991 resultados para Bird surveying method
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The aim of this study was to evaluate a simple molecular method of reverse transcriptase polymerase chain reaction (RT-PCR) to differentiate Newcastle disease virus strains according to their pathogenicity, in order to use it in molecular screening of Newcastle disease virus in poultry and free-living bird populations. Specific primers were developed to differentiate LaSota-LS-(vaccine strain) and Sao Joao do Meriti-SJM-strain (highly pathogenic strain). Chickens and pigeons were experimentally vaccinated/infected for an in vivo study to determine virus shedding in feces. Validation of sensitivity and specificity of the primers (SJM and LS) by experimental models used in the present study and results obtained in the molecular analysis of the primers by BLAST made it possible to generalize results. The development of primers that differentiate the level of pathogenicity of NDV stains is very important, mainly in countries where real-time RT-PCR is still not used as a routine test. These primers were able to determine the presence of the agent and to differentiate it according to its pathogenicity. © 2012 Springer Science+Business Media B.V.
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Airports worldwide are at a disadvantage when it comes to being able to spot birds and warn aircrews about the location of flocks either on the ground or close to the airfield. Birds simply cannot be easily seen during the day and are nearly invisible targets for planes at night or during low visibility. Thermal imaging (infrared) devices can be used to allow ground and tower personnel to pinpoint bird locations day or night, thus giving the airport operators the ability to launch countermeasures or simply warn the aircrews. This technology is available now, though it has been predominately isolated to medical and military system modifications. The cost of these devices has dropped significantly in recent years as technology, capability, and availability have continued to increase. Davison Army Airfield (DAAF), which is located about 20 miles south of Ronald Reagan National Airport in Washington, DC, is the transient home to many bird species including an abundance of ducks, seagulls, pigeons, and migrating Canadian geese. Over the past few years, DAAF implemented a variety of measures in an attempt to control the bird hazards on the airfield. Unfortunately, when it came to controlling these birds on or near our runways and aircraft movement areas we were more reactive than proactive. We would do airfield checks several times an hour to detect and deter any birds in these areas. The deterrents used included vehicle/human presence, pyrotechnics, and the periodic use of a trained border collie. At the time, we felt like we were doing all we could to reduce the threat to aircraft and human life. It was not until a near fatal accident in October 1998, when we truly realized how dangerous our operating environment really was to aircraft at or near the airfield. It was at this time, we had a C-12 (twin-engine passenger plane) land on our primary runway at night. The tower cleared the aircraft to land, and upon touchdown to the runway the aircraft collided with a flock of geese. Neither the tower nor the crew of the aircraft saw the geese because they were obscured in the darkness. The end result was 12 dead geese and $374,000 damage to the C-12. Fortunately, there were no human fatalities, but it was painfully clear we needed to improve our method of clearing the runway at night and during low visibility conditions. It was through this realization that we ventured to the U.S. Army Communications and Electronics Command for ideas on ways to deal with our threat. It was through a sub-organization within this command, Night Vision Labs, that we realized the possibilities of modifying thermal imagery and infrared technology to detecting wildlife on airports.
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The remarks that I have prepared deal with direct contacts selling pest and bird control programs. I am going to limit my remarks to what I feel are the more important aspects of selling Bird Control. I think it is safe to say that one of the most difficult aspects of selling for most sales personnel is prospecting, that is, finding accounts to call on. Our sales personnel have to more or less come up with their own leads. They have to find out who to contact once they get there. I have found that the best prospect most of us have for selling Bird Control accounts are our present pest control accounts. Generally speaking, we try to main¬tain contact with our applicators in the field, who are in these accounts every day, asking them if there are any of their accounts that are having bird control problems. Another method of finding potential accounts, is driving around looking. It is more difficult to drive around and look for rat and/or roach problems, but generally speaking if a building or some type of business has a bird problem, it is fairly easy to locate. Another thing we can do is call on specific accounts. There are generally cer¬tain accounts that just by the manufacturing process do attract birds, for example: food plants, mills, beet plants, grain elevators, food processors, and so on. Other type operations which lend themselves to bird problems are industrial plants because of the super-structure (physical plant) that they have. Sub-stations and power plants are very attractive to birds. Some other situations that should be checked for bird problems are lumber yards and contractors' storage buildings. After deciding on a contact we get into what I call my basic four. There are four basic things that I try to impress upon our personnel to keep in mind when they go in to make a contact. The first one is the interview or actually making the contact so that you get an opportunity to have the interview, either calling for an appointment or making a "cold" call. The second one is closing for the survey. The third one is making the survey and preparing a proposal. The fourth and last one is the proposal presentation and closing of the sale. An additional item which would make a basic five is after you make the sale don't forget to follow up on the sale.
