Many tropical regions are experiencing an intensification of drought, with increasing severity and frequency. The ecosystem response to these changes is still highly uncertain. On short time scales (from diurnal to seasonal), tropical forests respond to water stress by physiological controls, such as stomatal regulation and phenological adjustment, to cope with increasing atmospheric water demand and reduced water supply. However, the interactions among biological processes and co‐varying environmental factors that determine the ecosystem‐level fluxes are still unclear. Furthermore, climate variability at longer time scales, such as that generated by ENSO, produces less predictable effects because it depends on a highly stochastic combination of factors that might vary among forests and even between events in the same forest. This study will present some emerging patterns of response to water stress from 5 years of water, carbon, and energy fluxes observed on a seasonal tropical forest in central Panama, including an increase in productivity during the 2015 El Niño. These responses depend on the combination of environmental factors experienced by the forest throughout the seasonal cycle, in particular, increase in solar radiation, stimulating productivity, and increasing vapor pressure deficit (VPD) and decreasing soil moisture, limiting stomata opening. These results suggest a critical role of plant hydraulics in mediating the response to water stress over a broad range of temporal scales (diurnal, intraseasonal, seasonal, and interannual), by acclimating canopy conductance to light and VPD during different soil moisture regimes. A multilayer photosynthesis model coupled with a plant hydraulics scheme can reproduce these complex responses. However, results depend critically on parameters regulating water transport efficiency and the cost of water stress. As these costs have not been properly identified and quantified yet, more empirical research is needed to elucidate physiological mechanisms of hydraulic failure and recover, for example embolism repair and xylem regrowth.
- Award ID(s):
- 1616827
- NSF-PAR ID:
- 10313129
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract Tropical montane cloud forests support abundant epiphytic vascular plant communities that serve important ecosystem functions, but their reliance on atmospheric inputs of water may make them susceptible to the drying effects of rising cloud bases and more frequent droughts.
We conducted a common garden experiment to explore the combined effects of decreasing cloud influence—lower humidity, warmer temperature, brighter light—and meteorological drought (i.e. absence of rain) on the physiology and morphology of vascular epiphytes native to primary forests of Monteverde, Costa Rica. The epiphytes, which exhibited C3photosynthesis, were sourced from a lower montane cloud forest (CF) or a rainforest (RF) below the current cloud base and transplanted into nearby shadehouses (CF or RF shadehouse respectively). Vapour pressure deficit (VPD) and light availability, measured as photosynthetically active radiation, were 2.5 and 3.1 times higher in the RF than the CF shadehouse. Half of the plants were subjected to a severe 4‐week drought followed by a recovery period, and the other half were watered controls.
Plants subjected to low VPD/light conditions of the CF shadehouse were physiologically and morphologically resistant to the drought treatment. However, compared to control plants, both sources of plants subjected to high VPD/light conditions of the RF shadehouse experienced declines in maximum net photosynthesis (
A max), stomatal conductance (g s) and the proportion of healthy leaves (those not exhibiting chlorosis, desiccation or necrosis). At peak drought, leaves from the RF were 19% thinner than controls. Within 7–14 days after rewatering,A max,g sand leaf health recovered to nearly the levels of controls. Growth rate, mortality and phenology were unaffected by the treatments.The divergent responses to drought in the CF versus RF shadehouses, combined with the recovery in the RF shadehouse, indicate that these epiphytes possess adaptive properties that confer low resistance, but high recovery capacity, to episodes of short‐term drought over a range of cloud influence. In addition, the reduction in
A maxsuggests stomatal regulation that favours water conservation over carbon acquisition, a strategy that may inform epiphyte responses to rising clouds and increasing drought frequency expected in the long term.A free
Plain Language Summary can be found within the Supporting Information of this article. -
more » « less
Abstract Context Processes that shape genomic and ecological divergence can reveal important evolutionary dynamics to inform the conservation of threatened species.
Fontainea is a genus of rainforest shrubs and small trees including critically endangered and threatened species restricted to narrow, but complex geographic and ecological regions. Several species ofFontainea are subject to spatially explicit conditions and experience limited intra-specific gene flow, likely generating genetic differentiation and local adaptation.Objectives Here, we explored the genetic and ecological mechanisms underlying patterns of diversification in two, closely related threatened
Fontainea species. Our aim was to compare spatial patterns of genetic variation between the vulnerableFontainea australis (Southern Fontainea) and critically endangeredF. oraria (Coastal Fontainea), endemic to the heterogeneous subtropical region of central, eastern Australia, where large-scale clearing has severely reduced rainforest habitat to a fraction (< 1%) of its pre-European settlement extent.Methods We used a set of 10,000 reduced-representation markers to infer genetic relationships and the drivers of spatial genetic variation across the two species. In addition, we employed a combination of univariate and multivariate genome-environment association analysis using a set of topo-climatic variables to explore potential patterns of local adaptation as a factor impacting genomic divergence.
