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At least 1,531 records · Page 85Linked to original sources

USGS2014

Yield of sediment in relation to mean annual precipitation

Effective mean annual precipitation is related to sediment yield from drainage basins throughout the climatic regions of the United States. Sediment yield is a maximum at about 10 to 14 inches of precipitation, decreasing sharply on both sides of this maximum in one case owing to a deficiency of runoff and in the other to increased density of vegetation. Data are presented illustrating the increase in bulk density of vegetation with increased annual precipitation and the relation of relative erosion to vegetative density. It is suggested that the effect of a climatic change on sediment yield depends not only upon direction of climate change, but also on the climate before the change. Sediment concentration in runoff is shown to increase with decreased annual precipitation, suggesting further that a decrease in precipitation will cause stream channel aggradation

Eos, Transactions, American Geophysical Union↗

USGS2017

Multidirectional abundance shifts among North American birds and the relative influence of multifaceted climate factors

Shifts in species distributions are major fingerprint of climate change. Examining changes in species abundance structures at a continental scale enables robust evaluation of climate change influences, but few studies have conducted these evaluations due to limited data and methodological constraints. In this study, we estimate temporal changes in abundance from North American Breeding Bird Survey data at the scale of physiographic strata to examine the relative influence of different components of climatic factors and evaluate the hypothesis that shifting species distributions are multidirectional in resident bird species in North America. We quantify the direction and velocity of the abundance shifts of 57 permanent resident birds over 44 years using a centroid analysis. For species with significant abundance shifts in the centroid analysis, we conduct a more intensive correlative analysis to identify climate components most strongly associated with composite change of abundance within strata. Our analysis focus on two contrasts: the relative importance of climate extremes vs. averages, and of temperature vs. precipitation in strength of association with abundance change. Our study shows that 36 species had significant abundance shifts over the study period. The average velocity of the centroid is 5.89 km·yr −1 . The shifted distance on average covers 259 km, 9% of range extent. Our results strongly suggest that the climate change fingerprint in studied avian distributions is multidirectional. Among 6 directions with significant abundance shifts, the northwestward shift was observed in the largest number of species ( n = 13). The temperature/average climate model consistently has greater predictive ability than the precipitation/extreme climate model in explaining strata‐level abundance change. Our study shows heterogeneous avian responses to recent environmental changes. It highlights needs for more species‐specific approaches to examine contributing factors to recent distributional changes and for comprehensive conservation planning for climate change adaptation.

Global Change Biology↗

USGS2017

Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape

It is generally accepted that climate change will stress coldwater species such as Pacific salmon. However, it is unclear what aspect of altered thermal regimes (e.g., warmer winters, springs, summers, or increased variability) will have the greatest effect, and what role the spatial properties of river networks play. Thermally diverse habitats may afford protection from climate change by providing opportunities for aquatic organisms to find and use habitats with optimal conditions for growth. We hypothesized that climate‐altered thermal regimes will change growth and timing of life history events such as emergence or migration but that changes will be moderated in topologically complex stream networks where opportunities to thermoregulate are more readily available to mobile animals. Because climate change effects on populations are spatially variable and contingent upon physiological optima, assessments of risk must take a spatially explicit approach. We developed a spatially structured individual‐based model for Chinook Salmon ( Oncorhynchus tshawytscha ) in which movement decisions and growth were governed by water temperature and conspecific density. We evaluated growth and phenology (timing of egg emergence and smolting) under a variety of thermal regimes (each having a different minimum, rate of warming, maximum, and variability) and in three network shapes of increasing spatial complexity. Across networks, fish generally grew faster and were capable of smolting earlier in warmer scenarios where water temperatures experienced by fish were closer to optimal; however, growth decreased for some fish. We found that salmon size and smolt date responded more strongly to warmer springs and summers than to warmer winters or increased variability. Fish in the least complex network grew faster and were ready to smolt earlier than fish in the more spatially complex network shapes in the contemporary thermal regime; patterns were similar but less clear in warmer thermal regimes. Our results demonstrate that network topology may influence how fish respond to thermal landscapes, and this information will be useful for incorporating a spatiotemporal context into conservation decisions that promote long‐term viability of salmon in a changing climate.

