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USGS2005

LogCauchy, log-sech and lognormal distributions of species abundances in forest communities

Species-abundance (SA) pattern is one of the most fundamental aspects of biological community structure, providing important information regarding species richness, species-area relation and succession. To better describe the SA distribution (SAD) in a community, based on the widely used lognormal (LN) distribution model with exp(-x2) roll-off on Preston's octave scale, this study proposed two additional models, logCauchy (LC) and log-sech (LS), respectively with roll-offs of simple x-2 and e-x. The estimation of the theoretical total number of species in the whole community, S*, including very rare species not yet collected in sample, was derived from the left-truncation of each distribution. We fitted these three models by Levenberg-Marquardt nonlinear regression and measured the model fit to the data using coefficient of determination of regression, parameters' t-test and distribution's Kolmogorov-Smirnov (KS) test. Examining the SA data from six forest communities (five in lower subtropics and one in tropics), we found that: (1) on a log scale, all three models that are bell-shaped and left-truncated statistically adequately fitted the observed SADs, and the LC and LS did better than the LN; (2) from each model and for each community the S* values estimated by the integral and summation methods were almost equal, allowing us to estimate S* using a simple integral formula and to estimate its asymptotic confidence internals by regression of a transformed model containing it; (3) following the order of LC, LS, and LN, the fitted distributions became lower in the peak, less concave in the side, and shorter in the tail, and overall the LC tended to overestimate, the LN tended to underestimate, while the LS was intermediate but slightly tended to underestimate, the observed SADs (particularly the number of common species in the right tail); (4) the six communities had some similar structural properties such as following similar distribution models, having a common modal octave and a similar proportion of common species. We suggested that what follows the LN distribution should follow (or better follow) the LC and LS, and that the LC, LS and LN distributions represent a "sequential distribution set" in which one can find a best fit to the observed SAD. ?? 2004 Elsevier B.V. All rights reserved.

Ecological Modelling↗

USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗

USGS2012

Plant toxins and trophic cascades alter fire regime and succession on a boral forest landscape

Two models were integrated in order to study the effect of plant toxicity and a trophic cascade on forest succession and fire patterns across a boreal landscape in central Alaska. One of the models, ALFRESCO, is a cellular automata model that stochastically simulates transitions from spruce dominated 1 km2 spatial cells to deciduous woody vegetation based on stochastic fires, and from deciduous woody vegetation to spruce based on age of the cell with some stochastic variation. The other model, the ‘toxin-dependent functional response’ model (TDFRM) simulates woody vegetation types with different levels of toxicity, an herbivore browser (moose) that can forage selectively on these types, and a carnivore (wolf) that preys on the herbivore. Here we replace the simple succession rules in each ALFRESCO cell by plant–herbivore–carnivore dynamics from TDFRM. The central hypothesis tested in the integrated model is that the herbivore, by feeding selectively on low-toxicity deciduous woody vegetation, speeds succession towards high-toxicity evergreens, like spruce. Wolves, by keeping moose populations down, can help slow the succession. Our results confirmed this hypothesis for the model calibrated to the Tanana floodplain of Alaska. We used the model to estimate the effects of different levels of wolf control. Simulations indicated that management reductions in wolf densities could reduce the mean time to transition from deciduous to spruce by more than 15 years, thereby increasing landscape flammability. The integrated model can be useful in estimating ecosystem impacts of wolf control and moose harvesting in central Alaska.

Alaska↗

USGS2023

An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA

Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past and future climate change. We identified region-specific thresholds in fire-season aridity that distinguish years with limited, moderate, and extensive area burned for 11 extensively forested ecoregions in the western United States. We developed a new area burned model using these relationships and demonstrate its application in the Southern Rocky Mountains using climate projections from five global climate models (GCMs) that bracket the range of projected changes in aridity. We used the aridity thresholds to classify each simulation year as having limited, moderate, or extensive area burned and defined fire-size distributions from historical fire records for these categories. We simulated individual fires from a regression relating fire season aridity to the annual number of fires and drew fire sizes from the corresponding fire-size distributions. We project dramatic increases in area burned after 2020 under most GCMs and after 2060 with all GCMs as the frequency of extensive fire years increases. Our adaptable model can readily incorporate new observations (e.g., extreme fire years) to directly address the non-stationarity of fire-climate relationships as climatic conditions diverge from past observations. Our aridity threshold fire model provides a simple yet spatially robust approach to project regional changes in area burned with broad applicability to ecosystem and vegetation simulation models.

