ORCID Profile
0000-0003-3400-8601
Current Organisations
University of Adelaide
,
University of New South Wales
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Wiley
Date: 19-06-2017
DOI: 10.1002/EAP.1557
Abstract: Soil carbon sequestration in agroecosystems could play a key role in climate change mitigation but will require accurate predictions of soil organic carbon (SOC) stocks over spatial scales relevant to land management. Spatial variation in underlying drivers of SOC, such as plant productivity and soil mineralogy, complicates these predictions. Recent advances in the availability of remotely sensed data make it practical to generate multidecadal time series of vegetation indices with high spatial resolution and coverage. However, the utility of such data largely is unknown, only having been tested with shorter (e.g., 1-2 yr) data summaries. Across a 2,000 ha subtropical grassland, we found that a long time series (28 yr) of a vegetation index (Enhanced Vegetation Index EVI) derived from the Landsat 5 satellite significantly enhanced prediction of spatially varying SOC pools, while a short summary (2 yr) was an ineffective predictor. EVI was the best predictor for surface SOC (0-5 cm depth) and total measured SOC stocks (0-15 cm). The optimum models for SOC in the upper soil layer combined EVI records with elevation and calcium concentration, while deeper SOC was more strongly associated with calcium availability. We demonstrate how data from the open access Landsat archive can predict SOC stocks, a key ecosystem metric, and illustrate the rich variety of analytical approaches that can be applied to long time series of remotely sensed greenness. Overall, our results showed that SOC pools were closely coupled to EVI in this ecosystem, demonstrating that maintenance of higher average green leaf area is correlated with higher SOC. The strong associations of vegetation greenness and calcium concentration with SOC suggest that the ability to sequester additional SOC likely will rely on strategic management of pasture vegetation and soil fertility.
Publisher: Wiley
Date: 15-11-2016
DOI: 10.1002/RSE2.33
Publisher: Elsevier BV
Date: 04-2019
Publisher: Wiley
Date: 12-2014
DOI: 10.3732/AJB.1400412
Abstract: • In ecosystems maintained by low-intensity surface fires, tree bark thickness is a determinant of fire-survival because it protects underlying tissues from heat damage. However, it has been unclear whether relatively thick bark i S: maintained at all heights or only near the ground where damage is most likely.• We studied six Quercus species from the red and white clades, with three species characteristic of fire-maintained savannas and three species characteristic of forests with infrequent fire. Inner and outer bark (secondary phloem and rhytidome, respectively) thicknesses were measured at intervals from 10 to 300 cm above the ground. We used linear mixed-effects models to test for relationships among height, habitat, and clade on relative thickness (stem proportion) of total, inner, and outer bark. Bark moisture and tissue density were measured for each species at 10 cm.• Absolute and relative total bark thickness declined with height, with no difference in height-related changes between habitat groups. Relative outer bark thickness showed a height-by-habitat interaction. There was a clade effect on relative thickness, but no interaction with height. Moisture contents were higher in inner than outer bark, and red oaks had denser bark than white oaks, but neither trait differed by habitat.• Quercus species characteristic of fire-prone habitats invest more in outer bark near the ground where heat damage to outer tissues is most likely. Future investigations of bark should consider the height at which measurements are made and distinguish between inner and outer bark.
Publisher: Informa UK Limited
Date: 04-07-2015
Publisher: Elsevier BV
Date: 12-2011
Publisher: Wiley
Date: 28-11-2021
DOI: 10.1111/GCB.15982
Abstract: A better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long‐term climate averages (mean climate) drive spatial variations in species’ baseline growth rates, whereas deviations from these averages over time (anomalies) can create growth variation around the local baseline. However, the rarity of long‐term tree census data spanning climatic gradients has so far limited our understanding of their respective role, especially in tropical systems. Furthermore, tree growth sensitivity to climate is likely to vary widely among species, and the ecological strategies underlying these differences remain poorly understood. Here, we utilize an exceptional dataset of 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how multiannual tree growth responds to both climate means and anomalies, and how species’ functional traits mediate these growth responses to climate. We show that anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast‐growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both climate means and anomalies. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests and that species traits can provide insights into understanding these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.
