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At least 1,045 records · Page 58Linked to original sources
USGS2017

Mangrove species' responses to winter air temperature extremes in China

The global distribution and diversity of mangrove forests is greatly influenced by the frequency and intensity of winter air temperature extremes. However, our understanding of how different mangrove species respond to winter temperature extremes has been lacking because extreme freezing and chilling events are, by definition, relatively uncommon and also difficult to replicate experimentally. In this study, we investigated species-specific variation in mangrove responses to winter temperature extremes in China. In 10 sites that span a latitudinal gradient, we quantified species-specific damage and recovery following a chilling event, for mangrove species within and outside of their natural range (i.e., native and non-native species, respectively). To characterize plant stress, we measured tree defoliation and chlorophyll fluorescence approximately one month following the chilling event. To quantify recovery, we measured chlorophyll fluorescence approximately nine months after the chilling event. Our results show high variation in the geographic- and species-specific responses of mangroves to winter temperature extremes. While many species were sensitive to the chilling temperatures (e.g., Bruguiera sexangula and species in the Sonneratia and Rhizophora genera), the temperatures during this event were not cold enough to affect certain species (e.g., Kandelia obovata , Aegiceras corniculatum , Avicennia marina, and Bruguiera gymnorrhiza ). As expected, non-native species were less tolerant of winter temperature extremes than native species. Interestingly, tidal inundation modulated the effects of chilling. In comparison with other temperature-controlled mangrove range limits across the world, the mangrove range limit in China is unique due to the combination of the following three factors: (1) Mangrove species diversity is comparatively high; (2) winter air temperature extremes, rather than means, are particularly intense and play an important ecological role; and (3) due to afforestation and restoration efforts, several species of non-native mangroves have been introduced beyond their natural range limits. Hence, from a global perspective, mangroves in China provide valuable opportunities to advance understanding of the effects of freezing and chilling temperatures on mangroves. Within the context of climate change, our findings provide a foundation for better understanding and preparing for mangrove species-specific responses to future changes in the duration and intensity of winter temperature extremes.

Ecosphere↗
USGS2017

Linear and nonlinear effects of temperature and precipitation on ecosystem properties in tidal saline wetlands

Climate greatly influences the structure and functioning of tidal saline wetland ecosystems. However, there is a need to better quantify the effects of climatic drivers on ecosystem properties, particularly near climate-sensitive ecological transition zones. Here, we used climate- and literature-derived ecological data from tidal saline wetlands to test hypotheses regarding the influence of climatic drivers (i.e., temperature and precipitation regimes) on the following six ecosystem properties: canopy height, biomass, productivity, decomposition, soil carbon density, and soil carbon accumulation. Our analyses quantify and elucidate linear and nonlinear effects of climatic drivers. We quantified positive linear relationships between temperature and above-ground productivity and strong positive nonlinear (sigmoidal) relationships between (1) temperature and above-ground biomass and canopy height and (2) precipitation and canopy height. Near temperature-controlled mangrove range limits, small changes in temperature are expected to trigger comparatively large changes in biomass and canopy height, as mangrove forests grow, expand, and, in some cases, replace salt marshes. However, within these same transition zones, temperature-induced changes in productivity are expected to be comparatively small. Interestingly, despite the significant above-ground height, biomass, and productivity relationships across the tropical–temperate mangrove–marsh transition zone, the relationships between temperature and soil carbon density or soil carbon accumulation were not significant. Our literature review identifies several ecosystem properties and many regions of the world for which there are insufficient data to fully evaluate the influence of climatic drivers, and the identified data gaps can be used by scientists to guide future research. Our analyses indicate that near precipitation-controlled transition zones, small changes in precipitation are expected to trigger comparatively large changes in canopy height. However, there are scant data to evaluate the influence of precipitation on other ecosystem properties. There is a need for more decomposition data across climatic gradients, and to advance understanding of the influence of changes in precipitation and freshwater availability, additional ecological data are needed from tidal saline wetlands in arid climates. Collectively, our results can help scientists and managers better anticipate the linear and nonlinear ecological consequences of climate change for coastal wetlands.

