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Abstract
Shallow landslides are often triggered during rainfall events, which can increase subsurface soil water pressure and destabilize hillslopes. The likelihood of regional shallow landslide initiation is often assessed through a comparison of rainfall intensity and duration to pre-established thresholds. While informative for landslide warning, this exclusive focus on rainfall exceeding thresholds does not consider the meteorological conditions producing the rainfall. Here, we ask the question, are there common meteorological characteristics that lead to landslide triggering precipitation? We develop a catalog of 18 post-1995 widespread, impactful shallow landslide events occurring within 13 storms across California, USA, where initiation time could be constrained to a <=6-hour window. We examine storm characteristics during the landslide initiation window using atmospheric reanalysis products, radar observations, and quantitative precipitation estimates. We find that, while there are some common atmospheric characteristics across landslide events, they can occur under a range of atmospheric conditions. For example, all northern California landslide events assessed are associated with moderate to strong atmospheric rivers (ARs) while southern California landslides feature non-AR to strong AR conditions. The storm events evaluated herein share many characteristics of hydrologically important storms in California that did not necessarily result in landslides, thus atmospheric characteristics alone may not be sufficient to determine whether landslides will occur. However, documenting the characteristics of landslide-triggering storms defines the conditions under which landslides tend to occur, provides analog events that can be useful in forecast applications, helps to define future research directions relating atmospheric conditions and landslides, and supports interdisciplinary research efforts.
Abstract
Shallow landslides are often triggered during rainfall events, which can increase subsurface soil water pressure and destabilize hillslopes. The likelihood of regional shallow landslide initiation is often assessed through a comparison of rainfall intensity and duration to pre-established thresholds. While informative for landslide warning, this exclusive focus on rainfall exceeding thresholds does not consider the meteorological conditions producing the rainfall. Here, we ask the question, are there common meteorological characteristics that lead to landslide triggering precipitation? We develop a catalog of 18 post-1995 widespread, impactful shallow landslide events occurring within 13 storms across California, USA, where initiation time could be constrained to a <=6-hour window. We examine storm characteristics during the landslide initiation window using atmospheric reanalysis products, radar observations, and quantitative precipitation estimates. We find that, while there are some common atmospheric characteristics across landslide events, they can occur under a range of atmospheric conditions. For example, all northern California landslide events assessed are associated with moderate to strong atmospheric rivers (ARs) while southern California landslides feature non-AR to strong AR conditions. The storm events evaluated herein share many characteristics of hydrologically important storms in California that did not necessarily result in landslides, thus atmospheric characteristics alone may not be sufficient to determine whether landslides will occur. However, documenting the characteristics of landslide-triggering storms defines the conditions under which landslides tend to occur, provides analog events that can be useful in forecast applications, helps to define future research directions relating atmospheric conditions and landslides, and supports interdisciplinary research efforts.
Abstract
With the importance of agriculture to the Southern Great Plains (SGP), accurate knowledge of growing season (GS) temperatures and precipitation is critical. Previous research into GS precipitation and temperature maxima lead to the development of the asynchronous difference index (ADI) which identified positive and negative ADI growing seasons (GSs; March to September). The goal of this research is to further investigate the ADI within a specific agricultural region of the SGP, the winter wheat region, and to quantify the temporal evolution of temperature and precipitation during positive and negative ADI GSs. For this, Global Historical Climatology Network (GHCN) daily station data were analyzed across the GS (March to September) from 1900 to 2020. Results show that differences appear in the temperature and precipitation fields when comparing positive and negative GSs. Namely, positive (negative) ADI GSs show positive (negative) precipitation and negative (positive) temperature anomalies early in the GS, with these anomalies flipping in the later portion of the GS. Further, the results of this work show that the depicted changes in temperature and precipitation during positive and negative ADI GSs impact winter wheat yields. Overall, these results analyze the implications of positive and negative ADI GSs on the SGP climate, namely the impact of the seasonal variability of daily maximum temperature and precipitation on agriculture.
