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At least 793 records · Page 44Linked to original sources
USGS2017

Causal mechanisms of soil organic matter decomposition: Deconstructing salinity and flooding impacts in coastal wetlands

Coastal wetlands significantly contribute to global carbon storage potential. Sea-level rise and other climate change-induced disturbances threaten coastal wetland sustainability and carbon storage capacity. It is critical that we understand the mechanisms controlling wetland carbon loss so that we can predict and manage these resources in anticipation of climate change. However, our current understanding of the mechanisms that control soil organic matter decomposition, in particular the impacts of elevated salinity, are limited, and literature reports are contradictory. In an attempt to improve our understanding of these complex processes, we measured root and rhizome decomposition and developed a causal model to identify and quantify the mechanisms that influence soil organic matter decomposition in coastal wetlands that are impacted by sea-level rise. We identified three causal pathways: 1) a direct pathway representing the effects of flooding on soil moisture, 2) a direct pathway representing the effects of salinity on decomposer microbial communities and soil biogeochemistry, and 3) an indirect pathway representing the effects of salinity on litter quality through changes in plant community composition over time. We used this model to test the effects of alternate scenarios on the response of tidal freshwater forested wetlands and oligohaline marshes to short- and long-term climate-induced disturbances of flooding and salinity. In tidal freshwater forested wetlands, the model predicted less decomposition in response to drought, hurricane salinity pulsing, and long-term sea-level rise. In contrast, in the oligohaline marsh, the model predicted no change in response to sea-level rise, and increased decomposition following a drought or a hurricane salinity pulse. Our results show that it is critical to consider the temporal scale of disturbance and the magnitude of exposure when assessing the effects of salinity intrusion on carbon mineralization in coastal wetlands. Here we identify three causal mechanisms that can reconcile disparities between long-term and short-term salinity impacts on organic matter decomposition.

Ecology↗
USGS1999

Exotic plant species invade hot spots of native plant diversity

Some theories and experimental studies suggest that areas of low plant species richness may be invaded more easily than areas of high plant species richness. We gathered nested-scale vegetation data on plant species richness, foliar cover, and frequency from 200 1-m 2 subplots (20 1000-m 2 modified-Whittaker plots) in the Colorado Rockies (USA), and 160 1-m 2 subplots (16 1000-m 2 plots) in the Central Grasslands in Colorado, Wyoming, South Dakota, and Minnesota (USA) to test the generality of this paradigm. At the 1-m 2 scale, the paradigm was supported in four prairie types in the Central Grasslands, where exotic species richness declined with increasing plant species richness and cover. At the 1-m 2 scale, five forest and meadow vegetation types in the Colorado Rockies contradicted the paradigm; exotic species richness increased with native-plant species richness and foliar cover. At the 1000-m 2 plot scale (among vegetation types), 83% of the variance in exotic species richness in the Central Grasslands was explained by the total percentage of nitrogen in the soil and the cover of native plant species. In the Colorado Rockies, 69% of the variance in exotic species richness in 1000-m 2 plots was explained by the number of native plant species and the total percentage of soil carbon. At landscape and biome scales, exotic species primarily invaded areas of high species richness in the four Central Grasslands sites and in the five Colorado Rockies vegetation types. For the nine vegetation types in both biomes, exotic species cover was positively correlated with mean foliar cover, mean soil percentage N, and the total number of exotic species. These patterns of invasibility depend on spatial scale, biome and vegetation type, spatial autocorrelation effects, availability of resources, and species-specific responses to grazing and other disturbances. We conclude that: (1) sites high in herbaceous foliar cover and soil fertility, and hot spots of plant diversity (and biodiversity), are invasible in many landscapes; and (2) this pattern may be more closely related to the degree resources are available in native plant communities, independent of species richness. Exotic plant invasions in rare habitats and distinctive plant communities pose a significant challenge to land managers and conservation biologists.

Ecological Monographs↗
USGS2000

Sensitivity of species habitat-relationship model performance to factors of scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service's Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area <0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of Spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 - minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 - percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy.

