularly at the landscape scale. We present the most extensive ecosystem analysis to date of the impacts of logging and conversion of tropical forest to oil palm from a large-scale study in Borneo, synthesizing responses from 79 variables categorized into four hierarchical ecological ‘levels’: 1) structure and environment, 2) species traits, 3) bio ersity and 4) ecosystem functions. Variables at the lowest levels that were directly impacted by the physical processes of timber extraction, such as soil characteristics, were sensitive to even moderate amounts of logging, whereas bio ersity and ecosystem functions proved remarkably resilient to logging in many cases, but were more affected by conversion to oil palm plantation. Logging tropical forest mostly impacts structure while bio ersity and functions are more vulnerable to habitat conversion
Publisher: Wiley
Date: 31-05-2021
DOI: 10.1111/GCB.15677
Abstract: Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also h ered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old‐growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi‐deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia ( n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water‐stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.
Publisher: Elsevier BV
Date: 12-2014
Publisher: Wiley
Date: 06-2021
Abstract: Forest degradation through logging is pervasive throughout the world's tropical forests, leading to changes in the three‐dimensional canopy structure that have profound consequences for wildlife, microclimate and ecosystem functioning. Quantifying these structural changes is fundamental to understanding the impact of degradation, but is challenging in dense, structurally complex forest canopies. We exploited discrete‐return airborne LiDAR surveys across a gradient of logging intensity in Sabah, Malaysian Borneo, and assessed how selective logging had affected canopy structure (Plant Area Index, PAI, and its vertical distribution within the canopy). LiDAR products compared well to independent, analogue models of canopy structure produced from detailed ground‐based inventories undertaken in forest plots, demonstrating the potential for airborne LiDAR to quantify the structural impacts of forest degradation at landscape scale, even in some of the world's tallest and most structurally complex tropical forests. Plant Area Index estimates across the plot network exhibited a strong linear relationship with stem basal area ( R 2 = 0.95). After at least 11–14 years of recovery, PAI was ~28% lower in moderately logged plots and ~52% lower in heavily logged plots than that in old‐growth forest plots. These reductions in PAI were associated with near‐complete lack of trees ‐m tall, which had not been fully compensated for by increasing plant area lower in the canopy. This structural change drives a marked reduction in the ersity of canopy environments, with the deep, dark understorey conditions characteristic of old‐growth forests far less prevalent in logged sites. Full canopy recovery is likely to take decades. Synthesis and applications . Effective management and restoration of tropical forests requires detailed monitoring of the forest and its environment. We demonstrate that airborne LiDAR can effectively map the canopy architecture of the complex tropical forests of Borneo, capturing the three‐dimensional impact of degradation on canopy structure at landscape scales, therefore facilitating efforts to restore and conserve these ecosystems.
Publisher: Copernicus GmbH
Date: 22-06-2018
Abstract: Abstract. Borneo contains some of the world's most bio erse and carbon-dense tropical forest, but this 750 000 km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognizing the ecosystem services they provide, including their ability to store and sequester carbon. Airborne laser scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into statewide assessments of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen new regional models need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rainforests of Sabah on the island of Borneo, we develop a simple yet general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbon stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalized and effective approach for mapping forest carbon stocks in Borneo and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.
Publisher: Frontiers Media SA
Date: 26-10-2018
Publisher: Wiley
Date: 17-12-2019
DOI: 10.1111/GCB.14903
Abstract: Logging, pervasive across the lowland tropics, affects millions of hectares of forest, yet its influence on nutrient cycling remains poorly understood. One hypothesis is that logging influences phosphorus (P) cycling, because this scarce nutrient is removed in extracted timber and eroded soil, leading to shifts in ecosystem functioning and community composition. However, testing this is challenging because P varies within landscapes as a function of geology, topography and climate. Superimposed upon these trends are compositional changes in logged forests, with species with more acquisitive traits, characterized by higher foliar P concentrations, more dominant. It is difficult to resolve these patterns using traditional field approaches alone. Here, we use airborne light detection and ranging‐guided hyperspectral imagery to map foliar nutrient (i.e. P, nitrogen [N]) concentrations, calibrated using field measured traits, over 400 km 2 of northeastern Borneo, including a landscape‐level disturbance gradient spanning old‐growth to repeatedly logged forests. The maps reveal that canopy foliar P and N concentrations decrease with elevation. These relationships were not identified using traditional field measurements of leaf and soil nutrients. After controlling for topography, canopy foliar nutrient concentrations were lower in logged forest than in old‐growth areas, reflecting decreased nutrient availability. However, foliar nutrient concentrations and specific leaf area were greatest in relatively short patches in logged areas, reflecting a shift in composition to pioneer species with acquisitive traits. N:P ratio increased in logged forest, suggesting reduced soil P availability through disturbance. Through the first landscape scale assessment of how functional leaf traits change in response to logging, we find that differences from old‐growth forest become more pronounced as logged forests increase in stature over time, suggesting exacerbated phosphorus limitation as forests recover.