Publisher: Wiley
Date: 21-10-2018
DOI: 10.1111/GCB.14457
Abstract: Amazon forests account for ~25% of global land biomass and tropical tree species. In these forests, windthrows (i.e., snapped and uprooted trees) are a major natural disturbance, but the rates and mechanisms of recovery are not known. To provide a predictive framework for understanding the effects of windthrows on forest structure and functional composition (DBH ≥10 cm), we quantified biomass recovery as a function of windthrow severity (i.e., fraction of windthrow tree mortality on Landsat pixels, ranging from 0%-70%) and time since disturbance for terra-firme forests in the Central Amazon. Forest monitoring allowed insights into the processes and mechanisms driving the net biomass change (i.e., increment minus loss) and shifts in functional composition. Windthrown areas recovering for between 4-27 years had biomass stocks as low as 65.2-91.7 Mg/ha or 23%-38% of those in nearby undisturbed forests (~255.6 Mg/ha, all sites). Even low windthrow severities (4%-20% tree mortality) caused decadal changes in biomass stocks and structure. While rates of biomass increment in recovering vegetation were nearly double (6.3 ± 1.4 Mg ha
Publisher: Wiley
Date: 04-03-2019
DOI: 10.1111/ELE.13243
Abstract: Climatic changes have profound effects on the distribution of bio ersity, but untangling the links between climatic change and ecosystem functioning is challenging, particularly in high ersity systems such as tropical forests. Tropical forests may also show different responses to a changing climate, with baseline climatic conditions potentially inducing differences in the strength and timing of responses to droughts. Trait-based approaches provide an opportunity to link functional composition, ecosystem function and environmental changes. We demonstrate the power of such approaches by presenting a novel analysis of long-term responses of different tropical forest to climatic changes along a rainfall gradient. We explore how key ecosystem's biogeochemical properties have shifted over time as a consequence of multi-decadal drying. Notably, we find that drier tropical forests have increased their deciduous species abundance and generally changed more functionally than forests growing in wetter conditions, suggesting an enhanced ability to adapt ecologically to a drying environment.
Publisher: Wiley
Date: 11-05-2023
DOI: 10.1111/AEC.13343
Abstract: In 2015/16, a strong El Niño event caused anomalously high temperatures and reduced precipitation resulting in Pantropical drought‐induced diebacks and wildfires. Although many studies have documented the El Niño impacts on tropical forests, little we know about its effects on tropical grasslands. Here, we investigated plant drought responses during and after the 2015/16 El Niño event (Jun 2016 to Aug 2017) in 12 species with contrasting drought strategies (tolerance, avoidance and escape) in a Brazilian tropical montane grassland. We tested if (1) the El Niño event induced meteorological drought anomalies, (2) the atmospheric and/or soil drought led to plant water stress and (3) plants showed signs of drought recovery. In contrast to other tropical areas, we found that the 2015/16 El Niño event did not strongly affect precipitation in our study site. However, it increased air temperature and vapour pressure deficit, thus pushing all grassland species, even the most drought‐tolerant ones, beyond their hydraulic safety margins during the dry season. Most species showed signs of drought recovery, returning to positive hydraulic margins in the wet season after the El Niño. However, the finding that all evaluated species, regardless of their drought‐response strategy, are already operating close to their hydraulic safe thresholds for stomatal closure and turgor loss suggests that this cool–humid tropical montane grassland is especially vulnerable to meteorological extremes exacerbated by the additive effects of El Niño and climate change.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-8249
Abstract: Australia is the driest inhabited continent. Annual rainfall is low and is accompanied by marked inter-annual variability, leading to multi-year droughts. n particular, & #8203 South-East Australia& #8203 & #8203 has recently experienced two of the worst droughts in the historical record (2000& #8211 and 2017& #8211 ). Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy-dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344& #8211 mm yr-1). We carried out three experiments: applying CABLE to the recent drought a theoretical future drier drought (20% reduction in rainfall) and a future drier drought (20% reduction in rainfall) with a doubling of atmospheric carbon dioxide (CO2). The drought's severity was highlighted as at least 25% of their distribution ranges, and 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within species& #8217 ranges, but we also pinpointed resilience in species found in predominantly semiarid regions. The importance of the role of CO2 in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of in idual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.