Ecological Modelling↗

USGS2008

Soil morphology of a debris flow chronosequence in a coniferous forest, southern California, USA

Soils on a series of debris flow deposits, ranging from < 1 to 244??years old, were described and sampled in order to investigate the early stages of soil development. The parent material at the site is debris flow regolith, composed mainly of gneiss, the soil moisture regime is xeric, and the vegetation is mixed coniferous forest. Ages of the deposits were assessed using dendrochronology. Morphologic trends in the organic horizons included a thickening of the humus form over time, along with the development of Fm and Hr horizons. The humus forms underwent a progression from Mormodors (20??years old), to Hemimors (26-101??years old), and finally Lignomors (163??years old) and Resimors (184-244??years old). Changes in physical properties of the uppermost mineral horizons as a function of increasing age included a decrease in the volume of coarse fragments, a linear decrease in bulk density, and a darkening and reddening of the soil color. No significant soil development took place in the subsoil during the time span of this chronosequence. The soils described were classified as Typic Xerofluvents and Typic Xerorthents (Regosols and Leptosols). Buried A horizons were observed in many of the soils. Where the A horizons could be linked to dendrochronology to assess the age of the buried surface, we found that the properties of the buried A horizons do not serve as a good indicator of the age of the surface. This study suggests rapid development of the humus form profile (organic horizons and A horizon) following debris flow deposition and rapid degradation of these horizons when the debris flow surface is buried. ?? 2008 Elsevier B.V.

Geoderma↗

USGS2018

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands versus non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at www.croplands.org and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC) https://www.lpdaac.usgs.gov/node/1282 .

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗

USGS2022

Assessing spatial transferability of a random forest metamodel for predicting drainage fraction

Fully distributed hydrological models are widely used in groundwater management, but model speed and data requirements impede their use for decision support purposes. Metamodels provide a simpler and faster model which emulates the underlying complex model using machine learning techniques. However, metamodel predictions beyond the ranges, in space and/or time, of training data are highly uncertain, and thus it is important to assess the predictive model performance to ranges outside the training data, i.e., model transferability . We present a novel methodology for evaluating model transferability to areas not contained in the training data set, based on various metrics that quantify the differences in covariate distributions between training and testing data. The transferability method can be employed as a screening tool to assess the suitability of a metamodel for spatial prediction beyond its training domain. We evaluated this transferability approach on a Random Forest metamodel of a 1000 km 2 fully distributed coupled groundwater model for predicting drainage fraction, the partitioning of infiltrating water between drains and groundwater. We conducted spatial cross-validation on 9 holdout sub-basins to assess metamodel transferability beyond sampling locations and compared this estimate with a random split-sample validation test. Using mappable covariates only, the metamodel showed high performance (R 2 = 0.79) tested on a 20% randomly sampled holdout. Conversely, metamodel performance significantly decreased for the 9 spatial holdouts (R 2 ranging from 0.13 to 0.61). We document that the proposed transferability metric correlates with metamodel predictive performance, and demonstrate its use to assess model transferability to datasets outside the training data spatial domain.

Journal of Hydrology↗

USGS2020

Habitat use by tiger prey in Thailand’s Western Forest Complex: What will it take to fill a half-full tiger landscape?