Ecosphere↗

USGS2009

Planning for an uncertain future - Monitoring, integration, and adaptation

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Scientific Investigations Report↗

USGS2011

U.S. Geological Survey development of a Landsat-based Fire Disturbance ECV

The United States Geological Survey (USGS) is the steward of the Landsat archive which includes satellite imagery dating back to 1972. The United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change have specified requirements to systematically observe atmosphere, ocean, and land characteristics, or Essential Climate Variables (ECVs). The Global Climate Observing System has developed formal specifications for ECVs that are technically and economically feasible for systematic ECV observation. Fire Disturbance is one of the 14 Terrestrial ECVs, and is defined as “burned area” supplemented by “active fires” and fire radiated power” (FRP) measurements. Landsat’s temporal resolution and sensor characteristics make it suitable for mapping burned area, but not suitable for monitoring active fires or FRP. In this paper, we describe the development of a database for calibration, verification, and validation of a Landsat-based burned area ECV, along with the algorithms to be tested against that database.

Conference Paper↗

USGS2022

Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem

Species' response to rapid climate change can be measured through shifts in timing of recurring biological events, known as phenology. The Gulf of Maine is one of the most rapidly warming regions of the ocean, and thus an ideal system to study phenological and biological responses to climate change. A better understanding of climate-induced changes in phenology is needed to effectively and adaptively manage human-wildlife conflicts. Using data from a 20+ year marine mammal observation program, we tested the hypothesis that the phenology of large whale habitat use in Cape Cod Bay has changed and is related to regional-scale shifts in the thermal onset of spring. We used a multi-season occupancy model to measure phenological shifts and evaluate trends in the date of peak habitat use for North Atlantic right ( Eubalaena glacialis ), humpback ( Megaptera novaeangliae ), and fin ( Balaenoptera physalus ) whales. The date of peak habitat use shifted by +18.1 days (0.90 days/year) for right whales and +19.1 days (0.96 days/year) for humpback whales. We then evaluated interannual variability in peak habitat use relative to thermal spring transition dates (STD), and hypothesized that right whales, as planktivorous specialist feeders, would exhibit a stronger response to thermal phenology than fin and humpback whales, which are more generalist piscivorous feeders. There was a significant negative effect of western region STD on right whale habitat use, and a significant positive effect of eastern region STD on fin whale habitat use indicating differential responses to spatial seasonal conditions. Protections for threatened and endangered whales have been designed to align with expected phenology of habitat use. Our results show that whales are becoming mismatched with static seasonal management measures through shifts in their timing of habitat use, and they suggest that effective management strategies may need to alter protections as species adapt to climate change.

Massachusetts↗

USGS2017

Drought, multi-seasonal climate, and wildfire in northern New Mexico

Wildfire is increasingly a concern in the USA, where 10 million acres burned in 2015. Climate is a primary driver of wildfire, and understanding fire-climate relationships is crucial for informing fire management and modeling the effects of climate change on fire. In the southwestern USA, fire-climate relationships have been informed by tree-ring data that extend centuries prior to the onset of fire exclusion in the late 1800s. Variability in cool-season precipitation has been linked to fire occurrence, but the effects of the summer North American monsoon on fire are less understood, as are the effects of climate on fire seasonality. We use a new set of reconstructions for cool-season (October–April) and monsoon-season (July–August) moisture conditions along with a large new fire scar dataset to examine relationships between multi-seasonal climate variability, fire extent, and fire seasonality in the Jemez Mountains, New Mexico (1599–1899 CE). Results suggest that large fires burning in all seasons are strongly influenced by the current year cool-season moisture, but fires burning mid-summer to fall are also influenced by monsoon moisture. Wet conditions several years prior to the fire year during the cool season, and to a lesser extent during the monsoon season, are also important for spring through late-summer fires. Persistent cool-season drought longer than 3 years may inhibit fires due to the lack of moisture to replenish surface fuels. This suggests that fuels may become increasingly limiting for fire occurrence in semi-arid regions that are projected to become drier with climate change.

New Mexico↗

USGS2024

Disease-smart climate adaptation for wildlife management and conservation

Climate change is a well-documented driver and threat multiplier of infectious disease in wildlife populations. However, wildlife disease management and climate-change adaptation have largely operated in isolation. To improve conservation outcomes, we consider the role of climate adaptation in initiating or exacerbating the transmission and spread of wildlife disease and the deleterious effects thereof, as illustrated through several case studies. We offer insights into best practices for disease-smart adaptation, including a checklist of key factors for assessing disease risks early in the climate adaptation process. By assessing risk, incorporating uncertainty, planning for change, and monitoring outcomes, natural resource managers and conservation practitioners can better prepare for and respond to wildlife disease threats in a changing climate.

