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At least 883 records · Page 49Linked to original sources

Atmospheric propagation modeling indicates homing pigeons use loft-specific infrasonic ‘map’ cues

Results from an acoustic ray-tracing program using daily meteorological profiles are presented to explain ‘release-site biases’ for homing pigeons at three experimental sites in upstate New York where W. T. Keeton and his co-workers at Cornell University conducted extensive releases between 1968 and 1987 in their investigations of the avian navigational ‘map’. The sites are the Jersey Hill and Castor Hill fire towers, and another near Weedsport, where control pigeons from the Cornell loft vanished in random directions, in directions consistently >50 deg clockwise and in directions ∼15 deg clockwise from the homeward bearing, respectively. Because Cornell pigeons were disoriented at Jersey Hill whereas birds from other lofts were not, it is inferred that Jersey Hill lies within an acoustic ‘shadow’ zone relative to infrasonic signals originating from the Cornell loft’s vicinity. Such signals could arise from ground-to-air coupling of near-continuous microseisms, or from scattering of direct microbaroms off terrain features, both of which are initially generated by wave–wave interactions in the deep ocean. HARPA runs show that little or no infrasound from the loft area arrived at Jersey Hill on days when Cornell pigeons were disoriented there, and that homeward infrasonic signals could have arrived at all three sites from directions consistent with pigeon departure bearings, especially on days when these bearings were unusual. The general stability of release-site biases might be due to influences of terrain on transmission of the homeward signals under prevailing weather patterns, whereas short-term changes in biases might be caused by rapid shifts in atmospheric conditions.

New York

Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach

The increasing availability of multi-scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model-assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the "hot" and "cold" reference conditions. The SSEBop model was used for computing ET for 12 years (2000-2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000-2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

Journal of the American Water Resources Associatio

Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy

This study combined a radar-based time series of Hurricane Sandy surge and estimated persistence with optical sensor-based marsh condition change to assess potential causal linkages of surge persistence and marsh condition change along the New Jersey Atlantic Ocean coast. Results based on processed TerraSAR-X and COSMO-SkyMed synthetic aperture radar (SAR) images indicated that surge flooding persisted for 12 h past landfall in marshes from Great Bay to Great Egg Harbor Bay and up to 59 h after landfall in many back-barrier lagoon marshes. Marsh condition change (i.e. loss of green marsh vegetation) was assessed from optical satellite images (Satellite Pour l’Observation de la Terre and Moderate Resolution Imaging Spectroradiometer) collected before and after Hurricane Sandy. High change in condition often showed spatial correspondence, with high surge persistence in marsh surrounding the lagoon portion of Great Bay, while in contrast, low change and high persistence spatial correspondence dominated the interior marshes of the Great Bay and Great Egg Harbor Bay estuaries. Salinity measurements suggest that these areas were influenced by freshwater discharges after landfall possibly mitigating damage. Back-barrier marshes outside these regions exhibited mixed correspondences. In some cases, topographic features supporting longer surge persistence suggested that non-correspondence between radar and optical data-based results may be due to differential resilience; however, in many cases, reference information was lacking to determine a reason for non-correspondence.

New Jersey

Semiautomated tremor detection using a combined cross-correlation and neural network approach

Despite observations of tectonic tremor in many locations around the globe, the emergent phase arrivals, low‒amplitude waveforms, and variable event durations make automatic detection a nontrivial task. In this study, we employ a new method to identify tremor in large data sets using a semiautomated technique. The method first reduces the data volume with an envelope cross‒correlation technique, followed by a Self‒Organizing Map (SOM) algorithm to identify and classify event types. The method detects tremor in an automated fashion after calibrating for a specific data set, hence we refer to it as being “semiautomated”. We apply the semiautomated detection algorithm to a newly acquired data set of waveforms from a temporary deployment of 13 seismometers near Cholame, California, from May 2010 to July 2011. We manually identify tremor events in a 3 week long test data set and compare to the SOM output and find a detection accuracy of 79.5%. Detection accuracy improves with increasing signal‒to‒noise ratios and number of available stations. We find detection completeness of 96% for tremor events with signal‒to‒noise ratios above 3 and optimal results when data from at least 10 stations are available. We compare the SOM algorithm to the envelope correlation method of Wech and Creager and find the SOM performs significantly better, at least for the data set examined here. Using the SOM algorithm, we detect 2606 tremor events with a cumulative signal duration of nearly 55 h during the 13 month deployment. Overall, the SOM algorithm is shown to be a flexible new method that utilizes characteristics of the waveforms to identify tremor from noise or other seismic signals.