Tiger populations are declining globally, and depletion of major ungulate prey is an important contributing factor. To better understand factors affecting prey distribution in Thailand’s Western Forest Complex (WEFCOM), we conducted sign surveys for gaur (Bos gaurus ), banteng ( Bos javanicus ), and sambar ( Rusa unicolor ) along 3517 1-km transects and used occupancy models to identify important covariates associated with habitat use by each species. Habitat use by both gaur and sambar was lowest in areas closest to human settlements, although sambar preferred lower slopes near streams whereas gaur preferred steeper slopes at higher elevations. Banteng were found in only one of 17 protected areas (Huai Kha Khaeng [HKK] Wildlife Sanctuary), where they used low elevations and low slopes. We used these modeled relationships to predict occurrence of gaur, sambar, and banteng across each square km of the 19,000 km 2 WEFCOM landscape, using > 60 % occupancy probability to define suitable habitat use for each species. Based on this criterion, gaur and sambar occupied 28 and 50 % of suitable habitat in WEFCOM, and banteng occupied 57 % of suitable habitat in HKK. We used our models to assess the effectiveness of two hypothetical conservation initiatives. First, we modeled the impact of decreasing human activities around nine villages in the core of WEFCOM, which increased predicted suitable habitat in WEFCOM to 68 and 75 % for guar and sambar. We also modeled the extent of potential banteng habitat that still remains in the other 16 protected areas. This could result in a 4-fold increase in banteng suitable habitat in WEFCOM. This is the first study to use occupancy surveys to determine where large prey species can be restored to support management to increase the distribution of tigers, and potentially fill a half-full tiger landscape.

Journal for Nature Conservation↗

USGS2008

Seasonal and event variations in δ 34 S values of stream sulfate in a Vermont forested catchment: Implications for sulfur sources and cycling

Stable sulfur (S) isotope ratios can be used to identify the sources of sulfate contributing to streamwater. We collected weekly and high-flow stream samples for S isotopic analysis of sulfate through the entire water year 2003 plus the snowmelt period of 2004. The study area was the 41-ha forested W-9 catchment at Sleepers River Research Watershed, Vermont, a site known to produce sulfate from weathering of sulfide minerals in the bedrock. The δ 34 S values of streamwater sulfate followed an annual sinusoidal pattern ranging from about 6.5&permil; in early spring to about 10&permil; in early fall. During high-flow events, δ 34 S values typically decreased by 1 to 3&permil; from the prevailing seasonal value. The isotopic evidence suggests that stream sulfate concentrations are controlled by: (1) an overall dominance of bedrock-derived sulfate ( δ 34 S ~ 6–14&permil;); (2) contributions of pedogenic sulfate ( δ 34 S ~ 5–6&permil;) during snowmelt and storms with progressively diminishing contributions during base flow recession; and (3) minor effects of dissimilatory bacterial sulfate reduction and subsequent reoxidation of sulfides. Bedrock should not be overlooked as a source of S in catchment sulfate budgets.

Vermont↗

USGS2020

Estimating burn severity and carbon emissions from a megafire in boreal forests of China

Wildfires, especially those of large size, worsen air quality and alter the carbon cycle through combustion of large quantities of biomass and release of carbon into the atmosphere. The Black Dragon fire, which occurred in 1987 in the boreal forests of China is among the top five of such megafires ever recorded in the world. With over 30 years of accumulation of data and availability of new greenhouse gas emission accounting methods, carbon emissions from this megafire can now be estimated with improved precision and greater spatial resolution. To do this, we combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire. Results of the study showed that 1.30 million hectares burned and 52% of that area burned with high severity. The emitted carbon dioxide equivalents (CO2e), accounted for approximately 10% of total fossil fuel emissions from China in 1987, along with CO (2%–3% of annual anthropogenic CO emissions from China) and non-methane hydrocarbons (NMHC) contributing to the atmospheric pollutants. Our study provides an important basis for carbon emission estimation and understanding the impacts of megafires.

Science of the Total Environment↗

USGS2022

Predicting regional fluoride concentrations at public and domestic supply depths in basin-fill aquifers of the western United States using a random forest model

A random forest regression (RFR) model was applied to over 12,000 wells with measured fluoride (F) concentrations in untreated groundwater to predict F concentrations at depths used for domestic and public supply in basin-fill aquifers of the western United States. The model relied on twenty-two regional-scale environmental and surficial predictor variables selected to represent factors known to control F concentrations in groundwater. The testing model fit R 2 and RMSE were 0.52 and 0.78 mg/L. Comparisons of measured to predicted proportions of four F-concentrations categories (<0.7 mg/L, 0.7–2 mg/L, >2 mg/L – 4 mg/L, and > 4 mg/L) indicate that the model performed well at making regional-scale predictions. Differences between measured and predicted proportions indicate underprediction of measured F at values by between 4 and 20 mg/L, representing less than 1% of the regional scale predicted values. These residuals most often map to geographic regions where local-scale processes including evaporative discharge in closed basins or intermittent streams concentrate fluoride in shallow groundwater. Despite this, the RFR model provides spatially continuous F predictions across the basin-fill aquifers where discrete samples are missing. Further, the predictions capture documented areas that exceed the F maximum contaminant level for drinking water of 4 mg/L and areas that are below the oral-health benchmark of 0.7 mg/L. These predictions can be used to estimate fluoride concentrations in unmonitored areas and to aid in identifying geographic areas that may require further investigation at localized scales.

