| 1. |
- Ibanez, Thomas, et al.
(författare)
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Damage to tropical forests caused by cyclones is driven by wind speed but mediated by topographical exposure and tree characteristics
- 2024
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Ingår i: Global Change Biology. - : John Wiley & Sons. - 1354-1013 .- 1365-2486. ; 30:5
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Tidskriftsartikel (refereegranskat)abstract
- Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world.
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| 2. |
- Doughty, Christopher E., et al.
(författare)
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Drought impact on forest carbon dynamics and fluxes in Amazonia
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 519:7541, s. 78-140
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Tidskriftsartikel (refereegranskat)abstract
- In 2005 and 2010 the Amazon basin experienced two strong droughts', driven by shifts in the tropical hydrological regime(2) possibly associated with global climate change(3), as predicted by some global models'. Tree mortality increased after the 2005 drought(4), and regional atmospheric inversion modelling showed basin-wide decreases in CO2 uptake in 2010 compared with 2011 (ref. 5). But the response of tropical forest carbon cycling to these droughts is not fully understood and there has been no detailed multi-site investigation in situ. Here we use several years of data from a network of thirteen 1-ha forest plots spread throughout South America, where each component of net primary production (NPP), autotrophic respiration and heterotrophic respiration is measured separately, to develop a better mechanistic understanding of the impact of the 2010 drought on the Amazon forest. We find that total NPP remained constant throughout the drought. However, towards the end of the drought, autotrophic respiration, especially in roots and stems, declined significantly compared with measurements in 2009 made in the absence of drought, with extended decreases in autotrophic respiration in the three driest plots. In the year after the drought, total NPP remained constant but the allocation of carbon shifted towards canopy NPP and away from fine-root NPP. Both leaf-level and plot-level measurements indicate that severe drought suppresses photosynthesis. Scaling these measurements to the entire Amazon basin with rainfall data, we estimate that drought suppressed Amazon-wide photosynthesis in 2010 by 0.38 petagrams of carbon (0.23-0.53 petagrams of carbon). Overall, we find that during this drought, instead of reducing total NPP, trees prioritized growth by reducing autotrophic respiration that was unrelated to growth. This suggests that trees decrease investment in tissue maintenance and defence, in line with eco-evolutionary theories that trees are competitively disadvantaged in the absence of growth(6). We propose that weakened maintenance and defence investment may, in turn, cause the increase in post-drought tree mortality observed at our plots.
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| 3. |
- Doughty, Christopher E., et al.
(författare)
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Source and sink carbon dynamics and carbon allocation in the Amazon basin
- 2015
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Ingår i: Global Biogeochemical Cycles. - 0886-6236. ; 29:5, s. 645-655
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Tidskriftsartikel (refereegranskat)abstract
- Changes to the carbon cycle in tropical forests could affect global climate, but predicting such changes has been previously limited by lack of field-based data. Here we show seasonal cycles of the complete carbon cycle for 14, 1ha intensive carbon cycling plots which we separate into three regions: humid lowland, highlands, and dry lowlands. Our data highlight three trends: (1) there is differing seasonality of total net primary productivity (NPP) with the highlands and dry lowlands peaking in the dry season and the humid lowland sites peaking in the wet season, (2) seasonal reductions in wood NPP are not driven by reductions in total NPP but by carbon during the dry season being preferentially allocated toward either roots or canopy NPP, and (3) there is a temporal decoupling between total photosynthesis and total carbon usage (plant carbon expenditure). This decoupling indicates the presence of nonstructural carbohydrates which may allow growth and carbon to be allocated when it is most ecologically beneficial rather than when it is most environmentally available.
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| 4. |
- Huaraca Huasco, Walter, et al.