California

Gravity field over the Sea of Galilee: Evidence for a composite basin along a transform fault

The Sea of Galilee (Lake Kinneret) is located at the northern portion of the Kinneret-Bet Shean basin, in the northern Dead Sea transform. Three hundred kilometers of continuous marine gravity data were collected in the lake and integrated with land gravity data to a distance of more than 20 km around the lake. Analyses of the gravity data resulted in a free-air anomaly map, a variable density Bouguer anomaly map, and a horizontal first derivative map of the Bouguer anomaly. These maps, together with gravity models of profiles across the lake and the area south of it, were used to infer the geometry of the basins in this region and the main faults of the transform system. The Sea of Galilee can be divided into two units. The southern half is a pull-apart that extends to the Kinarot Valley, south of the lake, whereas the northern half was formed by rotational opening and transverse normal faults. The deepest part of the basinal area is located well south of the deepest bathymetric depression. This implies that the northeastern part of the lake, where the bathymetry is the deepest, is a young feature that is actively subsiding now. The pull-apart basin is almost symmetrical in the southern part of the lake and in the Kinarot Valley south of the lake. This suggests that the basin here is bounded by strike-slip faults on both sides. The eastern boundary fault extends to the northern part of the lake, while the western fault does not cross the northern part. The main factor controlling the structural complexity of this area is the interaction of the Dead Sea transform with a subperpendicular fault system and rotated blocks.

Sea of Galilee

Pore systems and organic petrology of cretaceous Mowry and Niobrara source-rock reservoirs, Powder River Basin, Wyoming, USA

The Powder River Basin (PRB) is a world-class oil province, in large part thanks to contributions from premier source rocks, Cretaceous Mowry and Niobrara shales. Both formations are also unconventional reservoirs. A critical aspect of evaluating production potential and finding sweet spots is the nature of the pore systems in these fine-grained source-rock reservoirs. Variation by stratigraphic interval is important for selecting optimum target zones for horizontal wells. Understanding variation in pore type, size, and connectivity and relationships with mineralogy and fabric help in determining prospectivity in different parts of the basin. Deciphering controls on pore-system development helps predict intervals and locations of optimum reservoir quality. Imaging of Niobrara and Mowry samples from a range of thermal maturities provided observations and data on pore systems, organic matter (OM) types and associations with mineralogy and fabric, wettability, and microporosity associated with both diagenetic and detrital clays. Imaging techniques included scanning electron microscopy, organic petrography and correlative scanning electron microscopy, and mapping of mineralogy through energy dispersive spectroscopy. Mean solid bitumen (BR o ) and vitrinite reflectance (VR o ) values indicate all samples are in the oil window with values ranging from 0.52 to 1.15%. Organic fluorescence is prominent in amorphous OM, solid bitumen and some vitrinite in the early oil window. The fluorescence is extinguished at higher thermal maturity. Carbonate pellets (in Niobrara) mainly contain migrated solid bitumen and residual live oil and little or no terrigenous OM (vitrinite and inertinite). However, terrigenous OM is common in siliceous/argillaceous laminae in both formations, where it occurs with amorphous OM, some of which has converted in situ to a solid bitumen petroleum residue. One key finding is the widespread presence of migrated OM at very early oil window maturity. Distribution of such OM and associated wettability alteration is fabric-controlled, at all levels of thermal maturity studied. Clay morphology and abundance and supporting rigid mineral grain framework strongly influence pore development, preservation, and connectivity in both formations. Carbonate content is a good proxy for reservoir quality in Niobrara intervals due to association of porous solid bitumen with calcareous fecal pellets. High recrystallized microquartz content is associated with the best reservoir intervals in the Mowry.