Arizona, California, Colorado, New Mexico, Nevada,↗

USGS2017

Extent of localized tree mortality influences soil biogeochemical response in a beetle-infested coniferous forest

Recent increases in the magnitude and occurrence of insect-induced tree mortality are disruptingevergreen forests globally. To resolve potentially conflicting ecosystem responses, we investigatedwhether surrounding trees exert compensatory effects on biogeochemical signatures following beetleinfestation. To this end, plots were surveyed within a Colorado Rocky Mountain watershed that expe-rienced beetle infestation almost a decade prior and contained a range of surrounding tree mortality(from 9 to 91% of standing trees). Near-surface soil horizons under plot-centered live (green) and beetle-killed (grey) lodgepole pines were sampled over two consecutive summers with variable moistureconditions. Results revealed that soil respiration was 18e28% lower beneath beetle-infested trees andcorrelated to elevated dissolved organic carbon aromaticity. While certain edaphic parameters includingpH and water content were elevated below grey compared to green trees regardless of the mortalityextent within plots, other biogeochemical responses required a higher severity of surrounding mortalityto overcome compensatory effects of neighboring live trees. For instance, C:N ratios under grey treesdeclined with increased severity of surrounding tree mortality, and the proportion of ammonium dis-played a threshold effect with pronounced increases after surrounding tree mortality exceeded ~40%.Overall, the biogeochemical response to tree death was most prominent in the mineral soil horizonwhere tree mortality had the largest affect on carbon recalcitrance and the enrichment of nitrogenspecies. These results can aid in determining when and where nutrient cycles and biogeochemicalfeedbacks to the atmosphere and hydrosphere will be observed in association with this type of ecological disturbance.

Rocky Mountain Watershed↗

USGS2020

Local abundance of Ixodes scapularis in forests: Effects of environmental moisture, vegetation characteristics, and host abundance

Ixodes scapularis is the primary vector of Lyme disease spirochetes in eastern and central North America, and local densities of this tick can affect human disease risk. We sampled larvae and nymphs from sites in Massachusetts and Wisconsin, USA, using flag/drag devices and by collecting ticks from hosts, and measured environmental variables to evaluate the environmental factors that affect local distribution and abundance of I. scapularis . Our sites were all forested areas with known I. scapularis populations. Environmental variables included those associated with weather (e.g., temperature and relative humidity), vegetation characteristics (at canopy, shrub, and ground levels), and host abundance (small and medium-sized mammals and reptiles). The numbers of larvae on animals at a given site and season showed a logarithmic relationship to the numbers in flag/drag samples, suggesting limitation in the numbers on host animals. The numbers of nymphs on animals showed no relationship to the numbers in flag/drag samples. These results suggest that only a small proportion of larvae and nymphs found hosts because in neither stage did the numbers of host-seeking ticks decline with increased numbers on hosts. Canopy cover was predictive of larval and nymphal numbers in flag/drag samples, but not of numbers on hosts. Numbers of small and medium-sized mammal hosts the previous year were generally not predictive of the current year’s tick numbers, except that mouse abundance predicted log numbers of nymphs on all hosts the following year. Some measures of larval abundance were predictive of nymphal numbers the following year. The mean number of larvae per mouse was well predicted by measures of overall larval abundance (based on flag/drag samples and samples from all hosts), and some environmental factors contributed significantly to the model. In contrast, the mean numbers of nymphs per mouse were not well predicted by environmental variables, only by overall nymphal abundance on hosts. Therefore, larvae respond differently than nymphs to environmental factors. Furthermore, flag/drag samples provide different information about nymphal numbers than do samples from hosts. Flag/drag samples can provide information about human risk of acquiring nymph-borne pathogens because they provide information on the densities of ticks that might encounter humans, but to understand the epizootiology of tick-borne agents both flag/drag and host infestation data are needed.