Frontiers in Ecology and the Environment↗

USGS2016

Demography of an apex predator at the edge of its range: impacts of changing sea ice on polar bears in Hudson Bay

Changes in the abundance and distribution of wildlife populations are common consequences of historic and contemporary climate change. Some Arctic marine mammals, such as the polar bear ( Ursus maritimus ), may be particularly vulnerable to such changes due to the loss of Arctic sea ice. We evaluated the impacts of environmental variation on demographic rates for the Western Hudson Bay (WH), polar bear subpopulation from 1984 to 2011 using live-recapture and dead-recovery data in a Bayesian implementation of multistate capture–recapture models. We found that survival of female polar bears was related to the annual timing of sea ice break-up and formation. Using estimated vital rates (e.g., survival and reproduction) in matrix projection models, we calculated the growth rate of the WH subpopulation and projected population responses under different environmental scenarios while accounting for parametric uncertainty, temporal variation, and demographic stochasticity. Our analysis suggested a long-term decline in the number of bears from 1185 (95% Bayesian credible interval [BCI] = 993–1411) in 1987 to 806 (95% BCI = 653–984) in 2011. In the last 10 yr of the study, the number of bears appeared stable due to temporary stability in sea ice conditions (mean population growth rate for the period 2001–2010 = 1.02, 95% BCI = 0.98–1.06). Looking forward, we estimated long-term growth rates for the WH subpopulation of ~1.02 (95% BCI = 1.00–1.05) and 0.97 (95% BCI = 0.92–1.01) under hypothetical high and low sea ice conditions, respectively. Our findings support previous evidence for a demographic linkage between sea ice conditions and polar bear population dynamics. Furthermore, we present a robust framework for sensitivity analysis with respect to continued climate change (e.g., to inform scenario planning) and for evaluating the combined effects of climate change and management actions on the status of wildlife populations.

Hudson Bay↗

USGS2019

Vulnerability of subsistence systems due to social and environmental change: A case study in the Yukon-Kuskokwim Delta, Alaska

Arctic Indigenous communities have been classified as highly vulnerable to climate change impacts. The remoteness of Arctic communities, their dependence upon local species and habitats, and the historical marginalization of Indigenous peoples, enhances this characterization of vulnerability. However, vulnerability is a result of diverse historical, social, economic, political, cultural, institutional, natural resource, and environmental conditions and processes and is not easily reduced to a single metric. Furthermore, despite the widespread characterization of vulnerability, Arctic Indigenous communities are extremely resilient as evidenced by subsistence institutions that have been developed over thousands of years. We explored the vulnerability of subsistence systems in the Cup’ik village of Chevak and Yup’ik village of Kotlik through the lens of the strong seasonal dimensions of resource availability. In the context of subsistence harvesting in Alaskan Native Villages, vulnerability may be determined by analyzing the exposure of subsistence resources to climate change impacts, the sensitivity of a community to those impacts, and the capacity of subsistence institutions to absorb these impacts. Subsistence resources, their seasonality, and perceived impacts to these resources were investigated via semi-structured interviews and participatory mapping-calendar workshops. Results suggest that while these communities are experiencing disproportionate impacts of climate change, Indigenous ingenuity and adaptability provide an avenue for culturally appropriate adaptation strategies. However, despite this capacity for resiliency, rapid socio-cultural changes have the potential to be a barrier to community adaptation and the recent, ongoing shifts in seasonal weather patterns, may make seasonally specific subsistence adaptations to landscape particularly vulnerable.

Alaska↗

USGS2015

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

California↗

USGS2009

Selected achievements, science directions, and new opportunities for the WEBB small watershed research program