Publisher: Elsevier BV
Date: 2015
Publisher: Wiley
Date: 17-05-2019
DOI: 10.1002/ECY.2739
Abstract: By feeding on plant tissue, insect herbivores can change several characteristics of their hosts. These changes have the potential to alter the quality of the plant for other herbivore species, potentially altering the structure of the community of species attacking the plant at a later point in time. We tested whether herbivory early in the season changes host plant performance, polyphenol chemistry, and the community structure of sessile herbivores later in the season. We experimentally manipulated densities of early-season moth caterpillars on a set of young oak trees and measured tree growth, reproduction, leaf chemistry, and the abundance and community composition of leafmining and galling species later in the season. The experimental manipulations of early-season herbivores did not affect late-season leaf chemistry or tree performance. Early-season herbivores had a weak negative effect on the abundance of gallers and a positive, tree-dependent effect on the overall ersity of late-season sessile herbivores. The chemical composition of leaves covaried with the species composition of the late-season leafmining and galling community. Both the chemical composition of the host tree and the late-season insect community structure were strongly affected by the growth location of the tree. Our results suggest that plant-mediated indirect effects between herbivores might play a limited role in this system, whereas the underlying variation in plant chemistry is an important factor structuring the associated insect community. Our results emphasize that factors other than prior herbivory can be important determinants of plant chemistry and the community composition of herbivores.
Publisher: IOP Publishing
Date: 29-07-2019
Abstract: El Niño events generate periods of relatively low precipitation, low cloud cover and high temperature over the rainforests of Southeast Asia, but their impact on tree physiology remains poorly understood. Here we use remote sensing and functional trait approaches—commonly used to understand plant acclimation to environmental fluctuations—to evaluate rainforest responses to an El Niño event at a site in northern Borneo. Spaceborne measurements (i.e. normalised difference vegetation index calculated from Moderate Resolution Imaging Spectroradiometer data) show the rainforest canopy greened throughout 2015, coinciding with a strengthening of the El Niño event in Sabah, Malaysia, then lost greenness in early 2016, when the El Niño was at its peak. Leaf chemical and structural traits measured for mature leaves of 65 species (104 branches from 99 tree canopies), during and after this El Niño event revealed that chlorophyll and carotenoid concentrations were 35% higher in mid 2015 than in mid 2016. Foliar concentrations of the nutrients N, P, K and Mg did not vary, suggesting the mineralisation and transportation processes were unaffected by the El Niño event. Leaves contained more phenolics, tannins and cellulose but less Ca and lignin during the El Niño event, with concentration shifts varying strongly among species. These changes in functional traits were also apparent in hyperspectral reflectance data collected using a field spectrometer, particularly in the shortwave infrared region. Leaf-level acclimation and leaf turnover could have driven the trait changes observed. We argue that trees were not water limited in the initial phase of the El Niño event, and responded by flushing new leaves, seen in the canopy greening trend and higher pigment concentrations (associated with young leaves) we argue that high evaporative demand and depleted soil water eventually caused leaves to drop in 2016. However, further studies are needed to confirm these ideas. Time-series of vegetation dynamics obtained from space can only be understood if changes in functional traits, as well as the quantity of leaves in canopies, are monitored on the ground.
Publisher: MDPI AG
Date: 07-2023
DOI: 10.3390/RS15133374
Abstract: In intelligent traffic control systems, the features extracted by loop detectors are insufficient to accurately impute missing data. Most of the existing imputation methods use only these extracted features, which leads to the construction of data models that cannot fulfill the required accuracy. This deficiency is the main motivation to propose an enrichment imputation method for loop detectors namely EIM-LD, in which the imputation accuracy is increased for different missing patterns and ratios by introducing a data enrichment technique using statistical multi-class labeling. It first enriches the clean data by adding a statistical multi-class label, including C1…Cn classes. Then, the class of s les in the missed-volume data is labeled using the best data model constructed from the labeled clean data by five different classifiers. Experts of the traffic control department in Isfahan city determined classes of the statistical multi-class label for n = 5 (class labels), and we also developed subclass labels (n = 20) since the number of s les in the subclass labels was sufficient. Next, the enriched data are ided into n datasets, each of them is imputed independently using various imputation methods, and their results are finally merged. To evaluate the impact of using the proposed method, the original data, including missing volumes, are first imputed without our enrichment method. Then, the proposed method’s accuracy is evaluated by considering two class labels and subclass labels. The experimental and statistical results prove that the proposed EIM-LD method can enrich the real data collected by loop detectors, by which the comparative imputation methods construct a more accurate data model. In addition, using subclass labels further enhances the imputation method’s accuracy.
