Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 20 de 140
Filter
Add more filters

Publication year range
1.
Nature ; 627(8003): 321-327, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38480963

ABSTRACT

Overnight fires are emerging in North America with previously unknown drivers and implications. This notable phenomenon challenges the traditional understanding of the 'active day, quiet night' model of the diurnal fire cycle1-3 and current fire management practices4,5. Here we demonstrate that drought conditions promote overnight burning, which is a key mechanism fostering large active fires. We examined the hourly diurnal cycle of 23,557 fires and identified 1,095 overnight burning events (OBEs, each defined as a night when a fire burned through the night) in North America during 2017-2020 using geostationary satellite data and terrestrial fire records. A total of 99% of OBEs were associated with large fires (>1,000 ha) and at least one OBE was identified in 20% of these large fires. OBEs were early onset after ignition and OBE frequency was positively correlated with fire size. Although warming is weakening the climatological barrier to night-time fires6, we found that the main driver of recent OBEs in large fires was the accumulated fuel dryness and availability (that is, drought conditions), which tended to lead to consecutive OBEs in a single wildfire for several days and even weeks. Critically, we show that daytime drought indicators can predict whether an OBE will occur the following night, which could facilitate early detection and management of night-time fires. We also observed increases in fire weather conditions conducive to OBEs over recent decades, suggesting an accelerated disruption of the diurnal fire cycle.


Subject(s)
Darkness , Droughts , Wildfires , Droughts/statistics & numerical data , Ecosystem , North America , Wildfires/statistics & numerical data
2.
Nature ; 626(7999): 555-564, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38356065

ABSTRACT

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1-3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.


Subject(s)
Forests , Global Warming , Trees , Droughts/statistics & numerical data , Feedback , Global Warming/prevention & control , Global Warming/statistics & numerical data , Trees/growth & development , Wildfires/statistics & numerical data , Uncertainty , Environmental Restoration and Remediation/trends
3.
Nature ; 631(8019): 111-117, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38898277

ABSTRACT

Amazonia contains the most extensive tropical forests on Earth, but Amazon carbon sinks of atmospheric CO2 are declining, as deforestation and climate-change-associated droughts1-4 threaten to push these forests past a tipping point towards collapse5-8. Forests exhibit complex drought responses, indicating both resilience (photosynthetic greening) and vulnerability (browning and tree mortality), that are difficult to explain by climate variation alone9-17. Here we combine remotely sensed photosynthetic indices with ground-measured tree demography to identify mechanisms underlying drought resilience/vulnerability in different intact forest ecotopes18,19 (defined by water-table depth, soil fertility and texture, and vegetation characteristics). In higher-fertility southern Amazonia, drought response was structured by water-table depth, with resilient greening in shallow-water-table forests (where greater water availability heightened response to excess sunlight), contrasting with vulnerability (browning and excess tree mortality) over deeper water tables. Notably, the resilience of shallow-water-table forest weakened as drought lengthened. By contrast, lower-fertility northern Amazonia, with slower-growing but hardier trees (or, alternatively, tall forests, with deep-rooted water access), supported more-drought-resilient forests independent of water-table depth. This functional biogeography of drought response provides a framework for conservation decisions and improved predictions of heterogeneous forest responses to future climate changes, warning that Amazonia's most productive forests are also at greatest risk, and that longer/more frequent droughts are undermining multiple ecohydrological strategies and capacities for Amazon forest resilience.


Subject(s)
Drought Resistance , Droughts , Forests , Groundwater , Photosynthesis , Soil , Sunlight , Trees , Brazil , Carbon Sequestration , Droughts/statistics & numerical data , Groundwater/analysis , Soil/chemistry , Trees/classification , Trees/metabolism , Trees/physiology , Tropical Climate , Drought Resistance/physiology , Phylogeography , Conservation of Natural Resources
4.
Nature ; 614(7949): 719-724, 2023 02.
Article in English | MEDLINE | ID: mdl-36755095

