50 research outputs found
EFFECTS OF WIND FARMS ON SAND HILL CRANE PLAY A OCCUPANCY ON THE TEXAS HIGH PLAINS
Wind energy is essential for a shift to carbon-emission free energy, however there has been very little research investigating the disturbance caused by wind farms on the landscape. Texas is a leading state in wind power capacity, and the High Plains of Texas support over 80% of the midcontinent population of sandhill cranes (Grus canadensis) every winter. Historically, cranes used saline lakes for fresh water and predator protection, but recent hydrological changes due to agricultural practices have reduced the availability of the lakes for wintering birds. Playa wetlands currently represent the main source of water and roosting habitat in the High Plains. We examined crane occupancy of playa wetlands in 4 counties of Texas during the fall and winters of 2009-10 and 2010-11. In addition to recording presence/no presence, we recorded multiple variables and used information theory and AICc to develop models which best explained crane occupancy. Using occupancy modeling methods to survey playas in Texas resulted in no combination of variables explaining crane presence or absence in playas, most likely because cranes likely move between playas freely on their winter habitat. As playas are a vital part of their winter ecology, sandhill crane use and movement between them should be further examined to better describe crane use of their winter landscape and better plan and manage for large scale habitat alterations, such as the large increase in the number of wind turbines across the High Plains
SANDHILL CRANE COLLISIONS WITH WIND TURBINES IN TEXAS
The High Plains of the United States have been experiencing a large increase in wind energy generation sites with the American Wind Energy Association reporting an increase across America from 10 total installed gigawatts in 2006 to 60 total installed gigawatts in 2012. (American Wind Energy Association 2012). The High Plains also coincides with the Central Flyway in North America which is used by numerous bird species during migration, some with large bodies and high wing loading including the sandhill cranes (Grus canandensis), whooping cranes (G. americana), and waterfowl. Species such as these tend to be more vulnerable to mortality from strikes with structures due to reduced maneuverability (Bevenger 1998). Texas is currently 1 of the top 5 producers of wind power generation, and installation of wind power is expected to increase due to its high wind capabilities (American Wind Energy Association 2012).
Eighty percent of the midcontinent sandhill crane population migrates to northwestern Texas every winter (Iverson et al. 1985), and the entire wild North American whooping crane population migrates through northern Texas to winter along the coast of the Gulf of Mexico (Stehn 2010). More wind turbines on the landscape may put these populations of cranes at risk for increased turbine collisions
Urban Amphibians of the Texas Panhandle: Baseline Inventory and Habitat Associations in a Drought Year
Habitat loss, degradation, and fragmentation due to urbanization are implicated in amphibian declines worldwide. Conservation efforts require information on resident species and their habitat interactions, but amphibian ecology is largely unstudied in urban centers of the Southern High Plains. Here, we gathered baseline data on amphibian presence, species richness, and habitat preferences at site-specific and landscape scales during a severe drought year in the city of Lubbock, in northwestern Texas. Ephemeral playa wetlands are characteristic of this landscape. During urbanization, these have been extensively modifiied for stormwater drainage, agriculture, and construction of roads, buildings and neighborhoods. A semi-arid climate with frequent droughts, together with urbanization, could have an adverse effect on resident amphibians. In 2011, we sampled 23 urban lakes for amphibian presence, using a combination of audio, visual, and larval surveys. We detected five amphibian species at seven lakes; Texas Toads (Anaxyrus speciosus) and Spotted Chorus Frogs (Pseudacris clarkii) were the most frequently encountered species. We found significant negative effects of nearby road density on amphibian species presence and richness. We also detected significant negative effects of basic pH on amphibian species richness. These data can be used for prioritizing lakes for amphibian conservation strategies, to monitor ecosystem function in urban wetlands, and to guide future development and restoration efforts
Acute Opioid Withdrawal Mimicking Postoperative Joint Infection Following anterior cruciate ligament (ACL) Reconstruction: A Case Report.