Publisher: Wiley
Date: 02-08-2021
DOI: 10.1002/CLI2.11
Abstract: This study aims to investigate local‐scale meteorological conditions associated with large fires in Brazil during recent decades. We assess whether there are large fire types with preceding predictors. Our results show that large fires, defined with a threshold of a daily burned area th percentile of the historical record, mainly occur in August and September in Brazil, and Amazônia and Cerrado experience much higher numbers of large fires than the other biomes. There are two large fire types that have robust meteorological signatures: (1) a wind driven type, characterized by peak wind speed on the day of the fire, and anomalously high wind speed a few (∼3) days before and after the fire and (2) a Hot‐Drought driven type, characterized by anomalously high temperature, low relative humidity, and consistent drought conditions indicated by anomalously high fuel aridity starting as far back as 5 months prior to the fires. A third one is characterized by no anomalous meteorological conditions. The wind driven type most frequently occurs in southern and southeastern Amazônia, Pantanal, and western and northern‐to‐central Cerrado, with some occurrences over the western Caatinga region bordering Cerrado, southern Cerrado, and southern Mata Atlântica whereas the Hot‐Drought driven type most frequently occurs in southern and southeastern Amazônia, Pantanal and western and northern‐to‐central Cerrado, with some occurrences over the western Caatinga region bordering Cerrado, southern Cerrado, central‐to‐southern Mata Atlântica, and a few occurrences over Northern Brazil where the Amazônia meets Roraima. Southern and southeastern Amazônia, Pantanal and western and northern‐to‐central Cerrado are the major large fire prone regions. Our results highlight that understanding the temporal and spatial variability of the meteorological conditions associated with large fires is essential for developing spatially explicit forecasting, and future projections of large fire hazards under climate change in Brazil, in particular the Hot‐Drought driven type.
Publisher: The Royal Society
Date: 08-10-2018
Abstract: To understand the impacts of extreme climate events, it is first necessary to understand the spatio-temporal characteristics of the event. Gridded climate products are frequently used to describe climate patterns but have been shown to perform poorly over data-sparse regions such as tropical forests. Often, they are uncritically employed in a wide range of studies linking tropical forest processes to large-scale climate variability. Here, we conduct an inter-comparison and assessment of near-surface air temperature fields supplied by four state-of-the-art reanalysis products, along with precipitation estimates supplied by four merged satellite-gauge rainfall products. Firstly, spatio-temporal patterns of temperature and precipitation anomalies during the 2015–2016 El Niño are shown for each product to characterize the impact of the El Niño on the tropical forest biomes of Equatorial Africa, Southeast Asia and South America. Using meteorological station data, a two-stage assessment is then conducted to determine which products most reliably model tropical climates during the 2015–2016 El Niño, and which perform best over the longer-term satellite observation period (1980–2016). Results suggest that eastern Amazonia, parts of the Congo Basin and mainland Southeast Asia all experienced significant monthly mean temperature anomalies during the El Niño, while northeastern Amazonia, eastern Borneo and southern New Guinea experienced significant precipitation deficits. Our results suggest ERA-Interim and MERRA2 are the most reliable air temperature datasets, while TRMM 3B42 V7 and CHIRPS v2.0 are the best-performing rainfall datasets. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
Publisher: Copernicus GmbH
Date: 05-06-2023
DOI: 10.5194/EGUSPHERE-2023-1057
Abstract: Abstract. We develop high resolution (1 km) estimates of Gross Primary Productivity (GPP), Ecosystem Respiration (ER) and Net Ecosystem Exchange (NEE) over the Australian continent for the period January 2003 to June 2022 by empirical upscaling of flux tower measurements. We compare our estimates with nine other products that cover the three broad categories that define current methods for estimating the terrestrial carbon cycle and assess if consiliences between datasets can point to the correct dynamics of Australia’s carbon cycle. Our results indicate that regional empirical upscaling greatly improves upon the existing global empirical upscaling efforts, outperforms process-based models, and agrees much better with the dynamics of CO2 flux over Australia as estimated by two regional atmospheric inversions. Our nearly 20-year estimates of terrestrial carbon fluxes revealed Australia is a strong net carbon sink of -0.44 (IQR=0.42) PgC/year on-average, with an inter-annual variability of 0.18 PgC/year and an average seasonal litude of 0.85 PgC/yr. Annual mean carbon uptake estimated from other methods ranged considerably, while carbon flux anomalies showed much better agreement between methods. NEE anomalies were predominately driven by cumulative rainfall deficits and surpluses, resulting in larger anomalous responses from GPP over ER. In contrast, we show that the long-term average seasonal cycle is dictated more by the variability in ER than GPP, resulting in peak carbon uptake typically occurring during the cooler, drier Austral autumn, and winter months. This new estimate of Australia’s terrestrial carbon cycle provides a benchmark for assessment against Land Surface Model simulations, and a means for monitoring of Australia’s terrestrial carbon cycle at an unprecedented high-resolution. We call this new estimate of Australia’s terrestrial carbon cycle, “AusEFlux” (Australian Empirical Fluxes).