Results Our study revealed that Coastal Fontainea have a close genetic relationship with Southern Fontainea. We showed that isolation by distance has played a key role in their genetic variation, indicating that vicariance can explain the spatial genetic distribution of the two species. Genotype-environment analyses showed a strong association with temperature and topographic features, suggesting adaptation to localised thermal environments. We used a multivariate redundancy analysis to identify a range of putatively adapted loci associated with local environmental conditions.
Conclusions Divergent selection at the local-habitat scale as a result of dispersal limitations and environmental heterogeneity (including physical barriers) are likely contributors to adaptive divergence between the two
Fontainea species. Our findings have presented evidence to indicate that Southern and Coastal Fontainea were comprised of distinct genetic groups and ecotypes, that together may form a single species continuum, with further phenotype research suggested to confirm the current species boundaries. Proactive conservation actions, including assisted migration to enhance the resilience of populations lacking stress-tolerant single nucleotide polymorphisms (SNPs) may be required to secure the long-term future of both taxa. This is especially vital for the critically endangered Coastal Fontainea given projections of habitat decline for the species under future climate scenarios. -
Climate change has affected the Arctic Ocean (AO) and its marginal seas significantly. The reduction of sea ice in the Arctic region has altered the magnitude of photosynthetically available radiation (PAR) entering the water column, impacting primary productivity. Increasing cloudiness in the atmosphere and rising turbidity in the coastal waters of the Arctic region are considered as the major factors that counteract the effect of reduced sea ice on underwater PAR. Additionally, extreme solar zenith angles and sea-ice cover in the AO increase the complexity of retrieving PAR. In this study, a PAR algorithm based on radiative transfer in the atmosphere and satellite observations is implemented to evaluate the effect of these factors on PAR in the coastal AO. To improve the performance of the algorithm, a flag is defined to identify pixels containing open-water, sea-ice or cloud. The use of flag enabled selective application of algorithms to compute the input parameters for the PAR algorithm. The PAR algorithm is validated using in situ measurements from various coastal sites in the Arctic and sub-Arctic seas. The algorithm estimated daily integrated PAR above the sea surface with an uncertainty of 19% in summer. The uncertainty increased to 24% when the algorithm was applied year-round. The PAR values at the seafloor were estimated with an uncertainty of 76%, with 36% of the samples under sea ice and/or cloud cover. The robust performance of the PAR algorithm in the pan-Arctic region throughout the year will help to effectively study the temporal and spatial variability of PAR in the Arctic coastal waters. The calculated PAR data are used to quantify the changing trend in PAR at the seafloor in the coastal AO with depth < 100 m using MODIS-Aqua data from 2003 to 2020. The general trends calculated using the pixels with average PAR > 0.415 mol m−2 day−1 at the seafloor during summer indicate that the annual average of PAR entering the water column in the coastal AO between 2003 and 2020 increased by 23%. Concurrently, due to increased turbidity, the attenuation in the water column increased by 22%. The surge in incident PAR in the water column due to retreating sea ice first led to increased PAR observed at the seafloor (∼12% between 2003 and 2014). However, in the last decade, the rapid increase in light attenuation of the water column has restricted the increase in average annual PAR reaching the bottom in the coastal AO.more » « less
-
more » « less
Abstract The interior of Dronning Maud Land (DML) in East Antarctica is one of the most data-sparse regions of Antarctica for studying climate change. A monthly mean near-surface temperature dataset for the last 30 years has been compiled from the historical records from automatic weather stations (AWSs) at three sites in the region (Mizuho, Relay Station, and Dome Fuji). Multiple AWSs have been installed along the route to Dome Fuji since the 1990s, and observations have continued to the present day. The use of passive-ventilated radiation shields for the temperature sensors at the AWSs may have caused a warm bias in the temperature measurements, however, due to insufficient ventilation in the summer, when solar radiation is high and winds are low. In this study, these warm biases are quantified by comparison with temperature measurements with an aspirated shield and subsequently removed using a regression model. Systematic error resulting from changes in the sensor height due to accumulating snow was insignificant in our study area. Several other systematic errors occurring in the early days of the AWS systems were identified and corrected. After the corrections, multiple AWS records were integrated to create a time series for each station. The percentage of missing data over the three decades was 21% for Relay Station and 28% for Dome Fuji. The missing rate at Mizuho was 49%, more than double that at Relay Station. These new records allow for the study of temperature variability and change in DML, where climate change has so far been largely unexplored.
Significance Statement Antarctic climate change has been studied using temperature data at staffed stations. The staffed stations, however, are mainly located on the Antarctic Peninsula and in the coastal regions. Climate change is largely unknown in the Antarctic plateau, particularly in the western sector of the East Antarctic Plateau in areas such as the interior of Dronning Maud Land (DML). To fill the data gap, this study presents a new dataset of monthly mean near-surface climate data using historical observations from three automatic weather stations (AWSs). This dataset allows us to study temperature variability and change over a data-sparse region where climate change has been largely unexplored.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41598-019-56469-w