ABSTRACT

The potential of climate change to substantially alter human history is a pressing concern, but the specific effects of different types of climate change remain unknown. This question can be addressed using palaeoclimatic and archaeological data. For instance, a 300-year, low-frequency shift to drier, cooler climate conditions around 1200 BC is frequently associated with the collapse of several ancient civilizations in the Eastern Mediterranean and Near East1-4. However, the precise details of synchronized climate and human-history-scale associations are lacking. The archaeological-historical record contains multiple instances of human societies successfully adapting to low-frequency climate change5-7. It is likely that consecutive multi-year occurrences of rare, unexpected extreme climatic events may push a population beyond adaptation and centuries-old resilience practices5,7-10. Here we examine the collapse of the Hittite Empire around 1200 BC. The Hittites were one of the great powers in the ancient world across five centuries11-14, with an empire centred in a semi-arid region in Anatolia with political and socioeconomic interconnections throughout the ancient Near East and Eastern Mediterranean, which for a long time proved resilient despite facing regular and intersecting sociopolitical, economic and environmental challenges. Examination of ring width and stable isotope records obtained from contemporary juniper trees in central Anatolia provides a high-resolution dryness record. This analysis identifies an unusually severe continuous dry period from around 1198 to 1196 (±3) BC, potentially indicating a tipping point, and signals the type of episode that can overwhelm contemporary risk-buffering practices.


Subject(s)
Climate Change , Droughts , Humans , Archaeology , Climate Change/history , Climate Change/statistics & numerical data , Droughts/history , Droughts/statistics & numerical data , Trees , History, Ancient , Juniperus , Ancient Lands , Turkey
5.
Nature ; 621(7980): 760-766, 2023 Sep.
Article in English | MEDLINE | ID: mdl-37648863

ABSTRACT

California has experienced enhanced extreme wildfire behaviour in recent years1-3, leading to substantial loss of life and property4,5. Some portion of the change in wildfire behaviour is attributable to anthropogenic climate warming, but formally quantifying this contribution is difficult because of numerous confounding factors6,7 and because wildfires are below the grid scale of global climate models. Here we use machine learning to quantify empirical relationships between temperature (as well as the influence of temperature on aridity) and the risk of extreme daily wildfire growth (>10,000 acres) in California and find that the influence of temperature on the risk is primarily mediated through its influence on fuel moisture. We use the uncovered relationships to estimate the changes in extreme daily wildfire growth risk under anthropogenic warming by subjecting historical fires from 2003 to 2020 to differing background climatological temperatures and aridity conditions. We find that the influence of anthropogenic warming on the risk of extreme daily wildfire growth varies appreciably on a fire-by-fire and day-by-day basis, depending on whether or not climate warming pushes conditions over certain thresholds of aridity, such as 1.5 kPa of vapour-pressure deficit and 10% dead fuel moisture. So far, anthropogenic warming has enhanced the aggregate expected frequency of extreme daily wildfire growth by 25% (5-95 range of 14-36%), on average, relative to preindustrial conditions. But for some fires, there was approximately no change, and for other fires, the enhancement has been as much as 461%. When historical fires are subjected to a range of projected end-of-century conditions, the aggregate expected frequency of extreme daily wildfire growth events increases by 59% (5-95 range of 47-71%) under a low SSP1-2.6 emissions scenario compared with an increase of 172% (5-95 range of 156-188%) under a very high SSP5-8.5 emissions scenario, relative to preindustrial conditions.


Subject(s)
Global Warming , Temperature , Wildfires , California , Climate Models , Droughts/statistics & numerical data , Global Warming/statistics & numerical data , Human Activities , Humidity , Machine Learning , Risk Assessment , Wildfires/statistics & numerical data , Humans
6.
Nature ; 620(7973): 336-343, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37558848

ABSTRACT

Anthropogenic climate change is predicted to severely impact the global hydrological cycle1, particularly in tropical regions where agriculture-based economies depend on monsoon rainfall2. In the Horn of Africa, more frequent drought conditions in recent decades3,4 contrast with climate models projecting precipitation to increase with rising temperature5. Here we use organic geochemical climate-proxy data from the sediment record of Lake Chala (Kenya and Tanzania) to probe the stability of the link between hydroclimate and temperature over approximately the past 75,000 years, hence encompassing a sufficiently wide range of temperatures to test the 'dry gets drier, wet gets wetter' paradigm6 of anthropogenic climate change in the time domain. We show that the positive relationship between effective moisture and temperature in easternmost Africa during the cooler last glacial period shifted to negative around the onset of the Holocene 11,700 years ago, when the atmospheric carbon dioxide concentration exceeded 250 parts per million and mean annual temperature approached modern-day values. Thus, at that time, the budget between monsoonal precipitation and continental evaporation7 crossed a tipping point such that the positive influence of temperature on evaporation became greater than its positive influence on precipitation. Our results imply that under continued anthropogenic warming, the Horn of Africa will probably experience further drying, and they highlight the need for improved simulation of both dynamic and thermodynamic processes in the tropical hydrological cycle.