Idaho↗
USGS2011

Soil carbon sequestration potential for "grain for green" project in Loess Plateau, China

Conversion of cropland into perennial vegetation land can increase soil organic carbon (SOC) accumulation, which might be an important mitigation measure to sequester carbon dioxide from the atmosphere. The “Grain for Green” project, one of the most ambitious ecological programmes launched in modern China, aims at transforming the low-yield slope cropland into grassland and woodland. The Loess Plateau in China is the most important target of this project due to its serious soil erosion. The objectives of this study are to answer three questions: (1) what is the rate of the SOC accumulation for this “Grain for Green” project in Loess Plateau? (2) Is there a difference in SOC sequestration among different restoration types, including grassland, shrub and forest? (3) Is the effect of restoration types on SOC accumulation different among northern, middle and southern regions of the Loess Plateau? Based on analysis of the data collected from the literature conducted in the Loess Plateau, we found that SOC increased at a rate of 0.712 TgC/year in the top 20 cm soil layer for 60 years under this project across the entire Loess Plateau. This was a relatively reliable estimation based on current data, although there were some uncertainties. Compared to grassland, forest had a significantly greater effect on SOC accumulation in middle and southern Loess Plateau but had a weaker effect in the northern Loess Plateau. There were no differences found in SOC sequestration between shrub and grassland across the entire Loess Plateau. Grassland had a stronger effect on SOC sequestration in the northern Loess Plateau than in the middle and southern regions. In contrast, forest could increase more SOC in the middle and southern Loess Plateau than in the northern Loess Plateau, whereas shrub had a similar effect on SOC sequestration across the Loess Plateau. Our results suggest that the “Grain for Green” project can significantly increase the SOC storage in Loess Plateau, and it is recommended to expand grassland and shrub areas in the northern Loess Plateau and forest in the middle and southern Loess Plateau to enhance the SOC sequestration in this area.

Environmental Management↗
USGS2024

Restoration treatments enhance tree growth and alter climatic constraints during extreme drought

The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients. We used tree-ring data from a system of replicated, long-term (>20 years) experiments in the southwestern United States to evaluate the effects of forest restoration treatments (i.e., evidence-based thinning and burning) on annual growth rates (i.e., basal area increment; BAI) of ponderosa pine ( Pinus ponderosa ), a broadly distributed and heavily managed species in western North America. The study sites were established at the onset of the most extreme drought event in at least 1200 years and span much of the climatic niche of Rocky Mountain ponderosa pine. Across sites, tree-level BAI increased due to treatment, where trees in treated units grew 133.1% faster than trees in paired, untreated units. Likewise, trees in treated units grew an average of 85.6% faster than their pre-treatment baseline levels (1985 to ca. 2000), despite warm, dry conditions in the post-treatment period (ca. 2000–2018). Variation in the local competitive environment promoted variation in BAI, and larger trees were the fastest-growing individuals, irrespective of treatment. Tree thinning and prescribed fire altered the climatic constraints on growth, decreasing the effects of belowground moisture availability and increasing the effects of atmospheric evaporative demand over multi-year timescales. Our results illustrate that restoration treatments can enhance tree-level growth across sites spanning ponderosa pine's climatic niche, even during recent, extreme drought events. However, shifting climatic constraints, combined with predicted increases in evaporative demand in the southwestern United States, suggest that the beneficial effects of such treatments on tree growth may wane over the upcoming decades.

Arizona, Colorado, Nevada, New Mexico, Texas↗
USGS2026

Recovery trajectories of surface fuels and forest trees following prescribed fire in low elevation conifer forests of California and southern Oregon

