New insights into the variability of the tropical land carbon cycle from the El Niño of 2015/2016

Malhi, Yadvinder; Rowland, Lucy; Aragão, Luiz E. O. C.; Fisher, Rosie A.

doi:10.1098/rstb.2017.0298

Cited by 26 publications

(21 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We recall that years 2015 and 2016 correspond to a strong El Niño event associated with a large CO 2 growth rate (e.g. Malhi et al, 2018 and references therein). The GOSAT inversions seem to underestimate the beginning of this anomaly (Fig.…”

Section: Annual Budgetsmentioning

confidence: 99%

Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

et al. 2019

View full text Add to dashboard Cite

Abstract. We study an ensemble of six multi-year global Bayesian carbon dioxide (CO2) atmospheric inversions that vary in terms of assimilated observations (either column retrievals from one of two satellites or surface air sample measurements) and transport model. The time series of inferred annual fluxes are first compared with each other at various spatial scales. We then objectively evaluate the small inversion ensemble based on a large dataset of accurate aircraft measurements in the free troposphere over the globe, which are independent of all assimilated data. The measured variables are connected with the inferred fluxes through mass-conserving transport in the global atmosphere and are part of the inversion results. Large-scale annual fluxes estimated from the bias-corrected land retrievals of the second Orbiting Carbon Observatory (OCO-2) differ greatly from the prior fluxes, but are similar to the fluxes estimated from the surface network within the uncertainty of these surface-based estimates. The OCO-2-based and surface-based inversions have similar performance when projected in the space of the aircraft data, but the relative strengths and weaknesses of the two flux estimates vary within the northern and tropical parts of the continents. The verification data also suggest that the more complex and more recent transport model does not improve the inversion skill. In contrast, the inversion using bias-corrected retrievals from the Greenhouse Gases Observing Satellite (GOSAT) or, to a larger extent, a non-Bayesian inversion that simply adjusts a recent bottom-up flux estimate with the annual growth rate diagnosed from marine surface measurements both estimate much different fluxes and fit the aircraft data less. Our study highlights a way to rate global atmospheric inversions. Without any general claim regarding the usefulness of all OCO-2 retrieval datasets vs. all GOSAT retrieval datasets, it still suggests that some satellite retrievals can now provide inversion results that are, despite their uncertainty, comparable with respect to credibility to traditional inversions using the accurate but sparse surface network and that are therefore complementary for studies of the global carbon budget.

show abstract

Section: Annual Budgetsmentioning

confidence: 99%

Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

et al. 2019

View full text Add to dashboard Cite

show abstract

“…It is important to mention that the increase in gap area percentage in 2014 compared to 2012 was due to logging activities, whereas no logging activities were conducted in the second acquisition interval. A plausible explanation for the observed results is the 2015/2016 El Niño event (Malhi, Rowland, Aragão, & Fisher, ). El Niño events cause extremely dry periods in Amazon region, which can lead to increased mortality rates, reported by Leitold et al ().…”

Section: Example Applicationsmentioning

confidence: 89%

“…in the logged forests when the 2014 and 2017 gap detection are compared (Table 2, Figure 6). It is important to mention that the increase in gap area percentage in 2014 compared to 2012 was due to logging activities, whereas no logging activities were conducted in the second (Malhi, Rowland, Aragão, & Fisher, 2018).…”

Section: Dynamics Of Forest Canopy Gaps In a Selectively Logged Tromentioning

confidence: 99%

“…Forests cover around 31 percent of global Earth's land area (Keenan et al, 2015). They have a critical role in the global carbon cycle and consist of the most important global repository of terrestrial biodiversity (Pan et al, 2011). In mature and old-growth forests, many forest functional processes are governed by local canopy gap dynamics (Vepakomma, St-Onge, & Kneeshaw, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