Abstract
With the importance of agriculture to the Southern Great Plains (SGP), accurate knowledge of growing season (GS) temperatures and precipitation is critical. Previous research into GS precipitation and temperature maxima lead to the development of the asynchronous difference index (ADI) which identified positive and negative ADI growing seasons (GSs; March to September). The goal of this research is to further investigate the ADI within a specific agricultural region of the SGP, the winter wheat region, and to quantify the temporal evolution of temperature and precipitation during positive and negative ADI GSs. For this, Global Historical Climatology Network (GHCN) daily station data were analyzed across the GS (March to September) from 1900 to 2020. Results show that differences appear in the temperature and precipitation fields when comparing positive and negative GSs. Namely, positive (negative) ADI GSs show positive (negative) precipitation and negative (positive) temperature anomalies early in the GS, with these anomalies flipping in the later portion of the GS. Further, the results of this work show that the depicted changes in temperature and precipitation during positive and negative ADI GSs impact winter wheat yields. Overall, these results analyze the implications of positive and negative ADI GSs on the SGP climate, namely the impact of the seasonal variability of daily maximum temperature and precipitation on agriculture.
Abstract
Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation P and temperature T footprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R 2 = 0.50 for May–September T). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change.
Significance Statement
We show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime.
Abstract
Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation P and temperature T footprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R 2 = 0.50 for May–September T). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change.
Significance Statement
We show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime.
Abstract
The effects of various strategies aimed at simultaneously promoting environmental conservation and human development are closely related to sustainable development regionally and globally. However, although the effects of many such strategies have been evaluated by ecologists and sociologists separately, their ability to simultaneously meet these two anticipated goals (i.e., environmental conservation and human development) at the fine spatial scale remains unclear. To answer this fundamental but crucial question, incorporating household and forest change data, we concurrently estimated the ecological and socioeconomic effects of two world-renowned Payment for Ecosystem Services (PES) programs (i.e., the Nature Forest Conservation Program, the Grain to Green Program) and nature-based tourism in 30 protected areas across 8 provinces in China. Here we showed a trade-off between the ecological and economic effects of two PES programs, while synergistic effects exist in the ecological and economic benefits of tourism. Attributes of household and protected areas significantly influenced economic and environmental benefits as well. Our research provides new insights into the complex effects of PES programs and tourism, and crucial information to support their adequate and sustainable implementation in China and the rest of the world.
Significance Statement
This work answers a fundamental but crucial question, that is, whether the policies commonly advocated to incorporate environmental conservation and human development can yield positive effects both for conservation and economic development. Our evaluation is also timely to inform some shortness (i.e., negligible economic effects, or the lack of expected positive economic benefits) and provides new insights (e.g., the implication of households and protected-areas attributes in conservation and economic outcomes) of Payment for Ecosystem Services (PES) programs and the complex effects of instruments in the context of multiple policies, particularly given the upcoming 2030 deadline for achieving the Sustainable Development goals (SDGs). We expected that implications in this study can provide important lessons for these two instruments, other PES programs, and other conservation and development instruments to support their adequate and sustainable implementation in China and beyond and to contribute to the achievement of relevant SDGs in the remaining years.
Abstract
The effects of various strategies aimed at simultaneously promoting environmental conservation and human development are closely related to sustainable development regionally and globally. However, although the effects of many such strategies have been evaluated by ecologists and sociologists separately, their ability to simultaneously meet these two anticipated goals (i.e., environmental conservation and human development) at the fine spatial scale remains unclear. To answer this fundamental but crucial question, incorporating household and forest change data, we concurrently estimated the ecological and socioeconomic effects of two world-renowned Payment for Ecosystem Services (PES) programs (i.e., the Nature Forest Conservation Program, the Grain to Green Program) and nature-based tourism in 30 protected areas across 8 provinces in China. Here we showed a trade-off between the ecological and economic effects of two PES programs, while synergistic effects exist in the ecological and economic benefits of tourism. Attributes of household and protected areas significantly influenced economic and environmental benefits as well. Our research provides new insights into the complex effects of PES programs and tourism, and crucial information to support their adequate and sustainable implementation in China and the rest of the world.