Massachusetts, Wisconsin↗

USGS2003

Terrestrial activity and conservation of adult California red-legged frogs Rana aurora draytonii in coastal forests and grasslands

The federally threatened California red-legged frog Rana aurora draytonii occupies both aquatic and terrestrial habitats in its adult life stage. The terrestrial activities of this species are not well known and require documentation to assist in the development of appropriate levels of protection under the US Endangered Species Act. We studied the terrestrial activities of radio-tagged red-legged frogs (n = 8-26) inhabiting a coastal watershed in Santa Cruz County, California, during 1997-1998. In particular, we investigated (1) the use of terrestrial habitats by non-migrating adults in relation to season, breeding chronology, and precipitation, and (2) adult migration behavior, including seasonal timing, duration, distances traveled, and the use of corridors. Non-migrating red-legged frogs occupied terrestrial habitats briefly (median = 4-6 days) following infrequent summer rains, but resided nearly continuously on land (median = 20-30 days) from the onset of the winter wet-season until breeding activities commenced 1-2 months later. All of the non-migrating frogs remained within 130 m of their aquatic site of residence (median <25 m). Intervals spent on land were again brief during mid/late winter (median = 1-4 days), despite frequent and copious rainfall. Adult migration to and from breeding sites occurred from late October through mid-May (wet season). We monitored 25 migration events between aquatic sites that were 200-2800 m apart. Short distance movements ( <300 m) were completed in 1-3 days, longer movements required up to 2 months. Most migrating frogs moved overland in approximately straight lines to target sites without apparent regard to vegetation type or topography. Riparian corridors were neither essential nor preferred as migration routes. Frogs traveling overland occurred in upland habitats as far as 500 m from water. Approximately 11-22% of the adult population was estimated to migrate to and from breeding sites annually, whereas the bulk of the adult population was resident at these sites. Adequate protection of red-legged frog populations inhabiting relatively undeveloped landscapes is liable to be achieved by retaining an array of suitable habitat elements within at least 100 m of occupied aquatic sites, and by imposing seasonal limitations on detrimental human activities occurring within this zone. Specific protections for migrating frogs are probably unwarranted in forest and rangeland environments because dispersal habitat is ubiquitous and migrating frogs are widely distributed across the landscape in space and time. Published by Elsevier Science Ltd.

Biological Conservation↗

USGS2001

Processes regulating watershed chemical export during snowmelt, fraser experimental forest, Colorado

In the Central Rocky Mountains, snowfall dominates precipitation. Airborne contaminants retained in the snowpack can affect high elevation surface water chemistry during snowmelt. At the Fraser Experimental Forest (FEF), located west of the Continental Divide in Central Colorado, snowmelt dominates the annual hydrograph, and accounts for >95% of annual stream water discharge. During the winters of 1989-1993, we measured precipitation inputs, snowpack water equivalent (SWE) and ion content, and stream water chemistry every 7-10 days along a 3150-3500 m elevation gradient in the subalpine and alpine Lexen Creek watershed. The study objectives were to (1) quantify the distribution of SWE and snowpack chemical content with elevation and aspect, (2) quantify snowmelt rates, temperature of soil, snowpack, and air with elevation and aspect, and (3) use change in upstream-downstream water chemistry during snowmelt to better define alpine and subalpine flowpaths. The SWE increased with elevation (P < 0.001) and was greater on NE aspects (P < 0.05). Subalpine soils were unfrozen. Snowmelt occurred throughout winter at low elevation (3150 m), SE aspect stations. By snowpack peak water equivalent (PWE), the snowpack lost about a third (0.24 m) of its moisture. The subalpine snowpack had warm (> - 3??C) temperatures throughout winter which resulted in significant snowpack ion loss. By snowpack PWE in mid May, the snowpack had lost almost half the cumulative precipitation H+, NH4+, and SO42- inputs and a third of the NO3- input. Windborne soil particulate inputs late in winter increased snowpack base cation content. Variation in subalpine SWE and snowpack ion content with elevation and aspect, and wind redistribution of snowfall in the alpine resulted in large year-to-year differences in the timing and magnitude of SWE, PWE, and snowpack ion content. The alpine stream water ion concentrations changed little during snowmelt indicating meltwater passed quickly through surface porous soils and was well mixed before entering the stream. Conversely, subalpine stream water chemistry was diluted during snowmelt suggesting much melt water moved to the stream as shallow subsurface lateral flow. Published by Elsevier Science B.V.