Publisher: IOP Publishing
Date: 07-2019
Abstract: Smallholder farmers dependent on rain-fed agriculture are particularly vulnerable to extreme climate events and, therefore, it is necessary to identify adaptive measures that would increase farmer resilience to these shocks. The management options in a low-input system, like forest coffee ( Coffea arabica ), are limited and there are several factors out of farmers’ control driving their vulnerability to changing climatic conditions. These can relate to social structures and landscape factors, which can interact to reduce farmers’ adaptive capacity, creating a state of contextual vulnerability. We explored the potential synergies of this interaction across elevation, patch area and shade management gradients for smallholder coffee farms around the UNESCO Yayu Coffee Forest Biosphere Reserve in Ethiopia before, during and immediately following the 2015/16 El Niño. We documented a dramatic collapse in coffee yields across all farms, resulting in coffee incomes 29.5% ± 18.0% and 19.5% ± 10.0% of 2014 incomes in 2015 and 2016, respectively. We identified farms at elevations between 1500 and 1600 m with canopy openness between 40% and 45% as being consistently low yielding over our study period. We found these farmers had the highest rates of income ersification and, therefore, were already exhibiting adaptive capacity. Farmers with the largest income losses were spatially concentrated between 1600 and 1700 m, located in larger patch areas with lower canopy openness. Farmers at this elevation have access to poor infrastructure, restrictions on shade management and reported higher dependence on income from coffee, indicating an interaction of biotic and social factors exacerbating their vulnerability. Unfortunately, due to a nationally declared state of emergency, we were unable to survey farmers on the adaptive measures they undertook therefore, we are limited in assessing their resilience. However, we do show the importance of considering both biotically and socially-mediated influences for assessing smallholder vulnerability, particularly barriers to ersifying incomes.
Publisher: Springer Science and Business Media LLC
Date: 08-2020
Publisher: Elsevier BV
Date: 05-2010
Publisher: Copernicus GmbH
Date: 05-08-2022
Abstract: Abstract. The total demand for and uptake of nutrients by vegetation is rarely quantified or compared across vegetation types. Here, we describe different nutrient use and allocation strategies in neotropical savanna (cerrado) and transitional forest (cerradão) tree communities composed of different species, report leaf nutrient resorption and calculate ecosystem-level nutrient use efficiency. We couple net primary productivity (NPP) estimates with nutrient stoichiometry to quantify nutrient demand and nutrient flows at the whole-stand scale for different components of vegetation biomass. Species from the two vegetation communities showed similar mean nutrient concentrations and nutrient resorption efficiency, except for wood P concentration that was fourfold higher in cerrado than cerradão species. The cerradão showed higher canopy NPP, while fine roots and wood NPP were similar for the two vegetation types. Nutrient requirement in the two vegetation types was dominated by the demands of the canopy, with canopy resorption generally contributing more than 50 % of the total canopy demand for nutrients, while less than 35 % of N, P, K, Ca and Mg were allocated to wood or fine roots. Proportionally, cerrado showed higher nutrient demand from fine roots (over 35 % of the total nutrient demand) and for the wood component (over 13 % of the total nutrient demand), while ∼ 60 %–70 % of the cerradão nutrient demand was allocated to the canopy. The proportional difference in nutrient allocation to the different biomass components suggests cerrado species allocate less nutrients to a given fine root biomass, but more nutrients to a given wood biomass. Our findings suggest that cerradão species are more limited in P and K than cerrado species, inducing higher resorption to compensate for low uptake. Moreover, we found that N uptake for cerradão was higher with lower N use efficiency, i.e. the amount of production per nutrient unit, leading higher N demand compared to the cerrado. This difference in nutrient dynamics explains how similar soils and the same climate dominated by savanna vegetation can also support forest-like formations. Tree species composition is likely the major factor regulating nutrient use, limiting vegetation transitions and influencing nutrient demand at landscape scales.