Background Prescribed fire is commonly used to manage surface fuels and stand structure in dry coniferous forests in the western United States. While the effectiveness of prescribed fire to manage fuel loads and live forest structure has been well documented, less is known about the shape of recovery trajectories more than a decade following treatment. We used up to 30 years of longitudinal observations from > 180 monitoring plots treated with a single prescribed fire-only treatment across six national parks in California and Oregon to compare competing recovery trajectory models: generalized linear models (GLM) that presumed exponential trajectories over time, generalized additive models (GAM) that had maximum flexibility to fit responses, and generalized Michaelis–Menten models that describe an asymptotic recovery trajectory. Results The Michaelis–Menten model had the lowest median RMSE of the fuel recovery models, with predicted recovery times and maximal fuel loads tending to increase with increasing fuel particle size. However, predictive performance was similar between model forms. GAM best predicted forest structure, showing that stem density of live overstory trees (> 15 cm stem diameter) declined immediately following prescribed fire without appreciable postfire accumulation. Results for live stem biomass were similar, but with less pronounced reductions. Conclusions We found that reductions in surface fuel biomass from a single prescribed fire-only treatment can last for more than a decade for some fuel types. Our analysis also demonstrates that asymptotic models reasonably describe surface fuel recovery trajectories. However, we lack the evidence to definitively conclude that asymptotic models best describe postfire recovery, even with repeated observations of up to three decades postfire. We also found that stem density and biomass of live trees with stem diameter > 15 cm both declined in the first few years immediately following the fire, after which they remained relatively unchanged for the remainder of the observation period.

California, Oregon↗
USGS2011

Using digital photography to examine grazing in montane meadows

Cattle ( Bos taurus ) numbers on national forests are allocated based on allotment grazing capacity, but spatial patterns of timing and density at smaller scales are difficult to assess. However, it is often in meadows or riparian areas that grazing may affect hydrology, biodiversity, and other important ecosystem characteristics. To explore real-time animal presence in montane meadows we distributed 18 digital cameras across nine sites in the Sierra National Forest, California. Our objectives were to document seasonal and diurnal presence of both cattle and mule deer ( Odocoileus hemionus ), identify the effects of three fencing treatments on animal distribution, and test digital photography as a tool for documenting cattle presence. We recorded 409 399 images during daylight hours for two grazing seasons, and we identified 5 084 and 24 482 cattle "marks" (instances of animal occurrence) in 2006 and 2007, respectively. Deer presence was much lower, with 331 marks in 2006 and 598 in 2007. Morning cattle presence was highest before 0800 hours both years (13.7% and 15.4% of total marks for 2006 and 2007, respectively). Marks decreased until 1100 hours and then increased around 1400 hours and remained relatively stable until 1900 hours. Marks then rose precipitously, with >20% of total marks recorded after 1900 hours both years. Deer presence was less than 10% per hour until 1800 hours, when >20% of total marks were recorded after this time both years. Among treatments, cattle marks were highest outside fences at partially fenced meadows, and deer were highest within completely fenced meadows. Our experience suggests that cameras are not viable tools for meadow monitoring due to variation captured within meadows and the time and effort involved in image processing and review.

Rangeland Ecology and Management↗
USGS2018

Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R 2 = 0.77, RMSE = 7%), annual grasses (R 2 = 0.70, RMSE = 21%), perennial grasses (R 2 = 0.36, RMSE = 12%), forbs (R 2 = 0.52, RMSE = 6%), bare earth or litter (R 2 = 0.49, RMSE = 19%), and the biomass of shrubs (R 2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R 2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous methods applying TLS to vegetation inventory. Improving application of TLS to studies of shrub-steppe ecosystems will serve immediate management needs by enhancing vegetation inventories, environmental modeling studies, and the ability to train broader datasets collected from air and space.

Idaho↗
USGS2022

Kirtland’s Warbler breeding productivity and habitat use in red pine-dominated habitat in Wisconsin, USA

During the breeding season, Kirtland’s Warblers ( Setophaga kirtlandii ) are strongly associated with young jack pine ( Pinus banksiana ) forests in northern Lower Michigan, USA. Since 2007, the species has been breeding in unusual habitat, red pine ( Pinus resinosa ) dominated plantations, in central Wisconsin, USA. Kirtland’s Warbler productivity and habitat use in red pine is not well understood, and the central Wisconsin population is at a range edge, a situation often associated with lower productivity. To compare range-edge and range-core populations, we estimated reproductive success and characterized habitat use of Kirtland’s Warblers in central Wisconsin red pine-dominated plantations during 2015–2017 using logistic regression models. We also monitored nests and fledgling success, and estimated nest survival using logistic exposure models. Trees were closer together and herbaceous vegetation was taller and denser within territories than at randomly located points outside of territories. Females selected nest sites with deeper dead ground vegetation and live vegetation that was taller and denser than was available at randomly located points within male territories. Nest success was not strongly influenced by within-patch habitat factors. Nest daily survival rate was 0.97 (95% CI = 0.94–0.98). The average number of young fledged per nest was between 2.5 and 2.8. Nest parasitism by Brown-headed Cowbirds ( Molothrus ater ) was 22.7%. Overall, reproductive success in the peripheral central Wisconsin breeding population of Kirtland’s Warblers that used red pine-dominated plantations was similar to that of Kirtland’s Warblers breeding in typical jack pine habitat in the range core. Young red pine-dominated habitat appears to approximate young jack pine in habitat quality for Kirtland’s Warblers, and this may provide managers some flexibility in habitat maintenance for this conservation-reliant species.