Ecosphere↗
USGS2018

A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language

Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.

Ecosphere↗
USGS2019

Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): A cross-system analysis

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis ) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.

Ecosphere↗
USGS2021

Exploration of the 2016 Yellowstone River fish kill and proliferative kidney disease in wild fish populations

Proliferative kidney disease (PKD) is an emerging disease that recently resulted in a large mortality event of salmonids in the Yellowstone River (Montana, USA). Total PKD fish mortalities in the Yellowstone River were estimated in the tens of thousands, which resulted in a multi‐week river closure and an estimated economic loss of US$500,000. This event shocked scientists, managers, and the public, as this was the first occurrence of the disease in the Yellowstone River, the only reported occurrence of the disease in Montana in the past 25 yr, and arguably the largest wild PKD fish kill in the world. To understand why the Yellowstone River fish kill occurred, we used molecular and historical data to evaluate evidence for several hypotheses: Was the causative parasite Tetracapsuloides bryosalmonae a novel invader, was the fish kill associated with a unique parasite strain, and/or was the outbreak caused by unprecedented environmental conditions? We found that T. bryosalmonae is widely distributed in Montana and have documented occurrence of this parasite in archived fish collected in the Yellowstone River prior to the fish kill. T. bryosalmonae had minimal phylogeographic population structure, as the DNA of parasites sampled from the Yellowstone River and distant water bodies were very similar. These results suggest that T. bryosalmonae could be endemic in Montana. Due to data limitations, we could not reject the hypothesis that the fish kill was caused by a novel and more virulent genetic strain of the parasite. Finally, we found that single‐year environmental conditions are insufficient to explain the cause of the 2016 Yellowstone River PKD outbreak. Other regional rivers where we documented T. bryosalmonae had similar or even more extreme conditions than the Yellowstone River and similar or more extreme conditions have occurred in the Yellowstone River in the recent past, yet mass PKD mortalities have not been documented in either instance. We conclude by placing these results and unresolved hypotheses into the broader context of international research on T. bryosalmonae and PKD, which strongly suggests that a better understanding of bryozoans, the primary host of T. bryosalmonae , is required for better ecosystem understanding.

Montana↗
USGS2021

Responses of American black bears to spring resources

In temperate regions of the world, food resources are seasonally limited, which causes some wildlife species to seek out nutrient-rich resources to better meet their caloric needs. Animals that utilize high-quality resources may reap fitness benefits as they prepare for mating, migration, or hibernation. American black bears ( Ursus americanus ) are omnivores that consume both plant and animal food resources to meet macronutrient needs. Black bears capitalize on high-quality food resources, such as soft mast in summer and hard mast during autumn, but we know less about the importance of resource quality during spring. Therefore, we sought to understand the relationship between the spatiotemporal variation in the availability of food and resource selection of black bears during spring. We also aimed to infer potential changes in foraging tactics, from opportunistic foraging to more active selection. Although black bears are described as opportunistic omnivores, we hypothesized they select areas with high-quality forage when available. We instrumented 7 black bears with GPS collars in 2017 and 2018 and estimated fine-scale resource selection with integrated step-selection functions. We found evidence that black bear movements were influenced by forage quality of vegetative food resources. However, we failed to find evidence that black bears actively alter their movements to take advantage of seasonal neonate elk. Although black bears represent a substantial cause of mortality for neonate elk, we found that black bears likely feed on neonates encountered opportunistically while traveling between patches of high-quality forage. Few studies have shown evidence of an omnivorous species capitalizing on spatiotemporal variation in forage quality, yet our data suggest this may be an important strategy for species with diverse diets, particularly where resources are seasonally limited.