ForestGapR: AnrPackage for forest gap analysis from canopy height models

et al. 2019

View full text Add to dashboard Cite

In forest ecosystems, many functional processes are governed by local canopy gap dynamics, caused by either natural or anthropogenic factors. Quantifying the size and spatial distribution of canopy gaps enables an improved understanding and predictive modelling of multiple environmental phenomena. For instance knowledge of canopy gap dynamics can help us elucidate time‐integrated effects of tree mortality, regrowth and succession rates, carbon flux patterns, species heterogeneity and three‐dimensional spacing within structurally complex forest ecosystems. Airborne Laser Scanning (ALS) has emerged as a technology that is well‐suited for mapping forest canopy gaps in a wide variety of forest ecosystems and across spatial scales. New technological and algorithmic advances, including ALS remote‐sensing, coupled with optimized frameworks for data processing and detection of forest canopy gaps, are allowing an enhanced understanding of forest structure and functional processes. This paper introduces ForestGapR, a cutting‐edge open source r package for forest gap analysis from canopy height models derived from ALS and other remote sensing sources. The ForestGapR package offers tools to (a) automate forest canopy gap detection, (b) compute a series of gap statistics, including gap‐size frequency distributions and spatial distribution, (c) map gap dynamics (when multitemporal ALS data are available) and (d) convert forest canopy gaps detected into raster or vector layers as per user requirements. As case studies, we run ForestGapR on ALS data collected over four different tropical forest regions worldwide. We hope this new package will enable further research towards understanding the distribution, dynamics and role of canopy gaps not only in tropical forests, but in other forest types elsewhere.

show abstract

“…Despite advances in our knowledge of El Niño consequences for the carbon cycle (Berenguer et al, ; Malhi et al, ), our understanding of the impacts for biodiversity and related ecosystem functions remains limited, especially in human‐modified tropical forests. While detailed studies have been conducted following experimental fires (e.g., ≤50‐ha forest plots; Balch, Massad, Brando, Nepstad, & Curran, ; Brando et al, ; Oliveras et al, ), these may underestimate the effects of large‐scale megafires which can affect millions of hectares (e.g., Withey et al, ).…”

Section: Introductionmentioning

confidence: 99%

El Niño impacts on human‐modified tropical forests: Consequences for dung beetle diversity and associated ecological processes

et al. 2020

View full text Add to dashboard Cite

Our knowledge of how tropical forest biodiversity and functioning respond to anthropogenic and climate‐associated stressors is limited. Research exploring El Niño impacts are scarce or based on single post‐disturbance assessments, and few studies assess forests previously affected by anthropogenic disturbance. Focusing on dung beetles and associated ecological functions, we assessed (a) the ecological effects of a strong El Niño, (b) if post‐El Niño beetle responses were influenced by previous forest disturbance, and (c) how these responses compare between forests impacted only by drought and those affected by both drought and fires. We sampled 30 Amazonian forest plots distributed across a gradient of human disturbance in 2010, 2016, and 2017—approximately 5 years before, and 3–6 and 15–18 months after the 2015–16 El Niño. We found 14,451 beetles from 98 species and quantified the beetle‐mediated dispersal of >8,600 seed mimics and the removal of c. 30 kg of dung. All dung beetle responses (species richness, abundance, biomass, compositional similarity to pre‐El Niño condition, and rates of dung removal and seed dispersal) declined after the 2015–16 El Niño, but the greatest immediate losses (i.e., in 2016) were observed within fire‐affected forests. Previous forest disturbance also influenced post‐El Niño dung beetle species richness, abundance, and species composition. We demonstrate that dung beetles and their ecological functions are negatively affected by climate‐associated disturbances in human‐modified Amazonian forests and suggest that the interaction between local anthropogenic and climate‐related stressors merits further investigation. Abstract in Portuguese is available with online material.

show abstract

New insights into the variability of the tropical land carbon cycle from the El Niño of 2015/2016

Cited by 26 publications

References 35 publications

Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

ForestGapR: AnrPackage for forest gap analysis from canopy height models

El Niño impacts on human‐modified tropical forests: Consequences for dung beetle diversity and associated ecological processes

Contact Info

Product

Resources

About