Publisher: Wiley
Date: 21-09-2016
DOI: 10.1002/EAP.1368
Abstract: Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between in iduals that promote differential levels of mortality.
Publisher: Wiley
Date: 22-03-2022
DOI: 10.1111/GCB.16141
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Publisher: The Royal Society
Date: 24-04-2017
Abstract: Considerable interest in the relationship between bio ersity and disease has recently captured the attention of the research community, with important public policy implications. In particular, malaria in the Amazon region is often cited as an ex le of how forest conservation can improve public health outcomes. However, despite a growing body of literature and an increased understanding of the relationship between malaria and land use / land cover change (LULC) in Amazonia, contradictions have emerged. While some studies report that deforestation increases malaria risk, others claim the opposite. Assessing malaria risk requires examination of dynamic processes among three main components: (i) the environment (i.e. LULC and landscape transformations), (ii) vector biology (e.g. mosquito species distributions, vector activity and life cycle, plasmodium infection rates), and (iii) human populations (e.g. forest-related activity, host susceptibility, movement patterns). In this paper, we conduct a systematic literature review on malaria risk and deforestation in the Amazon focusing on these three components. We explore key features that are likely to generate these contrasting results using the reviewed articles and our own data from Brazil and Peru, and conclude with suggestions for productive avenues in future research. This article is part of the themed issue ‘Conservation, bio ersity and infectious disease: scientific evidence and policy implications'.
Publisher: Wiley
Date: 19-08-2020
DOI: 10.1111/GCB.15215
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: Wiley
Date: 29-03-2021
DOI: 10.1111/PCE.14049
Abstract: Atmospheric and climate change will expose tropical forests to conditions they have not experienced in millions of years. To better understand the consequences of this change, we studied photosynthetic acclimation of the neotropical tree species Tabebuia rosea to combined 4°C warming and twice‐ambient (800 ppm) CO 2 . We measured temperature responses of the maximum rates of ribulose 1,5‐bisphosphate carboxylation ( V CMax ), photosynthetic electron transport ( J Max ), net photosynthesis ( P Net ), and stomatal conductance ( g s ), and fitted the data using a probabilistic Bayesian approach. To evaluate short‐term acclimation plants were then switched between treatment and control conditions and re‐measured after 1–2 weeks. Consistent with acclimation, the optimum temperatures ( T Opt ) for V CMax , J Max and P Net were 1–5°C higher in treatment than in control plants, while photosynthetic capacity ( V CMax , J Max , and P Net at T Opt ) was 8–25% lower. Likewise, moving control plants to treatment conditions moderately increased temperature optima and decreased photosynthetic capacity. Stomatal density and sensitivity to leaf‐to‐air vapour pressure deficit were not affected by growth conditions, and treatment plants did not exhibit stronger stomatal limitations. Collectively, these results illustrate the strong photosynthetic plasticity of this tropical tree species as even fully developed leaves of saplings transferred to extreme conditions partially acclimated.