Wyoming

Mapping playa evaporite minerals and associated sediments in Death Valley, California, with multispectral thermal infrared images

Efflorescent salt crusts and associated sediments in Death Valley, California, were studied with remote-sensing data acquired by the NASA thermal infrared multispectral scanner (TIMS). Nine spectral classes that represent a variety of surface materials were distinguished, including several classes that reflect important aspects of the playa groundwater chemistry and hydrology. Evaporite crusts containing abundant thenardite (sodium sulfate) were mapped along the northern and eastern margins of the Cottonball Basin, areas where the inflow waters are rich in sodium. Gypsum (calcium sulfate) crusts were more common in the Badwater Basin, particularly near springs associated with calcic groundwaters along the western basin margin. Evaporite-rich crusts generally marked areas where groundwater is periodically near the surface and thus able to replenish the crusts though capillary evaporation. Detrital silicate minerals were prevalent in other parts of the salt pan where shallow groundwater does not affect the surface composition. The surface features in Death Valley change in response to climatic variations on several different timescales. For example, salt crusts on low-lying mudflats form and redissolve during seasonal-to-interannual cycles of wetting and desiccation. In contrast, recent flooding and erosion of rough-salt surfaces in Death Valley probably reflect increased regional precipitation spanning several decades. Remote-sensing observations of playas can provide a means for monitoring changes in evaporite facies and for better understanding the associated climatic processes. At present, such studies are limited by the availability of suitable airborne scanner data. However, with the launch of the Earth Observing System (EOS) AM-1 Platform in 1998, multispectral visible/near-infrared and thermal infrared remote-sensing data will become globally available.

Journal of Geophysical Research B: Solid Earth

Identifying suitable sites for Florida panther reintroduction

A major objective of the 1995 Florida Panther ( Puma concolor cory ) Recovery Plan is the establishment of 2 additional panther populations within the historic range. Our goal was to identify prospective sites for Florida panther reintroduction within the historic range based on quantitative landscape assessments. First, we delineated 86 panther home ranges using telemetry data collected from 1981 to 2001 in south Florida to develop a Mahalanobis distance (D 2 ) habitat model, using 4 anthropogenic variables and 3 landscape variables mapped at a 500-m resolution. From that analysis, we identified 9 potential reintroduction sites of sufficient size to support a panther population. We then developed a similar D 2 model at a higher spatial resolution to quantify the area of favorable panther habitat at each site. To address potential for the population to expand, we calculated the amount of favorable habitat adjacent to each prospective reintroduction site within a range of dispersal distances of female panthers. We then added those totals to the contiguous patches to estimate the total amount of effective panther habitat at each site. Finally, we developed an expert-assisted model to rank and incorporate potentially important habitat variables that were not appropriate for our empirical analysis (e.g., area of public lands, livestock density). Anthropogenic factors heavily influenced both the landscape and the expert-assisted models. Of the 9 areas we identified, the Okefenokee National Wildlife Refuge, Ozark National Forest, and Felsenthal National Wildlife Refuge regions had the highest combination of effective habitat area and expert opinion scores. Sensitivity analyses indicated that variability among key model parameters did not affect the high ranking of those sites. Those sites should be considered as starting points for the field evaluation of potential reintroduction sites.

Florida

Mapping risk for nest predation on a barrier island

Barrier islands and coastal beach systems provide nesting habitat for marine and estuarine turtles. Densely settled coastal areas may subsidize nest predators. Our purpose was to inform conservation by providing a greater understanding of habitat-based risk factors for nest predation, for an estuarine turtle. We expected that habitat conditions at predated nests would differ from random locations at two spatial extents. We developed and validated an island-wide model for the distribution of predated Diamondback terrapin nests using locations of 198 predated nests collected during exhaustive searches at Fisherman Island National Wildlife Refuge , USA. We used aerial photographs to identify all areas of possible nesting habitat and searched each and surrounding environments for nests, collecting location and random-point microhabitat data. We built models for the probability of finding a predated nest using an equal number of random points and validated them with a reserve set ( N  = 67). Five variables in 9 a priori models were used and the best selected model (AIC weight 0.98) reflected positive associations with sand patches near marshes and roadways. Model validation had an average capture rate of predated nests of 84.14 % (26.17–97.38 %, Q1 77.53 %, median 88.07 %, Q3 95.08 %). Microhabitat selection results suggest that nests placed at the edges of sand patches adjacent to upland shrub/forest and marsh systems are vulnerable to predation. Forests and marshes provide cover and alternative resources for predators and roadways provide access; a suggestion is to focus nest protection efforts on the edges of dunes, near dense vegetation and roads.

Virginia

The importance of lake emergent aquatic vegetation for estimating Arctic-boreal methane emissions

Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under-represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ∼1.5 m deep and can be detected with synthetic aperture radar (SAR). To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR data from the NASA Arctic-Boreal Vulnerability Experiment to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ∼16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50–68]%, 22 [20–25]%, 1.0 [0.8–1.2]%, and 7.0 [5.0–12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18–25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.