Wisconsin↗
USGS2022

Importance of local weather and environmental gradients on demography of a broadly distributed temperate frog

Amphibian populations are sensitive to environmental temperatures and moisture, which vary with local weather conditions and may reach new norms and extremes as contemporary climate change progresses. Using long-term (11–16 years) mark-recapture data from 10 populations of the Columbia spotted frog ( Rana luteiventris ) from across its U.S. range, we addressed hypotheses about how demographic relationships to weather depend upon a population’s position along climate gradients. We estimated the effect of seasonal weather on annual survival probability and recruitment rates both within populations and across the species’ range from subalpine forests to semi-arid deserts. We calculated population-specific weather variables that captured seasonal temperature and precipitation between summer sampling events, both for periods when frogs were active (spring to fall) and inactive (winter). Across all populations, we marked 15,885 adult frogs, with 33% of frogs recaptured at least once. Population demography varied with seasonal weather across the species’ range. Annual adult survival probability and recruitment rates of each population were influenced by a unique set of seasonal temperature and precipitation variables, particularly in winter and spring. Hence, adult survival varied with local conditions but, when analyzed across all populations, was predictable along a species-environment response curve associated with the timing of snowmelt and spring moisture. In contrast, recruitment rates for each population peaked at different values along an environmental gradient associated with the amount of snow during winter, and fall temperature and moisture levels, suggesting that recruitment may be responding to local conditions independently within each population. These findings highlight that sampling across the environmental (i.e., elevational and meteorological) gradients within a species range is necessary to predict species-level responses to regional climate change. This study also provides evidence of the importance of winter conditions on the demography of temperate amphibians, conditions that are already responding to climate change. Finally, this study further emphasizes that local context and spatiotemporal scale of inquiry remain paramount to understanding and potentially managing for climate effects on populations of amphibian species with broad geographic ranges.

Idaho, Montana, Nevada, Oregon↗
USGS2017

Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

Switchgrass ( Panicum virgatum ) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine ( Pinus taeda ) plantations in Mississippi, USA. We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species. Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters. Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival. Synthesis and applications . Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km 2 ), although at a local scale (50 m 2 ) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.

Journal of Applied Ecology↗
USGS2024

Strategic restoration planning for land birds in the Colorado River Delta, Mexico

Ecological restoration is an essential strategy for mitigating the current biodiversity crisis, yet restoration actions are costly. We used systematic conservation planning principles to design an approach that prioritizes restoration sites for birds and tested it in a riparian forest restoration program in the Colorado River Delta. Restoration goals were to maximize the abundance and diversity of 15 priority birds with a variety of habitat preferences. We built abundance models for priority birds based on the current landscape, and predicted bird distributions and relative abundances under a scenario of complete riparian forest restoration throughout our study area. Then, we used Zonation conservation planning software to rank this restored landscape based on core areas for all priority birds. The locations with the highest ranks represented the highest priorities for restoration and were located throughout the river reach. We optimized how much of the available landscape to restore by simulating restoration of the top 10–90% of ranked sites in 10% intervals. We found that total diversity was maximized when 40% of the landscape was restored, and mean relative abundance was maximized when 80% of the landscape was restored. The results suggest that complete restoration is not optimal for this community of priority birds and restoration of approximately 60% of the landscape would provide a balance between maximum relative abundance and diversity. Subsequent planning efforts will combine our results with an assessment of restoration costs to provide further decision support for the restoration-siting process. Our approach can be applied to any landscape-scale restoration program to improve the return on investment of limited economic resources for restoration.