Publisher: MDPI AG
Date: 28-06-2019
DOI: 10.3390/RS11131534
Abstract: Tropical forests exhibit complex but poorly understood patterns of leaf phenology. Understanding species- and in idual-level phenological patterns in tropical forests requires datasets covering large numbers of trees, which can be provided by Unmanned Aerial Vehicles (UAVs). In this paper, we test a workflow combining high-resolution RGB images (7 cm ixel) acquired from UAVs with a machine learning algorithm to monitor tree and species leaf phenology in a tropical forest in Panama. We acquired images for 34 flight dates over a 12-month period. Crown boundaries were digitized in images and linked with forest inventory data to identify species. We evaluated predictions of leaf cover from different models that included up to 14 image features extracted for each crown on each date. The models were trained and tested with visual estimates of leaf cover from 2422 images from 85 crowns belonging to eight species spanning a range of phenological patterns. The best-performing model included both standard color metrics, as well as texture metrics that quantify within-crown variation, with r2 of 0.84 and mean absolute error (MAE) of 7.8% in 10-fold cross-validation. In contrast, the model based only on the widely-used Green Chromatic Coordinate (GCC) index performed relatively poorly (r2 = 0.52, MAE = 13.6%). These results highlight the utility of texture features for image analysis of tropical forest canopies, where illumination changes may diminish the utility of color indices, such as GCC. The algorithm successfully predicted both in idual-tree and species patterns, with mean r2 of 0.82 and 0.89 and mean MAE of 8.1% and 6.0% for in idual- and species-level analyses, respectively. Our study is the first to develop and test methods for landscape-scale UAV monitoring of in idual trees and species in erse tropical forests. Our analyses revealed undescribed patterns of high intraspecific variation and complex leaf cover changes for some species.
Publisher: Wiley
Date: 12-2019
DOI: 10.1111/GEB.13039
Publisher: Copernicus GmbH
Date: 21-03-2022
Publisher: Elsevier BV
Date: 2021
Publisher: Wiley
Date: 22-04-2022
DOI: 10.1111/NPH.18129
Abstract: Predicting species‐level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy dominant eucalypt tree species across South‐Eastern Australia (mean annual precipitation range: 344–1424 mm yr −1 ). We conducted three experiments: applying CABLE to the 2017–2019 drought a 20% drier drought and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO 2 ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within‐species’ ranges, but we also pinpointed resilience in species found in predominantly semiarid areas. The importance of the role of CO 2 in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of in idual tree species, providing an evidence base for decision‐making around the resilience of restoration plantings or net‐zero emission strategies.
Publisher: IOP Publishing
Date: 30-09-2019
Abstract: The El Niño Southern Oscillation (ENSO) is a major driver of seasonal and interannual climatic variability across the tropics. The 2015/16 El Niño event was one of the strongest El Niño events of the past century. Here we characterize the meteorological impacts of the 2015/16 El Niño event upon the terrestrial tropics, and place the severity of this event into context of previous strong events in 1982/83 and 1997/98. Strong drought-inducing meteorological anomalies (≥2 s.d.) occurred across vast regions (20%) of the terrestrial tropics, where the wet tropics (≥1200 mm yr −1 ) were more severely affected (33%) than the drier tropics (6%). Central and eastern Amazonia experienced the most sustained and spatially extensive drought inducing anomalies, while parts of the Congo basin and Insular Southeast Asia also experienced severe drought. Surprisingly, some regions of the tropics (e.g. the Guiana Shield) with well known ENSO teleconnections were only briefly affected by the 2015/16 El Niño event. 2015/16 El Niño soil water drought impacts affected 29% of the terrestrial tropics, compared to 16% and 18% in 1982/83 and 1997/98, respectively. Maximum temperatures were particularly exacerbated compared to previous strong El Niños because they were lified by the warming trend due to anthropogenic climate change. This also intensified positive anomalies of atmospheric vapor pressure deficit (the atmospheric demand for moisture), which had strongly negative consequences for vegetation productivity in the tropics. Even if El Niño events do not increase in intensity over coming decades, the pervasive long-term warming trend means that the atmospheric drought impact of each strong El Niño is becoming more severe, and many parts of the tropics will experience novel climate (temperature and VPD) conditions with each new strong El Niño event.
Publisher: IOP Publishing
Date: 05-2018
Publisher: Springer Science and Business Media LLC
Date: 18-05-2022
DOI: 10.1038/S41586-022-04737-7
Abstract: Evidence exists that tree mortality is accelerating in some regions of the tropics
Publisher: Copernicus GmbH
Date: 28-01-2022
Abstract: Abstract. Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e., increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water use efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread “greening” phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual- to decadal-scale climate variability. In this study we asked the question of how much CO2 has contributed towards greening. We focused our analysis on a broad aridity gradient spanning eastern Australia's woody ecosystems. Next we analyzed 38 years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heat waves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g., fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water use efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2-induced change in water use efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2-induced changes in water use efficiency affect trees and non-tree vegetation is needed.