BACKGROUND A short course of opioid narcotics is often prescribed for postoperative anterior cruciate ligament (ACL) reconstruction pain management. Unfortunately, there is a well-documented incidence of opioid withdrawal syndrome (OWS) following short-term use of these medications. OWS can present with symptoms such as influenza-like illness. It is important to differentiate OWS from infectious illnesses, especially after surgery. CASE REPORT We present a case of OWS in a patient who underwent ACL reconstruction 7 days prior. The patient\u27s OWS symptoms were similar to symptoms of a postoperative infection. The knee was aspirated, and the analysis of the aspirate was not concerning for an infection. The patient\u27s symptoms spontaneously resolved on postoperative day 10. This is the first documented case of OWS mimicking ACL reconstruction joint infection. CONCLUSIONS OWS after surgery may present with symptoms similar to joint infection. It is important to consider OWS as a potential complication after surgery and differentiate it from infection to avoid any further unnecessary invasive treatments for the patient
Projecting marine mammal distribution in a changing climate
Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations
Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0):Model Development, Network Assessment, and Budget Comparison
Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).</p
Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
Wetlands are responsible for 20%-31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency similar to 0.52-0.63 and 0.53). UpCH(4) estimated annual global wetland CH4 emissions of 146 +/- 43 TgCH4 y(-1) for 2001-2018 which agrees closely with current bottom-up land surface models (102-181 TgCH4 y(-1)) and overlaps with top-down atmospheric inversion models (155-200 TgCH4 y -1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25 degrees from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ ORNLDAAC/2253).Plain Language Summary Wetlands account for a large share of global methane emissions to the atmosphere, but current estimates vary widely in magnitude (similar to 30% uncertainty on annual global emissions) and spatial distribution, with diverging predictions for tropical rice growing (e.g., Bengal basin), rainforest (e.g., Amazon basin), and floodplain savannah (e.g., Sudd) regions. Wetland methane model estimates could be improved by increased use of land surface methane flux data. Upscaling approaches use flux data collected across globally distributed measurement networks in a machine learning framework to extrapolate fluxes in space and time. Here, we train and evaluate a methane upscaling model (UpCH4) and use it to generate monthly, globally gridded wetland methane emissions estimates for 2001-2018. The UpCH4 model uses only six predictor variables among which temperature is dominant. Global annual methane emissions estimates and associated uncertainty ranges from upscaling fall within state-of-the-art model ensemble estimates from the Global Carbon Project (GCP) methane budget. In some tropical regions, the spatial pattern of UpCH4 emissions diverged from GCP predictions, however, inclusion of flux measurements from additional ground-based sites, together with refined maps of tropical wetlands extent, could reduce these prediction uncertainties
Contrasting effects of nitrogenous pollution on fitness and swimming performance of Iberian waterfrog, Pelophylax perezi (Seoane, 1885), larvae in mesocosms and field enclosures
EFFECTS OF WIND FARMS ON SAND HILL CRANE PLAY A OCCUPANCY ON THE TEXAS HIGH PLAINS
Wind energy is essential for a shift to carbon-emission free energy, however there has been very little research investigating the disturbance caused by wind farms on the landscape. Texas is a leading state in wind power capacity, and the High Plains of Texas support over 80% of the midcontinent population of sandhill cranes (Grus canadensis) every winter. Historically, cranes used saline lakes for fresh water and predator protection, but recent hydrological changes due to agricultural practices have reduced the availability of the lakes for wintering birds. Playa wetlands currently represent the main source of water and roosting habitat in the High Plains. We examined crane occupancy of playa wetlands in 4 counties of Texas during the fall and winters of 2009-10 and 2010-11. In addition to recording presence/no presence, we recorded multiple variables and used information theory and AICc to develop models which best explained crane occupancy. Using occupancy modeling methods to survey playas in Texas resulted in no combination of variables explaining crane presence or absence in playas, most likely because cranes likely move between playas freely on their winter habitat. As playas are a vital part of their winter ecology, sandhill crane use and movement between them should be further examined to better describe crane use of their winter landscape and better plan and manage for large scale habitat alterations, such as the large increase in the number of wind turbines across the High Plains