Subject(s)
Climate Change , Climate Models , Droughts , Rain , Temperature , Water Cycle , Water , Atmosphere/chemistry , Carbon Dioxide/analysis , Climate Change/history , Droughts/statistics & numerical data , Geologic Sediments/chemistry , History, Ancient , Humidity , Kenya , Lakes/chemistry , Tanzania , Thermodynamics , Tropical Climate , Volatilization , Water/analysis
7.
Nature ; 621(7978): 318-323, 2023 Sep.
Article in English | MEDLINE | ID: mdl-37612502

ABSTRACT

The Amazon forest carbon sink is declining, mainly as a result of land-use and climate change1-4. Here we investigate how changes in law enforcement of environmental protection policies may have affected the Amazonian carbon balance between 2010 and 2018 compared with 2019 and 2020, based on atmospheric CO2 vertical profiles5,6, deforestation7 and fire data8, as well as infraction notices related to illegal deforestation9. We estimate that Amazonia carbon emissions increased from a mean of 0.24 ± 0.08 PgC year-1 in 2010-2018 to 0.44 ± 0.10 PgC year-1 in 2019 and 0.52 ± 0.10 PgC year-1 in 2020 (± uncertainty). The observed increases in deforestation were 82% and 77% (94% accuracy) and burned area were 14% and 42% in 2019 and 2020 compared with the 2010-2018 mean, respectively. We find that the numbers of notifications of infractions against flora decreased by 30% and 54% and fines paid by 74% and 89% in 2019 and 2020, respectively. Carbon losses during 2019-2020 were comparable with those of the record warm El Niño (2015-2016) without an extreme drought event. Statistical tests show that the observed differences between the 2010-2018 mean and 2019-2020 are unlikely to have arisen by chance. The changes in the carbon budget of Amazonia during 2019-2020 were mainly because of western Amazonia becoming a carbon source. Our results indicate that a decline in law enforcement led to increases in deforestation, biomass burning and forest degradation, which increased carbon emissions and enhanced drying and warming of the Amazon forests.


Subject(s)
Carbon Dioxide , Carbon Sequestration , Conservation of Natural Resources , Environmental Policy , Law Enforcement , Rainforest , Biomass , Brazil , Carbon Dioxide/analysis , Carbon Dioxide/metabolism , Environmental Policy/legislation & jurisprudence , Atmosphere/chemistry , Wildfires/statistics & numerical data , Conservation of Natural Resources/statistics & numerical data , El Nino-Southern Oscillation , Droughts/statistics & numerical data
8.
Nature ; 608(7921): 80-86, 2022 08.
Article in English | MEDLINE | ID: mdl-35922501

ABSTRACT

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.


Subject(s)
Droughts , Extreme Weather , Floods , Risk Management , Climate Change/statistics & numerical data , Datasets as Topic , Droughts/prevention & control , Droughts/statistics & numerical data , Floods/prevention & control , Floods/statistics & numerical data , Humans , Hydrology , Internationality , Risk Management/methods , Risk Management/statistics & numerical data , Risk Management/trends
9.
Nature ; 572(7768): 230-234, 2019 08.
Article in English | MEDLINE | ID: mdl-31391559

ABSTRACT

Groundwater in sub-Saharan Africa supports livelihoods and poverty alleviation1,2, maintains vital ecosystems, and strongly influences terrestrial water and energy budgets3. Yet the hydrological processes that govern groundwater recharge and sustainability-and their sensitivity to climatic variability-are poorly constrained4,5. Given the absence of firm observational constraints, it remains to be seen whether model-based projections of decreased water resources in dry parts of the region4 are justified. Here we show, through analysis of multidecadal groundwater hydrographs across sub-Saharan Africa, that levels of aridity dictate the predominant recharge processes, whereas local hydrogeology influences the type and sensitivity of precipitation-recharge relationships. Recharge in some humid locations varies by as little as five per cent (by coefficient of variation) across a wide range of annual precipitation values. Other regions, by contrast, show roughly linear precipitation-recharge relationships, with precipitation thresholds (of roughly ten millimetres or less per day) governing the initiation of recharge. These thresholds tend to rise as aridity increases, and recharge in drylands is more episodic and increasingly dominated by focused recharge through losses from ephemeral overland flows. Extreme annual recharge is commonly associated with intense rainfall and flooding events, themselves often driven by large-scale climate controls. Intense precipitation, even during years of lower overall precipitation, produces some of the largest years of recharge in some dry subtropical locations. Our results therefore challenge the 'high certainty' consensus regarding decreasing water resources4 in such regions of sub-Saharan Africa. The potential resilience of groundwater to climate variability in many areas that is revealed by these precipitation-recharge relationships is essential for informing reliable predictions of climate-change impacts and adaptation strategies.