Journal of Hydrology↗

USGS1998

Controls on denitrification in riparian soils in headwater catchments of a hardwood forest in the Catskill Mountains, U.S.A.

Denitrification in riparian soils is thought to be an important factor that reduces hydrologic export of nitrate from forested and agricultural catchments. A 2-y study to identify the soil factors most closely associated with denitrification in riparian soils in headwater catchments within the Catskill Mountains of New York, included field surveys of surface and subsurface denitrification rates, and an amendment experiment to assess the relative effects of increases in available carbon and substrate NO-/3 on denitrification rates. Denitrification rates were measured by acetylene inhibition during incubation of intact soil cores from eight soil types representing a range of drainage classes. Soil cores were analyzed for organic matter, total P, extractable NO-/3-N and NH+/4-N, organic N, pH, moisture, porosity, and water-filled pore space, to determine which of these factors were most closely associated with denitrification. The distribution of denitrification rates found during the field surveys was highly skewed, with many low or zero values and few high values. Denitrification rates were positively associated with high soil organic matter, total P, and water-filled pore space, and were highest in seep (poorly-drained) soils, toeslope (seasonally-drained) soils, and stream-edge (poorly- to moderately well-drained) soils in which these three soil characteristics were typically high. Denitrification rates in these wet locations were also positively associated with soil NH+/4-N concentration and pH, but not with NO-/3-N concentration, suggesting that the rate of NO-/3 supply (via nitrification or hydrologic transport) was more important than the instantaneous concentration of NO-/3-N in the soils. The amendment experiment indicated that denitrification in soil types studied was most responsive to added glucose alone or with NO-/3. Thus, in these soils, a combination of slow rates of NO-/3 supply and low available carbon appears to limit denitrification. Annual denitrification rates in spring-fed soils (0.74 to 1.43 kg N ha-1 y-1) were up to 5 times greater than in other surface soils, yet these soils accounted for only 1.8% of the catchment's N loss through denitrification because they represent less than 3% of the catchment area. Dry upland soils constituted 71% of the catchment area and accounted for 91% of the catchment's N loss through denitrification. Annual denitrification in the catchment equaled about 65% of stream NO-/3-N and NH+/4-N export and 14% of precipitation NO-/3-N and NH+/4-N inputs. Denitrification appears to be important relative to N input and export in these Catskill catchments.

Soil Biology and Biochemistry↗

USGS1996

A drowned lycopsid forest above the Mahoning coal (Conemaugh Group, Upper Pennsylvanian) in eastern Ohio, U.S.A

Over 800 mud-filled casts of upright lycopsid tree stumps have been documented immediately above the Mahoning coal in an active underground mine located in northwestern Jefferson County, Ohio. The coal body originated as a pod-shaped peat body of ∼ 60 km 2 . Trees are rooted at several levels within a thin (15–40 cm) bone coal directly above the banded coal; they extend upward up to 15 cm into overlying, flat-bedded, carbonaceous mudstones that coarsen up. From a maximum basal diameter of 1.2 m, stumps taper upward to diameters no less than 0.3 m. Within single-entry transects, < 6 m wide that total 2585 m in length, stumps are randomly distributed. The trees are identified as lepidodenrids on the basis of gross morphology, external stem patterns, and attached stigmarian root systems, and provisionally as Lepidophloios or Lepidodendron by associated palynology of the enclosing matrix. Palynological analyses of incremental seam samples indicate an initial dominance of lycopsid spores with lepidodendracean affinities ( Lycospora granulata from Lepidophloios hallii ), replaced upwards by tree-fern spores, with a reoccurrence of lepidodendracean spores in the upper benches: spores of Sigillaria (Crassispora) are abundant only at the base of the coal. Petrographic analyses indicate a prallel trend from vitrinite-rich to inertinite- and liptinite-rich upward in the coal body. All data indicate that the peat represented by the Mahoning coal was drowned slowly. During the earliest stages of inundation, a lycopsid forest was re-established, only to be subsequently drowned.

International Journal of Coal Geology↗