Montana, Wyoming↗
USGS2022

Maximizing species distribution model performance when using historical occurrences and variables of varying persistency

Occurrence data used to build species distribution models often include historical records from locations in which the species no longer exists. When these records are paired with contemporary environmental values that no longer represent the conditions the species experienced, the model creates false associations that hurt predictive performance. The extent of mismatching increases with the number of historical occurrences and with inclusion of environmental variables that are prone to change over time. Indeed, the mismatch between occurrence data and contemporaneous environmental variables is a common dilemma when modeling rare or cryptic species, especially those of conservation concern that were once more abundant. Herein, we assess (1) the impact of historical occurrences on model performance across three sets of environmental variables of increasing persistency and (2) the performance of models built using selected-historical occurrences from locations that showed evidence of limited environmental change over time. Concepts are tested on federally listed flatwoods salamanders, reflecting real-world conservation management efforts. We predicted that, compared to other occurrence sets, (1) historical occurrences would perform best with environmental variables that were more persistent, (2) recent occurrences would perform best when the environmental variables were more impersistent, and that (3) our selected-historical occurrences would perform best with a combination of persistent and impersistent variables. Our results showed the expected inversion of model performance of recent and historical occurrences across environmental variables of increasing persistency when evaluated by correct predictions. However, the inversion was not seen in area under the curve performance, in which historical occurrences outperformed recent occurrence models across all variable sets. Selected-historical occurrences did not notably improve performance over all-historical occurrences in any metric or variable set. To maximize utility and performance, modelers could acknowledge potential trade-offs from inclusion of historical occurrences and consider number and age of recent and historical occurrences available, the persistency of environmental variables considered, and how their conservation goals are reflected in model design and evaluation, particularly with respect to sensitivity versus specificity. Our study lends support for inclusion of historical occurrences, with the potential exception of mostly impersistent variables when sensitivity is the highest priority.

Alabama, Florida, Georgia, South Carolina↗
USGS2022

Controlling invasive fish in fluctuating environments: Model analysis of common carp (Cyprinus carpio) in a shallow lake

Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.

Oregon↗
USGS2022

The researcher's lament: Why do they ignore my science?

The researcher's lament is shared by many environmental and conservation scientists who complain about the little support they receive for their research proposals during the review and selection process. Understandably, any hopes of having their anticipated scientific findings applied toward the formulation of environmental management decisions or natural resource policy action are shattered. They attribute this lack of endorsement to shortcomings and limitations among decision makers and proposal selection officials when, in many cases, the rejection of project proposals is often a function of a handful of self-inflicted failures by applied scientists who anchor themselves stubbornly to doomed approaches. Familiar deficiencies in their research proposals perpetuate the disconnect between the enterprise of science and real-world resource management challenges. Researchers themselves can affect conditions that turn up the appetite for their scientific endeavors as a more meaningful component of the decision-making process, namely, to stage and deliver science that is more readily "actionable." Perhaps it is time for them to consider a course correction to improve the viability of their actionable science proposals. A few basic steps may help rejigger the science planning process in this direction and, consequently, help avoid the researcher's lament. The likelihood of gaining support during the proposal review and award adjudication process, and securing practical application of scientific products, increases when the products are (1) the result of active engagement of researchers with decision makers; (2) better connected to social and political priorities; (3) clearly designed to inform specific management decisions; and (4) tailored to fit the needs of targeted end users. These considerations and activities exist beyond the comfort zone of many environmental or conservation scientists. Yet, those who adopt them will spend less time lamenting rejection and become more influential in the production of actionable knowledge.

Ecosphere↗
USGS2022

Tough places and safe spaces: Can refuges save salmon from a warming climate?

The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual-based simulation model to evaluate the buffering potential of cold-water thermal refuges for anadromous salmon and trout ( Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold-water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold-water thermal refuges and mainstem temperatures. Use of cold-water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree-days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy-conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy-conserving phenotypic space contracted by 7%–23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool- and cold-water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change.