Significance Statement
This work answers a fundamental but crucial question, that is, whether the policies commonly advocated to incorporate environmental conservation and human development can yield positive effects both for conservation and economic development. Our evaluation is also timely to inform some shortness (i.e., negligible economic effects, or the lack of expected positive economic benefits) and provides new insights (e.g., the implication of households and protected-areas attributes in conservation and economic outcomes) of Payment for Ecosystem Services (PES) programs and the complex effects of instruments in the context of multiple policies, particularly given the upcoming 2030 deadline for achieving the Sustainable Development goals (SDGs). We expected that implications in this study can provide important lessons for these two instruments, other PES programs, and other conservation and development instruments to support their adequate and sustainable implementation in China and beyond and to contribute to the achievement of relevant SDGs in the remaining years.
Abstract
Harmful algae and cyanobacteria blooms are increasing in frequency and intensity in freshwater systems due to anthropogenic impacts such as nutrient loading in watersheds and engineered alterations of natural waterways. There are multiple physical factors that affect the conditions in a freshwater system that contribute to optimal habitats for harmful algae and toxin-producing cyanobacteria. A growing body of research shows that climate change stressors also are impacting water-body conditions that favor harmful algae and cyanobacteria species over other phytoplankton. The overgrowth of these organisms, or a “bloom,” increases the opportunity for exposure to toxins by humans, companion animals, livestock, and wildlife. As waters warm and precipitation patterns change over time, exposure to these blooms is projected to increase. Hence, it is important that states and tribes develop monitoring and reporting strategies as well as align governmental policies to protect their citizens and ecosystems within their jurisdiction. Currently, the policies and approaches taken to monitor and report on harmful algae and cyanobacteria blooms vary widely among states, and it is undetermined if any tribes have specific policies on harmful algae blooms. This paper synthesizes research on algal blooms in inland freshwater systems of the United States. This review examines how climate change contributes to trends in bloom frequency or severity and outlines approaches that states and tribes may use to monitor, report, and respond to harmful algae and cyanobacteria blooms.
Significance Statement
Inland bodies of freshwater supply drinking water for humans and animals, water for irrigating crops, habitats for aquatic species, places of cultural significance for Indigenous peoples, and other important functions. Many of these bodies of water have been polluted with runoff from industry, including agriculture, and already support harmful algal blooms during warm conditions. Hot extremes associated with climate change are expected to increase the occurrence and duration of harmful algal blooms, and in some places, initiate blooms where none have been recorded previously. These toxic blooms are harmful to people, companion animals, livestock, and wildlife. It is important to review the interconnections among biological, climate, and water systems to monitor blooms and alert the public about their toxin production.
Abstract
Harmful algae and cyanobacteria blooms are increasing in frequency and intensity in freshwater systems due to anthropogenic impacts such as nutrient loading in watersheds and engineered alterations of natural waterways. There are multiple physical factors that affect the conditions in a freshwater system that contribute to optimal habitats for harmful algae and toxin-producing cyanobacteria. A growing body of research shows that climate change stressors also are impacting water-body conditions that favor harmful algae and cyanobacteria species over other phytoplankton. The overgrowth of these organisms, or a “bloom,” increases the opportunity for exposure to toxins by humans, companion animals, livestock, and wildlife. As waters warm and precipitation patterns change over time, exposure to these blooms is projected to increase. Hence, it is important that states and tribes develop monitoring and reporting strategies as well as align governmental policies to protect their citizens and ecosystems within their jurisdiction. Currently, the policies and approaches taken to monitor and report on harmful algae and cyanobacteria blooms vary widely among states, and it is undetermined if any tribes have specific policies on harmful algae blooms. This paper synthesizes research on algal blooms in inland freshwater systems of the United States. This review examines how climate change contributes to trends in bloom frequency or severity and outlines approaches that states and tribes may use to monitor, report, and respond to harmful algae and cyanobacteria blooms.