Over nearly two decades, the Water, Energy, and Biogeochemical Budgets (WEBB) small watershed research program of the U.S. Geological Survey (USGS) has documented how water and solute fluxes, nutrient, carbon, and mercury dynamics, and weathering and sediment transport respond to natural and humancaused drivers, including climate, climate change, and atmospheric deposition. Together with a continued and increasing focus on the effects of climate change, more investigations are needed that examine ecological effects (e.g., evapotranspiration, nutrient uptake) and responses (e.g., species abundances, biodiversity) that are coupled with the physical and chemical processes historically observed in the WEBB program. Greater use of remote sensing, geographic modeling, and habitat/watershed modeling tools is needed, as is closer integration with the USGS-led National Phenology Network. Better understanding of process and system response times is needed. The analysis and observation of land-use and climate change effects over time should be improved by pooling data obtained by the WEBB program during the last two decades with data obtained earlier and (or) concurrently from other research and monitoring studies conducted at or near the five WEBB watershed sites. These data can be supplemented with historical and paleo-environmental information, such as could be obtained from tree rings and lake cores. Because of the relatively pristine nature and small size of its watersheds, the WEBB program could provide process understanding and basic data to better characterize and quantify ecosystem services and to develop and apply indicators of ecosystem health. In collaboration with other Federal and State watershed research programs, the WEBB program has an opportunity to contribute to tracking the short-term dynamics and long-term evolution of ecosystem services and health indicators at a multiplicity of scales across the landscape.

Conference Paper↗

USGS2015

Web based visualization of large climate data sets

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Environmental Modelling and Software↗

USGS2021

Multivariate Bayesian clustering using covariate-informed components with application to boreal vegetation sensitivity

Climate change is impacting both the distribution and abundance of vegetation, especially in far northern latitudes. The effects of climate change are different for every plant assemblage and vary heterogeneously in both space and time. Small changes in climate could result in large vegetation responses in sensitive assemblages but weak responses in robust assemblages. But, patterns and mechanisms of sensitivity and robustness are not yet well understood, largely due to a lack of long-term measurements of climate and vegetation. Fortunately, observations are sometimes available across a broad spatial extent. We develop a novel statistical model for a multivariate response based on unknown cluster-specific effects and covariances, where cluster labels correspond to sensitivity and robustness. Our approach utilizes a prototype model for cluster membership that offers flexibility while enforcing smoothness in cluster probabilities across sites with similar characteristics. We demonstrate our approach with an application to vegetation abundance in Alaska, USA, in which we leverage the broad spatial extent of the study area as a proxy for unrecorded historical observations. In the context of the application, our approach yields interpretable site-level cluster labels associated with assemblage-level sensitivity and robustness without requiring strong a priori assumptions about the drivers of climate sensitivity.

Alaska↗

USGS2014

Water quality and algal community dynamics of three deepwater lakes in Minnesota utilizing CE-QUAL-W2 models

Water quality, habitat, and fish in Minnesota lakes will potentially be facing substantial levels of stress in the coming decades primarily because of two stressors: (1) land-use change (urban and agricultural) and (2) climate change. Several regional and statewide lake modeling studies have identified the potential linkages between land-use and climate change on reductions in the volume of suitable lake habitat for coldwater fish populations. In recent years, water-resource scientists have been making the case for focused assessments and monitoring of sentinel systems to address how these stress agents change lakes over the long term. Currently in Minnesota, a large-scale effort called “Sustaining Lakes in a Changing Environment” is underway that includes a focus on monitoring basic watershed, water quality, habitat, and fish indicators of 24 Minnesota sentinel lakes across a gradient of ecoregions, depths, and nutrient levels. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Department of Natural Resources, developed predictive water quality models to assess water quality and habitat dynamics of three select deepwater lakes in Minnesota. The three lakes (Lake Carlos in Douglas County, Elk Lake in Clearwater County, and Trout Lake in Cook County) were assessed under recent (2010–11) meteorological conditions. The three selected lakes contain deep, coldwater habitats that remain viable during the summer months for coldwater fish species. Hydrodynamics and water-quality characteristics for each of the three lakes were simulated using the CE-QUAL-W2 model, which is a carbon-based, laterally averaged, two-dimensional water-quality model. The CE-QUAL-W2 models address the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of temperature and oxygen in lakes. The CE-QUAL-W2 models for all three lakes successfully predicted water temperature, on the basis of the two metrics of absolute mean error and root mean square error, using measured inputs of water temperature and nutrients. One of the main calibration tools for CE-QUAL-W2 model development was the vertical profile temperature data, available for all three lakes. For all three lakes, the absolute mean error and root mean square error were less than 1.0 degree Celsius and 1.2 degrees Celsius, respectively, for the different depth ranges used for vertical profile comparisons. In Lake Carlos, simulated water temperatures compared better to measured water temperatures in the epilimnion than in the hypolimnion. The reverse was true for the other two lakes, Elk Lake and Trout Lake, where the simulated results were slightly better for the hypolimnion than the epilimnion. The model also was used to approximate the location of the thermocline throughout the simulation periods, approximately April to November, in all three lake models. Deviations between the simulated and measured water temperatures in the vertical lake profile commonly were because of an offset in the timing of thermocline shifts rather than the simulated results missing thermocline shifts altogether.