Colorado River Delta↗
USGS2017

Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management

Altitudinal movement by tropical birds to track seasonally variable resources can move them from protected areas to areas of increased vulnerability. In Hawaiʻi, historical reports suggest that many Hawaiian honeycreepers such as the ‘I‘iwi ( Drepanis coccinea ) once undertook seasonal migrations, but the existence of such movements today is unclear. Because Hawaiian honeycreepers are highly susceptible to avian malaria, currently minimal in high-elevation forests, understanding the degree to which honeycreepers visit lower elevation forests may be critical to predict the current impact of malaria on population dynamics and how susceptible bird populations may respond to climate change and mitigation scenarios. Using radio telemetry data, we demonstrate for the first time that a large fraction of breeding adult and juvenile ‘I‘iwi originating from an upper-elevation (1,920 m) population at Hakalau Forest National Wildlife Refuge exhibit post-breeding movements well below the upper elevational limit for mosquitoes. Bloom data suggest seasonal variation in floral resources is the primary driver of seasonal movement for ‘I‘iwi. To understand the demographic implications of such movement, we developed a spatial individual-based model calibrated using previously published and original data. ʻI‘iwi dynamics were simulated backward in time, to estimate population levels in the absence of avian malaria, and forward in time, to assess the impact of climate warming as well as two potential mitigation actions. Even in disease-free ‘refuge’ populations, we found that breeding densities failed to reach the estimated carrying capacity, suggesting the existence of a seasonal “migration load” as a result of travel to disease-prevalent areas. We predict that ‘I‘iwi may be on the verge of extinction in 2100, with the total number of pairs reaching only ~ 0.2–12.3% of the estimated pre-malaria density, based on an optimistic climate change scenario. The probability of extinction of ‘I‘iwi populations, as measured by population estimates for 2100, is strongly related to their estimated migration propensity. Long-term conservation strategies likely will require a multi-pronged response including a reduction of malaria threats, habitat restoration and continued landscape-level access to seasonally variable nectar resources.

Ecological Monographs↗
USGS2026

Growth form and lifespan of herbaceous species mediate the role of traits in short-term drought response

Increased climate variability is expected to intensify short-term drought events. Plants have evolved stress tolerance strategies involving trade-offs in resource conservation, mycorrhizal collaboration and plant size, yet how these strategies promote drought resistance across different herbaceous plant groups remains unknown. Leveraging 63 globally distributed grassland and shrubland sites from the International Drought Experiment, we identified plant traits linked to drought resistance in 661 populations of 421 species after 1 year of extreme drought. We assessed how traits, site precipitation and drought severity affected cover change across growth forms and lifespans, and how trait–environment interactions influenced drought resistance. Across all species, leaf N (an acquisitive trait) was associated with drought resistance, whereas in forbs, drought resistance was also associated with a conservative root trait and plant size. In addition, interactions among traits mediated drought resistance; root traits predicted performance only in concert with other traits. Environmental variables influenced trait effects on drought resistance, notably for annuals in wetter sites, suggesting that drought-escape strategies in annuals may be advantageous only under mild stress. Our study highlights variability in traits that predict drought resistance across herbaceous plant groups, emphasizing the importance of species context, environmental stress and the selection of traits in research and management.

Nature Ecology and Evolution↗
USGS2023

Crossing the threshold: Invasive grasses inhibit forest restoration on Hawaiian islands