Subject(s)
Groundwater/analysis , Rain , Africa South of the Sahara , Desert Climate , Droughts/statistics & numerical data
10.
Nature ; 569(7754): 59-65, 2019 05.
Article in English | MEDLINE | ID: mdl-31043729

ABSTRACT

Although anthropogenic climate change is expected to have caused large shifts in temperature and rainfall, the detection of human influence on global drought has been complicated by large internal variability and the brevity of observational records. Here we address these challenges using reconstructions of the Palmer drought severity index obtained with data from tree rings that span the past millennium. We show that three distinct periods are identifiable in climate models, observations and reconstructions during the twentieth century. In recent decades (1981 to present), the signal of greenhouse gas forcing is present but not yet detectable at high confidence. Observations and reconstructions differ significantly from an expected pattern of greenhouse gas forcing around mid-century (1950-1975), coinciding with a global increase in aerosol forcing. In the first half of the century (1900-1949), however, a signal of greenhouse-gas-forced change is robustly detectable. Multiple observational datasets and reconstructions using data from tree rings confirm that human activities were probably affecting the worldwide risk of droughts as early as the beginning of the twentieth century.


Subject(s)
Climate Change/statistics & numerical data , Droughts/statistics & numerical data , Human Activities , Water/analysis , Aerosols , History, 20th Century , History, 21st Century , Hydrology , Models, Theoretical , Plants/metabolism , Principal Component Analysis , Water/metabolism
11.
Nature ; 573(7772): 126-129, 2019 09.
Article in English | MEDLINE | ID: mdl-31462776

ABSTRACT

Through the lens of evolution, climate change is an agent of natural selection that forces populations to change and adapt, or face extinction. However, current assessments of the risk of biodiversity associated with climate change1 do not typically take into account how natural selection influences populations differently depending on their genetic makeup2. Here we make use of the extensive genome information that is available for Arabidopsis thaliana and measure how manipulation of the amount of rainfall affected the fitness of 517 natural Arabidopsis lines that were grown in Spain and Germany. This allowed us to directly infer selection along the genome3. Natural selection was particularly strong in the hot-dry location in Spain, where 63% of lines were killed and where natural selection substantially changed the frequency of approximately 5% of all genome-wide variants. A significant portion of this climate-driven natural selection of variants was predictable from signatures of local adaptation (R2 = 29-52%), as genetic variants that were found in geographical areas with climates more similar to the experimental sites were positively selected. Field-validated predictions across the species range indicated that Mediterranean and western Siberian populations-at the edges of the environmental limits of this species-currently experience the strongest climate-driven selection. With more frequent droughts and rising temperatures in Europe4, we forecast an increase in directional natural selection moving northwards from the southern end of Europe, putting many native A. thaliana populations at evolutionary risk.


Subject(s)
Acclimatization/genetics , Arabidopsis/genetics , Climate Change/statistics & numerical data , Genome, Plant/genetics , Selection, Genetic , Arabidopsis/growth & development , Droughts/statistics & numerical data , Genetic Fitness , Geographic Mapping , Germany , Global Warming/statistics & numerical data , Polymorphism, Single Nucleotide/genetics , Rain , Reproducibility of Results , Siberia , Spain
12.
Nature ; 574(7776): 90-94, 2019 10.
Article in English | MEDLINE | ID: mdl-31578485