(författare)
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Seasonal production, allocation and cycling of carbon in two mid-elevation tropical montane forest plots in the Peruvian Andes
- 2014
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Ingår i: Plant Ecology & Diversity. - : Informa UK Limited. - 1755-0874 .- 1755-1668. ; 7:1-2, s. 125-142
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Tidskriftsartikel (refereegranskat)abstract
- Background: Tropical montane cloud forests (TMCF) are unique ecosystems with high biodiversity and large carbon reservoirs. To date there have been limited descriptions of the carbon cycle of TMCF. Aims: We present results on the production, allocation and cycling of carbon for two mid-elevation (1500-1750 m) tropical montane cloud forest plots in San Pedro, Kosnipata Valley, Peru. Methods: We repeatedly recorded the components of net primary productivity (NPP) using biometric measurements, and autotrophic (R-a) and heterotrophic (Rh) respiration, using gas exchange measurements. From these we estimated gross primary productivity (GPP) and carbon use efficiency (CUE) at the plot level. Results: The plot at 1500 m was found very productive, with our results comparable with the most productive lowland Amazonian forests. The plot at 1750 m had significantly lower productivity, possibly because of greater cloud immersion. Both plots had similar patterns of NPP allocation, a substantial seasonality in NPP components and little seasonality in R-a. Conclusions: These two plots lie within the ecotone between lower and upper montane forests, near the level of the cloud base. Climate change is likely to increase elevation of the cloud base, resulting in shifts in forest functioning. Longer-term surveillance of the carbon cycle at these sites would yield valuable insights into the response of TMCFs to a shifting cloud base.
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| 5. |
- Rowland, L, et al.
(författare)
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Death from drought in tropical forests is triggered by hydraulics not carbon starvation.
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 528:7580, s. 119-122
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Tidskriftsartikel (refereegranskat)abstract
- Drought threatens tropical rainforests over seasonal to decadal timescales, but the drivers of tree mortality following drought remain poorly understood. It has been suggested that reduced availability of non-structural carbohydrates (NSC) critically increases mortality risk through insufficient carbon supply to metabolism ('carbon starvation'). However, little is known about how NSC stores are affected by drought, especially over the long term, and whether they are more important than hydraulic processes in determining drought-induced mortality. Using data from the world's longest-running experimental drought study in tropical rainforest (in the Brazilian Amazon), we test whether carbon starvation or deterioration of the water-conducting pathways from soil to leaf trigger tree mortality. Biomass loss from mortality in the experimentally droughted forest increased substantially after >10 years of reduced soil moisture availability. The mortality signal was dominated by the death of large trees, which were at a much greater risk of hydraulic deterioration than smaller trees. However, we find no evidence that the droughted trees suffered carbon starvation, as their NSC concentrations were similar to those of non-droughted trees, and growth rates did not decline in either living or dying trees. Our results indicate that hydraulics, rather than carbon starvation, triggers tree death from drought in tropical rainforest.
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| 6. |
- Doughty, Christopher E., et al.
(författare)
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What controls variation in carbon use efficiency among Amazonian tropical forests?
- 2018
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Ingår i: Biotropica. - : Wiley. - 0006-3606. ; 50:1, s. 16-25
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Tidskriftsartikel (refereegranskat)abstract
- Why do some forests produce biomass more efficiently than others? Variations in Carbon Use Efficiency (CUE: total Net Primary Production (NPP)/ Gross Primary Production (GPP)) may be due to changes in wood residence time (Biomass/NPPwood), temperature, or soil nutrient status. We tested these hypotheses in 14, one ha plots across Amazonian and Andean forests where we measured most key components of net primary production (NPP: wood, fine roots, and leaves) and autotrophic respiration (Ra; wood, rhizosphere, and leaf respiration). We found that lower fertility sites were less efficient at producing biomass and had higher rhizosphere respiration, indicating increased carbon allocation to belowground components. We then compared wood respiration to wood growth and rhizosphere respiration to fine root growth and found that forests with residence times <40 yrs had significantly lower maintenance respiration for both wood and fine roots than forests with residence times >40 yrs. A comparison of rhizosphere respiration to fine root growth showed that rhizosphere growth respiration was significantly greater at low fertility sites. Overall, we found that Amazonian forests produce biomass less efficiently in stands with residence times >40 yrs and in stands with lower fertility, but changes to long-term mean annual temperatures do not impact CUE.