Significance Statement
Inland bodies of freshwater supply drinking water for humans and animals, water for irrigating crops, habitats for aquatic species, places of cultural significance for Indigenous peoples, and other important functions. Many of these bodies of water have been polluted with runoff from industry, including agriculture, and already support harmful algal blooms during warm conditions. Hot extremes associated with climate change are expected to increase the occurrence and duration of harmful algal blooms, and in some places, initiate blooms where none have been recorded previously. These toxic blooms are harmful to people, companion animals, livestock, and wildlife. It is important to review the interconnections among biological, climate, and water systems to monitor blooms and alert the public about their toxin production.
Abstract
Cyanobacteria blooms are an increasing concern in U.S. freshwaters. Such blooms can produce nuisance conditions, deplete oxygen, and alter the food chain, and in some cases they may produce potent toxins, although many factors may modulate the relationships between biomass and toxin production. Cyanobacterial blooms are in turn associated with nutrient enrichment and warm water temperatures. Climate change is expected to increase water temperatures and, in many areas, surface runoff that can transport nutrient loads to lakes. While some progress has been made in short-term prediction of cyanobacterial bloom and toxin risk, the long-term projections of which lakes will become more vulnerable to such events as a result of climate change is less clear because of the complex interaction of multiple factors that affect bloom probability. We address this question by reviewing the literature to identify risk factors that increase lake vulnerability to cyanobacterial blooms and evaluating how climate change may alter these factors across the sample of conterminous U.S. lakes contained in the 2007 National Lakes Assessment. Results provide a national-scale assessment of where and in which types of lakes climate change will likely increase the overall risk of cyanobacterial blooms, rather than finer-scale prediction of expected cyanobacterial and toxin levels in individual lakes. This information can be used to guide climate change adaptation planning, including monitoring and management efforts to minimize the effects of increased cyanobacterial prevalence.
Significance Statement
Cyanobacteria blooms and associated algal toxins are an increasing problem in U.S. freshwater lakes and reservoirs. Climate change may further increase bloom frequency and severity. We survey the literature on relationships between bloom formation and climate. These relationships are combined with projections of future climate and lake response to develop indices of where and in what types of lakes such blooms are most likely to increase relative to current conditions. The results can help to focus monitoring and management measures to mitigate potential impacts on human health, wildlife, and aquatic biota.
Abstract
Cyanobacteria blooms are an increasing concern in U.S. freshwaters. Such blooms can produce nuisance conditions, deplete oxygen, and alter the food chain, and in some cases they may produce potent toxins, although many factors may modulate the relationships between biomass and toxin production. Cyanobacterial blooms are in turn associated with nutrient enrichment and warm water temperatures. Climate change is expected to increase water temperatures and, in many areas, surface runoff that can transport nutrient loads to lakes. While some progress has been made in short-term prediction of cyanobacterial bloom and toxin risk, the long-term projections of which lakes will become more vulnerable to such events as a result of climate change is less clear because of the complex interaction of multiple factors that affect bloom probability. We address this question by reviewing the literature to identify risk factors that increase lake vulnerability to cyanobacterial blooms and evaluating how climate change may alter these factors across the sample of conterminous U.S. lakes contained in the 2007 National Lakes Assessment. Results provide a national-scale assessment of where and in which types of lakes climate change will likely increase the overall risk of cyanobacterial blooms, rather than finer-scale prediction of expected cyanobacterial and toxin levels in individual lakes. This information can be used to guide climate change adaptation planning, including monitoring and management efforts to minimize the effects of increased cyanobacterial prevalence.