ABSTRACT

Groundwater is the world's largest freshwater resource and is critically important for irrigation, and hence for global food security1-3. Already, unsustainable groundwater pumping exceeds recharge from precipitation and rivers4, leading to substantial drops in the levels of groundwater and losses of groundwater from its storage, especially in intensively irrigated regions5-7. When groundwater levels drop, discharges from groundwater to streams decline, reverse in direction or even stop completely, thereby decreasing streamflow, with potentially devastating effects on aquatic ecosystems. Here we link declines in the levels of groundwater that result from groundwater pumping to decreases in streamflow globally, and estimate where and when environmentally critical streamflows-which are required to maintain healthy ecosystems-will no longer be sustained. We estimate that, by 2050, environmental flow limits will be reached for approximately 42 to 79 per cent of the watersheds in which there is groundwater pumping worldwide, and that this will generally occur before substantial losses in groundwater storage are experienced. Only a small decline in groundwater level is needed to affect streamflow, making our estimates uncertain for streams near a transition to reversed groundwater discharge. However, for many areas, groundwater pumping rates are high and environmental flow limits are known to be severely exceeded. Compared to surface-water use, the effects of groundwater pumping are markedly delayed. Our results thus reveal the current and future environmental legacy of groundwater use.


Subject(s)
Geographic Mapping , Groundwater/analysis , Rain , Rivers/chemistry , Water Movements , Water Supply/methods , Agricultural Irrigation/methods , Aquatic Organisms , Climate Change , Desiccation , Droughts/statistics & numerical data , Ecosystem , Fresh Water/analysis , Internationality , Models, Theoretical
13.
Nature ; 571(7764): 257-260, 2019 07.
Article in English | MEDLINE | ID: mdl-31217589

ABSTRACT

Increasing global food demand, low grain reserves and climate change threaten the stability of food systems on national to global scales1-5. Policies to increase yields, irrigation and tolerance of crops to drought have been proposed as stability-enhancing solutions1,6,7. Here we evaluate a complementary possibility-that greater diversity of crops at the national level may increase the year-to-year stability of the total national harvest of all crops combined. We test this crop diversity-stability hypothesis using 5 decades of data on annual yields of 176 crop species in 91 nations. We find that greater effective diversity of crops at the national level is associated with increased temporal stability of total national harvest. Crop diversity has stabilizing effects that are similar in magnitude to the observed destabilizing effects of variability in precipitation. This greater stability reflects markedly lower frequencies of years with sharp harvest losses. Diversity effects remained robust after statistically controlling for irrigation, fertilization, precipitation, temperature and other variables, and are consistent with the variance-scaling characteristics of individual crops required by theory8,9 for diversity to lead to stability. Ensuring stable food supplies is a challenge that will probably require multiple solutions. Our results suggest that increasing national effective crop diversity may be an additional way to address this challenge.


Subject(s)
Crops, Agricultural/classification , Crops, Agricultural/supply & distribution , Food Supply/methods , Food Supply/statistics & numerical data , Geography , Agricultural Irrigation/statistics & numerical data , Biodiversity , Calorimetry , Crops, Agricultural/growth & development , Droughts/statistics & numerical data , Fertilizers/supply & distribution , Models, Theoretical , Probability , Rain , Temperature
16.
Nature ; 556(7699): 99-102, 2018 04 05.
Article in English | MEDLINE | ID: mdl-29562235

ABSTRACT

Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.


Subject(s)
Biodiversity , Biomass , Climate Change , Droughts , Forests , Trees/classification , Trees/physiology , Carbon Sequestration , Dehydration , Droughts/statistics & numerical data , New England , Seasons , Southeastern United States , Trees/growth & development , Trees/metabolism , Water/analysis , Water/metabolism
17.
Proc Natl Acad Sci U S A ; 118(43)2021 10 26.
Article in English | MEDLINE | ID: mdl-34663728

ABSTRACT

Fire is a common ecosystem process in forests and grasslands worldwide. Increasingly, ignitions are controlled by human activities either through suppression of wildfires or intentional ignition of prescribed fires. The southeastern United States leads the nation in prescribed fire, burning ca. 80% of the country's extent annually. The COVID-19 pandemic radically changed human behavior as workplaces implemented social-distancing guidelines and provided an opportunity to evaluate relationships between humans and fire as fire management plans were postponed or cancelled. Using active fire data from satellite-based observations, we found that in the southeastern United States, COVID-19 led to a 21% reduction in fire activity compared to the 2003 to 2019 average. The reduction was more pronounced for federally managed lands, up to 41% below average compared to the past 20 y (38% below average compared to the past decade). Declines in fire activity were partly affected by an unusually wet February before the COVID-19 shutdown began in mid-March 2020. Despite the wet spring, the predicted number of active fire detections was still lower than expected, confirming a COVID-19 signal on ignitions. In addition, prescribed fire management statistics reported by US federal agencies confirmed the satellite observations and showed that, following the wet February and before the mid-March COVID-19 shutdown, cumulative burned area was approaching record highs across the region. With fire return intervals in the southeastern United States as frequent as 1 to 2 y, COVID-19 fire impacts will contribute to an increasing backlog in necessary fire management activities, affecting biodiversity and future fire danger.