Forest removal for livestock grazing is a striking example of human-caused state change leading to a stable, undesirable invasive grass system that is resistant to restoration efforts. Understanding which factors lead to resilience to the alternative grass state can greatly benefit managers when planning forest restoration. We address how thresholds of grass cover and seed rain might influence forest recovery in a restoration project on Hawaiʻi Island, USA. Since the 1980s, over 400,000 Acacia koa (koa) trees have been planted across degraded pasture, and invasive grasses still dominate the understory with no native woody-plant recruitment. Between this koa/grass matrix are remnant native Metrosideros polymorpha (ʻōhiʻa) trees beneath which native woody plants naturally recruit. We tested whether there were threshold levels of native woody understory that accelerate recruitment under both tree species by monitoring seed rain at 40 trees (20 koa and ʻōhiʻa) with a range of native woody understory basal area (BA). We found a positive relationship between total seed rain (but not bird-dispersed seed rain) and native woody BA and a negative relationship between native woody BA and grass cover, with no indication of threshold dynamics. We also experimentally combined grass removal levels with seed rain density (six levels) of two common understory species in plots under koa ( n = 9) and remnant ʻōhiʻa ( n = 9). Few seedlings emerged when no grass was removed despite adding seeds at densities two to 75 times higher than naturally occurring. However, seedling recruitment increased two to three times once at least 50% of grass was removed. Existing survey data of naturally occurring seedlings also supported a threshold of grass cover below which seedlings were able to establish. Thus, removal of all grasses is not necessary to achieve system responses: Even moderate reductions (~50%) can increase rates of native woody recruitment. The nonlinear thresholds found here highlight how incremental changes to an inhibitory factor lead to limited restoration success until a threshold is crossed. The resources needed to fully eradicate an invasive species may be unwarranted for state change, making understanding where thresholds lie of the utmost importance to prioritize resources.

Hawaii↗
USGS2025

Relating surface water dynamics in wetlands and lakes to spatial variability in hydrologic signatures

The retention of surface water in wetlands and lakes can modify the timing, duration, and magnitude of river discharge. However, efforts to characterize the influence of surface water on discharge regimes have been generally limited to small, wetland-dense watersheds. We developed random forest models to explain spatial variability in six hydrologic signatures, reflecting flashiness, high, and low flow conditions, at 72 gaged watersheds with variable water storage capacity across the conterminous United States. In addition to variables representing meteorology and landscape characteristics, we also tested the inclusion of surface water dynamics, derived from Sentinel-1 and Sentinel-2. Models for all six signatures improved with the addition of catchment characteristics, including surface water dynamics, relative to models with only climate variables. Percent improvement in model adjusted R 2 , mean square error, and Akaike information criterion ranged from 4.00 to 14.33%, 5.00 to 20.30%, and 2.75–8.14, respectively. Automated variable selection can be indicative of the relative importance of certain variables over others. Using a forward selection process, five of the six signature models selected remotely sensed inundation or wetland variables ( p < 0.05). For example, the variable semi-permanent and permanent (SP + P) floodplain inundation (i.e., lakes along rivers) was associated with lower annual flashiness. Further, SP + P non-floodplain waters and geographically isolated wetlands significantly contributed to explaining variability in the low flow signatures. Our findings underscore the capacity of wetlands to stabilize and maintain flows during dry periods. Improved understanding of how surface water dynamics influence hydrologic signatures can inform wetland restoration efforts and facilitate improved resilience to extreme flow conditions.

Wetland Ecology & Management↗
USGS2020

Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate

Hydrology is a critical driver controlling mangrove wetlands structural and functional attributes at different spatial and temporal scales. Yet, human activities have negatively affected hydrology, causing mangrove diebacks and coverage loss worldwide. In fact, the assessment of mangrove water budgets, impacted by natural and human disturbances, is limited due to a lack of long-term data and information that hinders our understanding of how changes in hydroperiod and salinity control mangrove productivity and spatial distribution. In this study, we implemented a mass balance-based hydrological model (RHYMAN) that explicitly considers groundwater discharge in the Shark River estuary (SRE, southwestern Everglades) located in a karstic geomorphic setting and influenced by regional hydrological restoration. We used long-term hydroperiod and porewater salinity (PWS) datasets obtained from 2004 to 2016 for model calibration and validation and to determine spatiotemporal variability in water levels and PWS at three riverine mangrove sites (downstream, SRS-6; midstream, SRS-5; upstream, SRS-4) along SRE. Model results agree with a distinct PWS pattern along the estuarine salinity gradient where the highest PWS occurs at SRS-6 (mean: 25, range: 22–30 ppt), followed by SRS-5 (17, 14–25 ppt) and SRS-4 (5, 3–13 ppt). A commensurate increase in PWS over a thirteen-year period indicates a long-term reduction in freshwater inflow coupled with sea-level rise (SLR). Increasing freshwater scenario simulation results show a significant reduction (17–27%) in PWS along the estuary in contrast with a high SLR scenario when salinity increases up to 1.1 to 2.5 times that of control values. Model results show that freshwater inflow and SLR are key drivers controlling mangrove wetlands PWS in this karstic coastal region. Given its relatively simple structure, this mass balance-based hydrological model could be used in other environmental settings to evaluate potential habitat and regime shifts due to changes in hydrology and PWS under regional hydrological restoration management.