Journal of Geophysical Research: Biogeosciences

Combining fisheries surveys to inform marine species distribution modelling

Ecosystem-scale examination of fish communities typically involves creating spatio-temporally explicit relative abundance distribution maps using data from multiple fishery-independent surveys. However, sampling performance varies by vessel and sampling gear, which may influence estimated species distribution patterns. Using GAMMs, the effect of different gear–vessel combinations on relative abundance estimates at length was investigated using European fisheries-independent groundfish survey data. We constructed a modelling framework for evaluating relative efficiency of multiple gear–vessel combinations. 19 northeast Atlantic surveys for 254 species-length combinations were examined. Space-time variables explained most of the variation in catches for 181/254 species-length cases, indicating that for many species, models successfully characterized distribution patterns when combining data from disparate surveys. Variables controlling for gear efficiency explained substantial variation in catches for 127/254 species-length data sets. Models that fail to control for gear efficiencies across surveys can mask changes in the spatial distribution of species. Estimated relative differences in catch efficiencies grouped strongly by gear type, but did not exhibit a clear pattern across species’ functional forms, suggesting difficulty in predicting the potential impact of gear efficiency differences when combining survey data to assess species’ distributions and highlighting the importance of modelling approaches that can control for gear differences.

ICES Journal of Marine Science

A framework for disaggregating remote-sensing cropland into rainfed and irrigated classes at continental scale

Agriculture consumes the largest share of freshwater globally; therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. In this study, a framework incorporating the Budyko model was used to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high-confidence cropland map (HCCM). The HCCM was generated for calibration and validation of the crop partitioning framework as an alternative to individual cropland masks which exhibit high disagreement. The accuracy of the framework in partitioning the HCCM was evaluated using an independent validation dataset, yielding an overall accuracy rate of 73 %. The findings of this study indicate that out of the total area covered by the HCCM (2.36 million km 2 ), about 461,000 km 2 (19 %) is irrigated cropland. The partitioning framework was applied on eight landcover products, and the extent of irrigated areas varied between 19 % and 30 % of the total cropland area. The framework demonstrated high precision and specificity scores, indicating its effectiveness in correctly identifying irrigated areas while minimizing the misclassification of rainfed areas as irrigated. This study provides an enhanced understanding of rainfed and irrigation patterns across Africa, supporting efforts towards achieving sustainable and resilient agricultural systems. Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.

International Journal of Applied Earth Observation

Characterizing riverbed sediment using high-frequency acoustics 2: scattering signatures of Colorado River bed sediment in Marble and Grand Canyons

In this, the second of a pair of papers on the statistical signatures of riverbed sediment in high-frequency acoustic backscatter, spatially explicit maps of the stochastic geometries (length- and amplitude-scales) of backscatter are related to patches of riverbed surfaces composed of known sediment types, as determined by geo-referenced underwater video observations. Statistics of backscatter magnitudes alone are found to be poor discriminators between sediment types. However, the variance of the power spectrum, and the intercept and slope from a power-law spectral form (termed the spectral strength and exponent, respectively) successfully discriminate between sediment types. A decision-tree approach was able to classify spatially heterogeneous patches of homogeneous sands, gravels (and sand-gravel mixtures), and cobbles/boulders with 95, 88, and 91% accuracy, respectively. Application to sites outside the calibration, and surveys made at calibration sites at different times, were plausible based on observations from underwater video. Analysis of decision trees built with different training data sets suggested that the spectral exponent was consistently the most important variable in the classification. In the absence of theory concerning how spatially variable sediment surfaces scatter high-frequency sound, the primary advantage of this data-driven approach to classify bed sediment over alternatives is that spectral methods have well understood properties and make no assumptions about the distributional form of the fluctuating component of backscatter over small spatial scales.