Publisher: Wiley
Date: 26-07-2018
DOI: 10.1111/NPH.15338
Abstract: Insect herbivores cause substantial changes in the leaves they attack, but their effects on the ecophysiology of neighbouring, nondamaged leaves have never been quantified in natural canopies. We studied how winter moth (Operophtera brumata), a common herbivore in temperate forests, affects the photosynthetic and isoprene emission rates of its host plant, the pedunculate oak (Quercus robur). Through a manipulative experiment, we measured leaves on shoots damaged by caterpillars or mechanically by cutting, or left completely intact. To quantify the effects at the canopy scale, we surveyed the extent and patterns of leaf area loss in the canopy. Herbivory reduced photosynthesis both in damaged leaves and in their intact neighbours. Isoprene emission rates significantly increased after mechanical leaf damage. When scaled up to canopy-level, herbivory reduced photosynthesis by 48 ± 10%. The indirect effects of herbivory on photosynthesis in undamaged leaves (40%) were much more important than the direct effects of leaf area loss (6%). If widespread across other plant-herbivore systems, these findings suggest that insect herbivory has major and previously underappreciated influences in modifying ecosystem carbon cycling, with potential effects on atmospheric chemistry.
Publisher: Wiley
Date: 06-2013
DOI: 10.1890/11-2059.1
Abstract: A typical way to quantify aboveground carbon in forests is to measure tree diameters and use species-specific allometric equations to estimate biomass and carbon stocks. Using "citizen scientists" to collect data that are usually time-consuming and labor-intensive can play a valuable role in ecological research. However, data validation, such as establishing the s ling error in volunteer measurements, is a crucial, but little studied, part of utilizing citizen science data. The aims of this study were to (1) evaluate the quality of tree diameter and height measurements carried out by volunteers compared to expert scientists and (2) estimate how sensitive carbon stock estimates are to these measurement s ling errors. Using all diameter data measured with a diameter tape, the volunteer mean s ling error (difference between repeated measurements of the same stem) was 9.9 mm, and the expert s ling error was 1.8 mm. Excluding those s ling errors > 1 cm, the mean s ling errors were 2.3 mm (volunteers) and 1.4 mm (experts) (this excluded 14% [volunteer] and 3% [expert] of the data). The s ling error in diameter measurements had a small effect on the biomass estimates of the plots: a volunteer (expert) diameter s ling error of 2.3 mm (1.4 mm) translated into 1.7% (0.9%) change in the biomass estimates calculated from species-specific allometric equations based upon diameter. Height s ling error had a dependent relationship with tree height. Including height measurements in biomass calculations compounded the s ling error markedly the impact of volunteer s ling error on biomass estimates was +/- 15%, and the expert range was +/- 9%. Using dendrometer bands, used to measure growth rates, we calculated that the volunteer (vs. expert) s ling error was 0.6 mm (vs. 0.3 mm), which is equivalent to a difference in carbon storage of +/- 0.011 kg C/yr (vs. +/- 0.002 kg C/yr) per stem. Using a citizen science model for monitoring carbon stocks not only has benefits in educating and engaging the public in science, but as demonstrated here, can also provide accurate estimates of biomass or forest carbon stocks.
Publisher: The Royal Society
Date: 08-10-2018
Abstract: Meteorological extreme events such as El Niño events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high–temporal resolution dataset (for 1–13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPP stem ) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr −1 , with an interannual range 1.96–2.26 Pg C yr −1 between 1996–2016, and with the sharpest declines during the strong El Niño events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Niño–associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation ( r = −0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation. This article is part of the discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
Publisher: Wiley
Date: 20-09-2018
DOI: 10.1111/NPH.15444
Abstract: Plant functional traits regulate ecosystem functions but little is known about how co-occurring gradients of land use and edaphic conditions influence their expression. We test how gradients of logging disturbance and soil properties relate to community-weighted mean traits in logged and old-growth tropical forests in Borneo. We studied 32 physical, chemical and physiological traits from 284 tree species in eight 1 ha plots and measured long-term soil nutrient supplies and plant-available nutrients. Logged plots had greater values for traits that drive carbon capture and growth, whilst old-growth forests had greater values for structural and persistence traits. Although disturbance was the primary driver of trait expression, soil nutrients explained a statistically independent axis of variation linked to leaf size and nutrient concentration. Soil characteristics influenced trait expression via nutrient availability, nutrient pools, and pH. Our finding, that traits have dissimilar responses to land use and soil resource availability, provides robust evidence for the need to consider the abiotic context of logging when predicting plant functional ersity across human-modified tropical forests. The detection of two independent axes was facilitated by the measurement of many more functional traits than have been examined in previous studies.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Terhi Riutta.