Subject(s)
COVID-19/prevention & control , Pandemics , Physical Distancing , SARS-CoV-2 , Wildfires/prevention & control , Biodiversity , COVID-19/epidemiology , Droughts/statistics & numerical data , Ecosystem , Forests , Human Activities , Humans , Models, Statistical , Pandemics/prevention & control , Southeastern United States/epidemiology , Weather , Wildfires/statistics & numerical data
18.
Nature ; 548(7666): 202-205, 2017 08 09.
Article in English | MEDLINE | ID: mdl-28796213

ABSTRACT

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.


Subject(s)
Droughts/statistics & numerical data , Ecosystem , Internationality , Spatio-Temporal Analysis , Biodiversity , Carbon Dioxide/analysis , Carbon Sequestration , Droughts/history , Global Warming , History, 20th Century , History, 21st Century , Rain , Soil/chemistry , Temperature , Time Factors , Tropical Climate , Wildfires
19.
Nature ; 545(7653): 169-174, 2017 05 10.
Article in English | MEDLINE | ID: mdl-28492255

ABSTRACT

The high mountains of Asia-encompassing the Himalayas, the Hindu Kush, Karakoram, Pamir Alai, Kunlun Shan, and Tian Shan mountains-have the highest concentration of glaciers globally, and 800 million people depend in part on meltwater from them. Water stress makes this region vulnerable economically and socially to drought, but glaciers are a uniquely drought-resilient source of water. Here I show that these glaciers provide summer meltwater to rivers and aquifers that is sufficient for the basic needs of 136 million people, or most of the annual municipal and industrial needs of Pakistan, Tajikistan, Turkmenistan, Uzbekistan and Kyrgyzstan. During drought summers, meltwater dominates water inputs to the upper Indus and Aral river basins. Uncertainties in mountain precipitation are poorly known, but, given the magnitude of this water supply, predicted glacier loss would add considerably to drought-related water stress. Such additional water stress increases the risk of social instability, conflict and sudden, uncontrolled population migrations triggered by water scarcity, which is already associated with the large and rapidly growing populations and hydro-economies of these basins.


Subject(s)
Droughts/statistics & numerical data , Freezing , Ice Cover/chemistry , Water Supply/statistics & numerical data , Altitude , Asia , Droughts/economics , Groundwater , Hydrology , Kyrgyzstan , Politics , Rain , Rivers/chemistry , Seasons , Tajikistan , Temperature , Turkmenistan , Uncertainty , Uzbekistan , Water Supply/economics
20.
Water Sci Technol ; 87(11): 2756-2775, 2023 Jun.
Article in English | MEDLINE | ID: mdl-37318922

ABSTRACT

Reliable drought prediction plays a significant role in drought management. Applying machine learning models in drought prediction is getting popular in recent years, but applying the stand-alone models to capture the feature information is not sufficient enough, even though the general performance is acceptable. Therefore, the scholars tried the signal decomposition algorithm as a data pre-processing tool, and coupled it with the stand-alone model to build 'decomposition-prediction' model to improve the performance. Considering the limitations of using the single decomposition algorithm, an 'integration-prediction' model construction method is proposed in this study, which deeply combines the results of multiple decomposition algorithms. The model tested three meteorological stations in Guanzhong, Shaanxi Province, China, where the short-term meteorological drought is predicted from 1960 to 2019. The meteorological drought index selects the Standardized Precipitation Index on a 12-month time scale (SPI-12). Compared with stand-alone models and 'decomposition-prediction' models, the 'integration-prediction' models present higher prediction accuracy, smaller prediction error and better stability in the results. This new 'integration-prediction' model provides attractive value for drought risk management in arid regions.


Subject(s)
Droughts , Machine Learning , Meteorology , Algorithms , China , Droughts/statistics & numerical data , Meteorology/methods
SELECTION OF CITATIONS
SEARCH DETAIL