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| 7. |
- Hosseinzadeh, Griffin, et al.
(författare)
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Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot
- 2020
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 905:2
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Tidskriftsartikel (refereegranskat)abstract
- The classification of supernovae (SNe) and its impact on our understanding of explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming wide-field time-domain surveys have increased the transient discovery rate far beyond our capacity to obtain even a single spectrum of each new event. We must therefore rely heavily on photometric classification-connecting SN light curves back to their spectroscopically defined classes. Here, we present Superphot, an open-source Python implementation of the machine-learning classification algorithm of Villar et al., and apply it to 2315 previously unclassified transients from the Pan-STARRS1 Medium Deep Survey for which we obtained spectroscopic host-galaxy redshifts. Our classifier achieves an overall accuracy of 82%, with completenesses and purities of >80% for the best classes (SNe Ia and superluminous SNe). For the worst performing SN class (SNe Ibc), the completeness and purity fall to 37% and 21%, respectively. Our classifier provides 1257 newly classified SNe Ia, 521 SNe II, 298 SNe Ibc, 181 SNe IIn, and 58 SLSNe. These are among the largest uniformly observed samples of SNe available in the literature and will enable a wide range of statistical studies of each class.
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| 8. |
- Malhi, Yadvinder, et al.
(författare)
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The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests
- 2015
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013. ; 21:6, s. 2283-2295
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling.
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| 9. |
- Rowland, L, et al.
(författare)
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After more than a decade of soil moisture deficit, tropical rainforest trees maintain photosynthetic capacity, despite increased leaf respiration.
- 2015
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 21:12, s. 4662-4672
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Tidskriftsartikel (refereegranskat)abstract
- Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more than 12 years of experimental soil moisture deficit, via a through-fall exclusion experiment (TFE) in an eastern Amazonian rainforest. We find that experimentally drought-stressed trees and taxa maintain the same maximum leaf photosynthetic capacity as trees in corresponding control forest, independent of their susceptibility to drought-induced mortality. We hypothesise that photosynthetic capacity is maintained across all treatments and taxa to take advantage of short-lived periods of high moisture availability, when stomatal conductance (gs ) and photosynthesis can increase rapidly, potentially compensating for reduced assimilate supply at other times. Average leaf dark respiration (Rd ) was elevated in the TFE-treated forest trees relative to the control by 28.2±2.8% (mean ± one standard error). This mean Rd value was dominated by a 48.5±3.6% increase in the Rd of drought-sensitive taxa, and likely reflects the need for additional metabolic support required for stress-related repair, and hydraulic or osmotic maintenance processes. Following soil moisture deficit that is maintained for several years, our data suggest that changes in respiration drive greater shifts in the canopy carbon balance, than changes in photosynthetic capacity. This article is protected by copyright. All rights reserved.
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| 10. |
- Villar, V. Ashley, et al.
(författare)
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SuperRAENN : A Semisupervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium-Deep Survey Supernovae
- 2020
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 905:2
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Tidskriftsartikel (refereegranskat)abstract
- Automated classification of supernovae (SNe) based on optical photometric light-curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multiwavelength follow-up, as well as archival population studies. Here we present the complete sample of 5243 SN-like light curves (in g(P1)r(P1)i(P1)z(P1)) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters, and depth, making this a useful training set for the community. Using this data set, we train a novel semisupervised machine learning algorithm to photometrically classify 2315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of an RF supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I) and macro-averaged purity and completeness of 66% and 69%, respectively. We find the highest accuracy rates for SNe Ia and SLSNe and the lowest for SNe Ibc. Our complete spectroscopically and photometrically classified samples break down into 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects).
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