Significance Statement
Cyanobacteria blooms and associated algal toxins are an increasing problem in U.S. freshwater lakes and reservoirs. Climate change may further increase bloom frequency and severity. We survey the literature on relationships between bloom formation and climate. These relationships are combined with projections of future climate and lake response to develop indices of where and in what types of lakes such blooms are most likely to increase relative to current conditions. The results can help to focus monitoring and management measures to mitigate potential impacts on human health, wildlife, and aquatic biota.
Abstract
Rapidly warming temperatures in the Arctic are driving increasing tundra vegetation productivity, evidenced in both the satellite derived normalized difference vegetation index (NDVI) imagery and field studies. These trends, however, are not uniformly positive across the circumpolar Arctic. One notable region of negative linear NDVI trends that have persisted over the last 15 years is southwest Alaska’s Yukon–Kuskokwim Delta (YKD). Negative NDVI trends in the YKD region appear inconsistent with our understanding since tundra vegetation is temperature-limited and air temperatures have increased on the YKD. Analysis over a 40-yr record from 1982 to 2021 reveals distinct decadal variability in the NDVI time series, which continues to produce negative linear trends. Similar decadal variability is also evident in summer warmth and 100-km coastal zone spring sea ice concentrations. This suggests that decadal climate variations can dominate the trends of NDVI through their influence on the drivers of tundra vegetation, namely, coastal sea ice concentrations and summer warmth. The relationships among sea ice, summer warmth, and NDVI have changed over the 40-yr record. Seasonality analysis since 1982 shows declining sea ice concentration in spring is followed by trends of increasing temperatures, but weakly declining NDVI during the growing season. An additional key finding is that since early 2010s, the relationships between sea ice concentration and summer warmth, and sea ice concentration and NDVI have strengthened, while the relationship between NDVI and summer warmth has weakened, indicating that temperature may no longer be the primary limiting factor for Arctic tundra vegetation on the YKD.
Significance Statement
This paper addresses a curiosity of regional Arctic climate change, which is that despite increasing temperatures, spatially and temporally declining trends of vegetation productivity on the Yukon–Kuskokwim Delta appear in satellite data. This study bridges our understanding of Arctic climate relationships at varying scales and informs questions about how these relationships may change in the future.
Abstract
Rapidly warming temperatures in the Arctic are driving increasing tundra vegetation productivity, evidenced in both the satellite derived normalized difference vegetation index (NDVI) imagery and field studies. These trends, however, are not uniformly positive across the circumpolar Arctic. One notable region of negative linear NDVI trends that have persisted over the last 15 years is southwest Alaska’s Yukon–Kuskokwim Delta (YKD). Negative NDVI trends in the YKD region appear inconsistent with our understanding since tundra vegetation is temperature-limited and air temperatures have increased on the YKD. Analysis over a 40-yr record from 1982 to 2021 reveals distinct decadal variability in the NDVI time series, which continues to produce negative linear trends. Similar decadal variability is also evident in summer warmth and 100-km coastal zone spring sea ice concentrations. This suggests that decadal climate variations can dominate the trends of NDVI through their influence on the drivers of tundra vegetation, namely, coastal sea ice concentrations and summer warmth. The relationships among sea ice, summer warmth, and NDVI have changed over the 40-yr record. Seasonality analysis since 1982 shows declining sea ice concentration in spring is followed by trends of increasing temperatures, but weakly declining NDVI during the growing season. An additional key finding is that since early 2010s, the relationships between sea ice concentration and summer warmth, and sea ice concentration and NDVI have strengthened, while the relationship between NDVI and summer warmth has weakened, indicating that temperature may no longer be the primary limiting factor for Arctic tundra vegetation on the YKD.
Significance Statement
This paper addresses a curiosity of regional Arctic climate change, which is that despite increasing temperatures, spatially and temporally declining trends of vegetation productivity on the Yukon–Kuskokwim Delta appear in satellite data. This study bridges our understanding of Arctic climate relationships at varying scales and informs questions about how these relationships may change in the future.