Idaho, Oregon, Washington↗
USGS2024

Geographic distribution of feather δ34S in Europe

Geographic distribution models of environmentally stable isotopes (the so-called “isoscapes”) are widely employed in animal ecology, and wildlife forensics and conservation. However, the application of isoscapes is limited to elements and regions for which the spatial patterns have been estimated. Here, we focused on the ubiquitous yet less commonly used stable sulfur isotopes (δ 34 S). To predict the European δ 34 S isoscape, we used 242 feather samples from Eurasian Reed Warbler ( Acrocephalus scirpaceus ) formed at 69 European wetland sites. We quantified the relationships between sample δ 34 S and environmental covariates using a random forest regression model and applied the model to predict the geographic distribution of δ 34 S. We also quantified within-site variation in δ 34 S and complementarity with other isotopes on both individual and isoscape levels. The predicted feather δ 34 S isoscape shows only slight differences between the central and southern parts of Europe while the coastal regions were most enriched in 34 S. The most important covariates of δ 34 S were distance to coastline, surface elevation, and atmospheric concentrations of SO 2 gases. The absence of a systematic spatial pattern impedes the application of the δ 34 S isoscape, but high complementarity with other isoscapes advocates the combination of multiple isoscapes to increase the precision of animal tracing. Feather δ 34 S compositions showed considerable within-site variation with highest values in inland parts of Europe, likely attributed to wetland anaerobic conditions and redox sensitivity of sulfur. The complex European geography and topography as well as using δ 34 S samples from wetlands may contribute to the absence of a systematic spatial gradient of δ 34 S values in Europe. We thus encourage future studies to focus on the geographic distribution of δ 34 S using tissues from diverse taxa collected in various habitats over large land masses in the world (i.e., Africa, South America, or East Asia).

Ecosphere↗
USGS2024

Assessing giant sequoia mortality and regeneration following high-severity wildfire

Fire is a critical driver of giant sequoia ( Sequoiadendron giganteum [Lindl.] Buchholz) regeneration. However, fire suppression combined with the effects of increased temperature and severe drought has resulted in fires of an intensity and size outside of the historical norm. As a result, recent mega-fires have killed a significant portion of the world's sequoia population (13%–19%), and uncertainty surrounds whether severely affected groves will be able to recover naturally, potentially leading to a loss of grove area. To assess the likelihood of natural recovery, we collected spatially explicit data assessing mortality, crown condition, and regeneration within four giant sequoia groves that were severely impacted by the SQF- (2020) and KNP-Complex (2021) wildfires within Sequoia and Kings Canyon National Parks. In total, we surveyed 5.9 ha for seedlings and assessed the crown condition of 1104 giant sequoias. To inform management, we used a statistical methodology that robustly quantifies the uncertainty in inherently “noisy” seedling data and takes advantage of readily available remote sensing metrics that would make our findings applicable to other recently burned groves. A loss of giant sequoia grove area would be a consequence of giant sequoia tree mortality followed by a failure of natural regeneration. We found that areas that experienced very high-severity fire (above ~800 RdNBR) are at substantial risk for the loss of grove area, with tree mortality rapidly increasing and giant sequoia seedling density simultaneously decreasing with fire severity. Such high-severity areas comprised 17.8, 142.0, 14.6, 1.6 ha and ~90%, ~14%, ~53%, and ~27% of Board Camp, Redwood Mountain, Suwanee, and New Oriole Lake groves, respectively. In all sampling areas, we found that seedling densities fell far below the average density measured after prescribed fires, where seedling numbers were almost certainly adequate to maintain giant sequoia populations and postfire conditions were more in keeping with historical norms. Importantly, spatial pattern is also important in assessing the risk of grove loss, and in two groves, Suwanee and New Oriole Lake, the high-severity patches were not always contiguous, potentially making some areas more resilient to regeneration failure due to the proximity of surviving trees.

Ecosphere↗
USGS2024

Seasonal resource selection of a grassland bird in a dynamic landscape: Importance of a heterogeneous landscape