Arizona

Where to restore and conserve? A regional benefit cost analysis of coral reef protection and restoration for coastal flood resilience

Momentum is growing for the management of coral reefs as a strategy to reduce climate risks in tropical coastlines. Yet, quantification of the life-time costs, impacts, and benefits remains limited. This study provides one of the first rigorous, spatially explicit, regional-scale Benefit:Cost Analyses (BCA) for coral reef restoration and was designed to meet the BCA requirements of major hazard mitigation funding and programs. This study simulates coastal flooding using a hydrodynamic model under different scenarios representing current coral reef conditions, reef degradation, and reef restoration. These coastal flood maps are used to estimate socioeconomic damages, which are included in a BCA to assess cost-effectiveness and priority areas for coral reef conservation and restoration. The United States Virgin Islands is used as a case study given recent impacts from storms and their new policy that declares reefs as natural infrastructure. The results show that flood risk across the islands of Saint Croix, Saint John, and Saint Thomas is $51.4 million USD per year. Annually, coral reefs prevent flood damages to 481 people and $43.6 million USD of infrastructure, which represents 87 % of the flood risk. These results identify the communities that could receive the greatest benefits from coral conservation and restoration, which overlap significantly. Coral reef restoration is found to be a cost-effective strategy for flood mitigation although how reefs are restored matters. Hybrid coral reef restoration provides greater flood mitigation benefits than ecological restoration, but its cost-effectiveness is overall lower given its greater costs. Many coastal areas have benefit:cost ratios exceeding 1.5, which complies with typical government agencies’ requirements for accessing hazard mitigation funds. This valuation framework helps provide rigorous regional-scale quantification of nature-based coastal protection solutions for coastal risk management decisions.

Journal of Environmental Management

Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches

Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R 2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.

Illinois

Tectonics and metallogenesis of Proterozoic rocks of the Reading Prong

Detailed geologic mapping, petrography, and major and trace-element analyses of Proterozoic rocks from the Greenwood Lake Quadrangle, New York are compared with chemical analyses and stratigraphic information compiled for the entire Reading Prong. A persistent regional stratigraphy is evident in the mapped area whose geochemistry indicates protoliths consistent with a back-arc marginal basin sequence. The proposed marginal basin may have been floored by an older sialic basement and overlain by a basin-fill sequence consisting of a basal tholeiitic basalt, basic to intermediate volcanic or volcaniclastic rocks and carbonate sediments, a bimodal calc-alkaline volcanic sequence, and finally volcaniclastic, marine, and continental sediments. The presence of high-chlorine biotite and scapolite may indicate circulation of brine fluids or the presence of evaporite layers in the sequence. Abundant, stratabound magnetite deposits with a geologic setting very unlike that of cratonic, Proterozoic banded-iron formations are found throughout the proposed basin sequence. Associated with many of the magnetite deposits is unusual uranium and rare-earth element mineralization. It is proposed here that these deposits formed in an exhalative, volcanogenic, depositional environment within an extensional back-arc marginal basin. Such a tectonic setting is consistent with interpretations of protoliths in other portions of the Reading Prong, the Central Metasedimentary Belt of the Canadian Grenville Province, and recent interpretation of the origin of the Franklin lead-zinc deposits, suggesting a more cohesive evolving arc/back-arc tectonic model for the entire Proterozoic margin of the north-eastern portion of the North American craton. Published by Elsevier Ltd.

Journal of Geodynamics

Building hierarchical models of avian distributions for the State of Georgia

To predict the distributions of breeding birds in the state of Georgia, USA, we built hierarchical models consisting of 4 levels of nested mapping units of decreasing area: 90,000 ha, 3,600 ha, 144 ha, and 5.76 ha. We used the Partners in Flight database of point counts to generate presence and absence data at locations across the state of Georgia for 9 avian species: Acadian flycatcher (Empidonax virescens), brownheaded nuthatch (Sitta pusilla), Carolina wren (Thryothorus ludovicianus), indigo bunting (Passerina cyanea), northern cardinal (Cardinalis cardinalis), prairie warbler (Dendroica discolor), yellow-billed cuckoo (Coccyxus americanus), white-eyed vireo (Vireo griseus), and wood thrush (Hylocichla mustelina). At each location, we estimated hierarchical-level-specific habitat measurements using the Georgia GAP Analysis18 class land cover and other Geographic Information System sources. We created candidate, species-specific occupancy models based on previously reported relationships, and fit these using Markov chain Monte Carlo procedures implemented in OpenBugs. We then created a confidence model set for each species based on Akaike's Information Criterion. We found hierarchical habitat relationships for all species. Three-fold cross-validation estimates of model accuracy indicated an average overall correct classification rate of 60.5%. Comparisons with existing Georgia GAP Analysis models indicated that our models were more accurate overall. Our results provide guidance to wildlife scientists and managers seeking predict avian occurrence as a function of local and landscape-level habitat attributes.

Journal of Wildlife Management

The impact of antecedent fire area on burned area in southern California coastal ecosystems

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ∼ 0.25).

California