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: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-2419
Abstract: & & Predicting species-level responses to drought at the landscape scale is critical to reducing future uncertainty in terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterised the model for 15 canopy dominant eucalypt tree species representative of a broad precipitation gradient across South East Australia (mean annual precipitation range: 344& #8211 mm yr& sup& -1& /sup& ). We conducted three experiments: (i) applying CABLE to the 2017& #8211 drought in South East Australia (ii) a 20% drier drought and (iii) a 20% drier drought with a doubling of atmospheric carbon dioxide (CO& sub& & /sub& ). We identified several drought hotspots across the ranges of & em& E.viminalis& /em& , & em& E.obliqua& /em& , & em& E.globulus& /em& , & em& E.saligna,& /em& and & em& E.grandis& /em& . By contrast, CABLE simulated drought resilience in species that are found predominately in semi-arid areas such as & em& E.largiflorens& /em& and & em& E.populnea& /em& . We identified several key model assumptions (& em& e& /em& .& em& g& /em& ., the degree of stomatal control) and sensitivities (& em& e& /em& .& em& g& /em& ., the role of CO& sub& & /sub& in ameliorating drought) that require future research. Our results represent an important step forward in our capacity to forecast the resilience of in idual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or strategies associated with achieving net-zero emissions.& &
Publisher: PeerJ
Date: 21-08-2014
DOI: 10.7717/PEERJ.542
Publisher: American Association for the Advancement of Science (AAAS)
Date: 25-08-2023
Abstract: Carbon offsets from voluntary avoided-deforestation projects are generated on the basis of performance in relation to ex ante deforestation baselines. We examined the effects of 26 such project sites in six countries on three continents using synthetic control methods for causal inference. We found that most projects have not significantly reduced deforestation. For projects that did, reductions were substantially lower than claimed. This reflects differences between the project ex ante baselines and ex post counterfactuals according to observed deforestation in control areas. Methodologies used to construct deforestation baselines for carbon offset interventions need urgent revisions to correctly attribute reduced deforestation to the projects, thus maintaining both incentives for forest conservation and the integrity of global carbon accounting.
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: Copernicus GmbH
Date: 09-10-2023
Publisher: Copernicus GmbH
Date: 21-03-2022
DOI: 10.5194/BG-2022-63
Abstract: Abstract. The total demand and uptake of nutrients by vegetation is rarely quantified or compared across vegetation types. Here, we describe different nutrient use and allocation strategies in Neotropical savanna (cerrado) and transitional forest (cerradão) sites, report leaf nutrient resorption and calculate ecosystem-level nutrient use efficiency. For the first time, we couple net primary productivity (NPP) estimates with nutrient stoichiometry to quantify nutrient demand and nutrient flows at the whole stand scale for different components of vegetation biomass. The two vegetation types showed similar mean nutrient concentration and nutrient resorption efficiency except for wood P concentration that was 4-fold higher in cerrado than cerradão species. The cerradão showed higher canopy NPP, while fine roots and wood NPP were similar for the two vegetation types. Nutrient requirement in the two vegetation types was dominated by the demands of the canopy, with canopy resorption contributing generally more than 50 % of the total canopy demand for nutrients, while less than 35 % of N, P, K, Ca and Mg were allocated to wood or fine roots. Proportionally, the savanna site showed higher nutrient demand from fine-roots (over 35 % of total nutrient demand) and for the wood component (over 13 % of total nutrient demand), while ~60–70 % of cerradão nutrient demand was allocated to the canopy. The proportional difference in nutrient allocation to the different biomass components suggesting cerrado species are more efficient in fine root production, but less efficient in producing wood. Our findings suggest that cerradão species are limited in P and K, inducing a higher resorption to compensate for low uptake. Moreover, we found that N uptake for cerradão was higher with lower N use efficiency, leading higher N demand compared to the cerrado. This trade-off explains how similar soils and the same climate dominated by savanna vegetation can also support forest-like formations. The lack of difference in Ca and Mg use and uptake efficiency also suggests these ecosystems are able to acquire all Ca and Mg they need. Tree species composition is likely the major factor regulating nutrient use, limiting vegetation transitions and influencing nutrient demand at landscape scales.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Sami Rifai.