Habitat loss and fragmentation are a growing threat to wildlife, and a better understanding of these landscape processes is needed to mitigate their effects on species populations. Grassland biomes are among the most imperiled ecosystems in the world, and grassland birds are experiencing significant population declines in North America. Understanding how species respond to differences in resource availabilities across spatiotemporal extents is critical to determining animals' distributions. Here, we investigated the relationship of landscape attributes to spatiotemporal distribution of a grassland bird, the ring-necked pheasant ( Phasianus colchicus ), which has experienced population declines in the Midwest, USA. Pheasant declines have been attributed to two anthropogenic stressors, land use change and climate change. In this study, we evaluated the effect of landscape attributes (composition and configuration) on the home-range size and resource selection of pheasants. We used a 95% fixed kernel estimator to estimate home-range size and identified scales at which landscape features influenced home-range sizes. We quantified landscape features within radii of 250, 500, and 1000 m (i.e., local to broader spatial scales) from the home-range center. We also used resource selection functions to predict the home-range placement (second order) and resource selection within home ranges (third order) of pheasants during winter, pre-nesting, and nesting seasons. We developed multi-scale predictions of pheasant resource selection and identified wetlands, grasslands, Conservation Reserve Program (CRP) grasslands, and small grains as land cover types used by pheasants to fulfill their life requirements. Our results indicated home ranges were more likely to be in a landscape with more CRP, wetlands, and grasslands; more connected grasslands; and a greater number of grassland patches. Pheasants also selected heterogeneous landscape and avoided row crops at both orders of selection. Maintaining habitat heterogeneity, by managing landscapes composed of a high proportion of grasslands and CRP surrounded by small grains and wetlands, could enhance the benefits of local management practices for pheasants. Collectively, insights obtained from our study can advance habitat conservation efforts for similar grassland birds and consequently are of broad utility to biologists and wildlife managers.

South Dakota↗
USGS2026

Holistic understanding of uncertainty for collaborative and proactive global change decision making

Global change is accelerating and pushing the planet's ecosystems beyond the range of historical observations, creating increasing uncertainty in future system conditions. Despite general agreement that proactive environmental action is warranted, environmental decision conversations often end by identifying additional data needed to reduce uncertainty before taking novel action. Given the inherent uncertainty in complex issues such as global change, quantitative data alone are likely insufficient to support proactive environmental action. Holistic understanding of uncertainty includes scientific quantification of uncertainty paired with emotional responses and transcendental grounding to help people work together toward proactive action in uncertain decision contexts. Holistic understanding arises from the four ways in which humans perceive the world, termed the Four Realms: Physical (e.g., how I observe), Mental (e.g., how I think), Emotional (e.g., how I feel), and Transcendental (e.g., how I connect to greater meaning or purpose). Environmental scientists and decision makers are generally trained in Physical and Mental Realm observation and analysis, but not in how to apply Emotional and Transcendental Realm understanding. Emotional and Transcendental processing occurs in scientists and decision makers whether it is acknowledged or not and contributes to different people interpreting the same information in different ways. Thus, when the role of Emotional and Transcendental Realms in an individual's interpretation process is not understood, it can derail conversations and perpetuate the status quo. Explicitly recognizing all Four Realms can bring people together across differences and inspire shared, novel decision making even in increasing uncertainty. To illustrate the benefits of holistic understanding, we share stories from our experiences in environmental decision contexts. Because accessing the Four Realms requires experiential and embodied techniques, while still relying on core scientific tenets of observation and analysis, we also present techniques for readers to learn to feel their own emotional understanding and connect to their own transcendental understanding. Holistic understanding can enhance data-driven decisions by recognizing that human responses to uncertainty inherently include interactions between emotions, thoughts, transcendental connections, and behavior. Ultimately, holistic understanding can help anchor data-driven decisions in intra- and interpersonal connections, inspiring action in the face of uncertainty.

Ecosphere↗
USGS2016

Mangrove expansion and contraction at a poleward range limit: Climate extremes and land-ocean temperature gradients