Florida↗
USGS2007

Investigation of wind and water level for the Giacomini Wetland Restoration Project, Point Reyes National Seashore

Point Reyes National Seashore (PRNS), comprising unique elements of geological, biological, and historical interest, is located on the central California coast approximately 60 km northwest of San Francisco. The National Seashore contains nearly 130 km of exposed and protected shorelines, spectacular coastal cliffs and headlands, lagoons, open grasslands, bushy hillsides, and forested ridges. Approximately 30 km of the shoreline are coastal-dune habitat that supports 11 federally listed species, including the threatened western snowy plover and the endangered plants Tidestrom's lupine ( Lupinus tidestromii ) and beach layia ( Layia carnosa ). The San Andreas Fault, a right-lateral strike-slip fault, trends northwest along the northeastern side of the park. Tomales Bay, which is straight, long, narrow, and shallow, runs along the northeastern boundary of PRNS. The Bay, which fills the northwestern end of a rift valley at the intersection of the San Andreas Fault with the coastline, is approximately 20 km long, 2 km wide, and 6 m deep with mountainous terrain to the southwest and rolling hills to the northeast. Tomales Bay is one of the cleanest estuaries on the West Coast. In winter, approximately 17,000 to 20,000 shorebirds inhabit Tomales Bay and Bodega Bay, which lies directly to the north. At the head of Tomales Bay, the Giacomini Ranch comprises 563 acres of pastureland currently being used for grazing dairy cattle. After more than 50 years of operation as a dairy, the National Park Service acquired the Giacomini property with the intention to restore most of it and the nearby Olema Marsh to tidal wetland. Restoration will add approximately 4% to the existing coastal wetlands in California. The project will return the headwaters of Tomales Bay and two major stream intersections to an intertidal marsh environment, enhancing habitat for both wildlife and fish populations and contributing to the long-term health of Tomales Bay. Prior to the establishment of the ranch, the area was primarily salt marsh that formed as the delta of Lagunitas Creek expanded into Tomales Bay. In converting the salt marsh to dairy land, levees and tide gates were constructed to prevent tidal incursion and stream flooding. Those levees have significantly altered the patterns of estuarine circulation and sediment deposition. To restore natural hydrologic processes within the area and to promote the return of ecological functions and processes, the levees will have to be breached or removed. Developing a successful restoration strategy requires knowledge of elevations within the pastureland and the range of water depths that can be expected from tidal, river, and wind action. In support of the restoration program, the USGS provides technical assistance to PRNS in the form of a scientific study focusing on understanding the physical processes that could affect the Giacomini wetland restoration. The study will yield scientific products that NPS resource managers can use in designing and implementing the restoration project. Research elements include: - Develop a Geodetic Control Network (GCN) throughout PRNS that meets the standards specified National Geodetic Survey data base (the NGS "Bluebook"). The grid will allow this and future studies to be conducted to a precision commensurate with the expressed goals of PRNS. The survey will consist of three steps: (1) verify existing GPS control monuments in the area; (2) tie control monuments in the study areas to the GPS control monuments; and (3) establish NAVD88 elevations using a digital electronic level. - Conduct a detailed survey of the Giacomini site to produce an accurate topographic map of the property. The site survey can be coupled with on-site water-level measurements to produce an empirical flooding model. - Measure water level and wind regime at the Giacomini site. The water-level range is critical to determining the wetland types based on the elevation of the dairy land. Water level at Sacramento Landing, in central Tomales Bay, will also be measured for comparison. As of November 2005, we have created a GCN, produced a detailed topographic map of the Giacomini site, and collected approximately three years of water-level and wind data at the Giacomini site and over one year of usable water-level data at the Sacramento Landing pier.

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