Minnesota↗

USGS2025

Climate-Smart Siting for renewable energy expansion

A massive expansion of renewable energy (RE) is underway to meet the world’s climate goals. Although RE serves to reduce threats from climate change, it can also pose threats to species whose current and future ranges intersect with RE installations. Here, we propose a “Climate-Smart Siting” framework for addressing potential conflicts between RE expansion and biodiversity conservation. The framework engenders authentic consultation with affected and disadvantaged communities throughout and uses overlay and optimization routines to identify focal areas now and in the future where RE development poses promise and peril as species’ ranges shift in response to climate change. We use this framework to demonstrate methods, identify decision outcomes, and discuss market-based levers for aligning RE expansion with the United Nations Global Biodiversity Framework now and as climate change progresses. In the face of the climate crisis, a Climate-Smart Siting strategy could help create solutions without causing further harm to biodiversity and human communities.

iScience↗

USGS2010

U.S. Geological Survey activities related to American Indians and Alaska Natives: Fiscal years 2007 and 2008

In the late 1800s, John Wesley Powell, the second director of the U.S. Geological Survey (USGS), followed his interest in the tribes of the Great Basin and Colorado Plateau and studied their cultures, languages, and surroundings. From that early time, the USGS has recognized the importance of Native knowledge and living in harmony with nature as complements to the USGS mission to better understand the Earth. Combining traditional ecological knowledge with empirical studies allows the USGS and Native American governments, organizations, and people to increase their mutual understanding and respect for this land. The USGS is the earth and natural science bureau within the U.S. Department of the Interior (DOI) and is not responsible for regulations or land management. Climate change is a major current issue affecting Native lives and traditions throughout the United States. Climate projections for the coming century indicate an increasing probability for more frequent and more severe droughts in the Southwest, including the Navajo Nation. Erosion has claimed Native homes in Alaska. Fish have become inedible due to diseases that turn their flesh mushy. Native people who rely on or who are culturally sustained by hunting, fishing, and using local plants are living with climate change now. The traditional knowledge of Native peoples enriches and confirms the work of USGS scientists. The results are truly synergistic-greater than the sum of their parts. Traditional ecological knowledge is respected and increasingly used in USGS studies-when the holders of that knowledge choose to share it. The USGS respects the rights of Native people to maintain their patrimony of traditional ecological knowledge. The USGS studies can help Tribes, Native organizations, and natural resource professionals manage Native lands and resources with the best available unbiased data and information that can be added to their traditional knowledge. Wise Native leaders have noted that traditional ecological knowledge includes the connections between Earth and her denizens. From this perspective, it is the connections among these ?relatives? that needs to be nurtured. This perspective on nature is finding new adherents among Natives and non-Natives as understanding of climate change and other environmental conditions deepens. Although this report uses the term ?resources,? the USGS, through its interdisciplinary research, acknowledges the interconnectedness of the Earth and the things that live upon it.

Circular↗

USGS2011

Seasonal timing of first rain storms affects rare plant population dynamics

A major challenge in forecasting the ecological consequences of climate change is understanding the relative importance of changes to mean conditions vs. changes to discrete climatic events, such as storms, frosts, or droughts. Here we show that the first major storm of the growing season strongly influences the population dynamics of three rare and endangered annual plant species in a coastal California (USA) ecosystem. In a field experiment we used moisture barriers and water addition to manipulate the timing and temperature associated with first major rains of the season. The three focal species showed two- to fivefold variation in per capita population growth rates between the different storm treatments, comparable to variation found in a prior experiment imposing eightfold differences in season-long precipitation. Variation in germination was a major demographic driver of how two of three species responded to the first rains. For one of these species, the timing of the storm was the most critical determinant of its germination, while the other showed enhanced germination with colder storm temperatures. The role of temperature was further supported by laboratory trials showing enhanced germination in cooler treatments. Our work suggests that, because of species-specific cues for demographic transitions such as germination, changes to discrete climate events may be as, if not more, important than changes to season-long variables.

Ecology↗