Within the context of climate change, there is a pressing need to better understand the ecological implications of changes in the frequency and intensity of climate extremes. Along subtropical coasts, less frequent and warmer freeze events are expected to permit freeze-sensitive mangrove forests to expand poleward and displace freeze-tolerant salt marshes. Here, our aim was to better understand the drivers of poleward mangrove migration by quantifying spatiotemporal patterns in mangrove range expansion and contraction across land-ocean temperature gradients. Our work was conducted in a freeze-sensitive mangrove-marsh transition zone that spans a land-ocean temperature gradient in one of the world's most wetland-rich regions (Mississippi River Deltaic Plain; Louisiana, USA). We used historical air temperature data (1893-2014), alternative future climate scenarios, and coastal wetland coverage data (1978-2011) to investigate spatiotemporal fluctuations and climate-wetland linkages. Our analyses indicate that changes in mangrove coverage have been controlled primarily by extreme freeze events (i.e., air temperatures below a threshold zone of -6.3 to -7.6 °C). We expect that in the past 121 years, mangrove range expansion and contraction has occurred across land-ocean temperature gradients. Mangrove resistance, resilience, and dominance were all highest in areas closer to the ocean where temperature extremes were buffered by large expanses of water and saturated soil. Under climate change, these areas will likely serve as local hotspots for mangrove dispersal, growth, range expansion, and displacement of salt marsh. Collectively, our results show that the frequency and intensity of freeze events across land-ocean temperature gradients greatly influences spatiotemporal patterns of range expansion and contraction of freeze-sensitive mangroves. We expect that, along subtropical coasts, similar processes govern the distribution and abundance of other freeze-sensitive organisms. In broad terms, our findings can be used to better understand and anticipate the ecological effects of changing winter climate extremes, especially within the transition zone between tropical and temperate climates.

Louisiana↗
USGS2017

A global database of ant species abundances

What forces structure ecological assemblages? A key limitation to general insights about assemblage structure is the availability of data that are collected at a small spatial grain (local assemblages) and a large spatial extent (global coverage). Here, we present published and unpublished data from 51,388 ant abundance and occurrence records of more than 2693 species and 7953 morphospecies from local assemblages collected at 4212 locations around the world. Ants were selected because they are diverse and abundant globally, comprise a large fraction of animal biomass in most terrestrial communities, and are key contributors to a range of ecosystem functions. Data were collected between 1949 and 2014, and include, for each geo-referenced sampling site, both the identity of the ants collected and details of sampling design, habitat type and degree of disturbance. The aim of compiling this dataset was to provide comprehensive species abundance data in order to test relationships between assemblage structure and environmental and biogeographic factors. Data were collected using a variety of standardised methods, such as pitfall and Winkler traps, and will be valuable for studies investigating large-scale forces structuring local assemblages. Understanding such relationships is particularly critical under current rates of global change. We encourage authors holding additional data on systematically collected ant assemblages, especially those in dry and cold, and remote areas, to contact us and contribute their data to this growing dataset.

Ecology↗
USGS2017

Holy flux: Spatial and temporal variation in massive pulses of emerging insect biomass from western U.S. rivers

The river stonefly, Pteronarcys californica (aka salmonfly), is an iconic insect in rivers of western North America due to its large size and its support of economically important species like wild trout (Nehring et al. 2011). Their emergence generates a large economic subsidy to local communities, as anglers from around the world travel to western rivers to fish the salmonfly “hatch” (e.g., Willoughby 2013). Salmonflies, which have a 4-yr lifespan in the central Rocky Mountains (Nehring et al. 2011), emerge en masse during 1 week in late spring (Sheldon 1999), and more than 20 terrestrial species, including humans, are known to eat adult salmonflies (Muttkowski 1925, Sutton 1985, Rockwell et al. 2009). How they influence populations of insectivores or the broader river-riparian ecosystem is unknown; this itself is an issue because salmonflies are disappearing from some rivers (Nehring et al. 2011).

Ecology↗
USGS2021

Recursive Bayesian computation facilitates adaptive optimal design in ecological studies

Optimal design procedures provide a framework to leverage the learning generated by ecological models to flexibly and efficiently deploy future monitoring efforts. At the same time, Bayesian hierarchical models have become widespread in ecology and offer a rich set of tools for ecological learning and inference. However, coupling these methods with an optimal design framework can become computationally intractable. Recursive Bayesian computation offers a way to substantially reduce this computational burden, making optimal design accessible for modern Bayesian ecological models. We demonstrate the application of so-called prior-proposal recursive Bayes to optimal design using a simulated data binary regression and the real-world example of monitoring and modeling sea otters in Glacier Bay, Alaska. These examples highlight the computational gains offered by recursive Bayesian methods and the tighter fusion of monitoring and science that those computational gains enable.

Ecology↗