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Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.
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Notes from Henrik de Nie: The project started as a phenological study in cooperation with the (Dutch) meteorological institute (KNMI) to register the time of arrival of Fitis and Tjiftaf. During 1951 to 1969 he went every day to the wood (except 1966, in this year his wife died). Thereafter he went no more daily, but because he knew the wood very well and he was free to choice the day on which he did a survey, therefore he choose days with relatively good weather. He did not observe very common bird species, maybe because they are dependent on nest boxes and he did not want to be dependent on the management of the nest box-people (in fact I forgot precisely his arguments, and now I cannot ask him this): Common Starling; Eurasian Tree Sparrow (not common); Great Tit; Eurasian Blue Tit Pieter mentioned 14 species that scored many zero values or only one observation: Stock Dove; Common Cuckoo; Lesser Spotted Woodpecker; Eurasian Golden Oriole; Eurasian Nuthatch; Short-toed Treecreeper; Common Nightingale; Marsh Warbler; Lesser Whitethroat; Goldcrest; Common Firecrest (after 1970 he had difficulties in hearing these two species); Spotted Flycatcher; Eurasian Bullfinch; Black Woodpecker He also mentioned species that he found much fewer as: European Greenfinch; European Pied Flycatcher; Long-eared Owl; Red Crossbill; Sedge Warbler; Icterine Warbler; Eurasian Woodcock; Eurasian Siskin; European Green Woodpecker; Great Spotted Woodpecker; Eurasian Hobby; Western Barn Owl; Woodlark; Common Wood Pigeon; Little Owl; European Crested Tit; Hawfinch. But for these species I think that observations are strongly dependent on the number of visits to the wood. Also here, many zeros and few 1 x during the whole series of visits.
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We investigated the local bird community in Central Sulawesi (Indonesia), with focus on insectivorous species in the agroforestry landscapes adjacent to the Lore Lindu National Park. All study sites were situated at the northern tip of Napu Valley in Central Sulawesi, Indonesia. After an initial mapping of the study area, we selected 15 smallholder cacao plantations as sites for our study in March 2010. These sides were mainly used for bird and bat exclosure experiments. All sited were situated along a local gradient (shade availability on each plantation) and a landscape gradient (distance to primary forest), which were independent from each other. In September 2010 and from February until June 2011, we assessed the bird community on our 15 study sites using monthly point count and mist netting sampling. Point count (20 minutes between 07 am and 10 am and in between the net checking hours) and mist netting surveys (12 hours, between 05:30 am and 17:30 pm) were conducted simultaneously but only once per month on each study site, to avoid habituation of the local bird community to our surveys. Further, point counts were conducted at least 100 m apart from the mist netting sites, to avoid potential disturbance between the two methods. We discarded all observations beyond 50 m (including those individuals that flew over the canopy) from the statistical analysis, as well as recaptures of individuals within identical mist netting rounds.
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The performance of the maximum ratio combining method for the combining of antenna-diversity signals in correlated Rician-fading channels is rigorously studied. The distribution function of the normalized signal-to-noise ratio (SNR) is expanded in terms of a power series and calculated numerically. This power series can easily take into account the signal correlations and antenna gains and can be applied to any number of receiving antennas. An application of the method to dual-antenna diversity systems produces useful distribution curves for the normalized SNR which can be used to find the diversity gain. It is revealed that signal correlation in Rician-fading channels helps to increase the diversity gain rather than to decrease it as in the Rayleigh fading channels. It is also shown that with a relative strong direct signal component, the diversity gain can be much higher than that without a direct signal component.
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This work is supported by the Hungarian Scientific Research Fund (OTKA), grant T042706.
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This thesis reports on a novel method to build a 3-D model of the above-water portion of icebergs using surface imaging. The goal is to work towards the automation of iceberg surveys, allowing an Autonomous Surface Craft (ASC) to acquire shape and size information. After collecting data and images, the core software algorithm is made up of three parts: occluding contour finding, volume intersection, and parameter estimation. A software module is designed that could be used on the ASC to perform automatic and fast processing of above-water surface image data to determine iceberg shape and size measurement and determination. The resolution of the method is calculated using data from the iceberg database of the Program of Energy Research and Development (PERD). The method was investigated using data from field trials conducted through the summer of 2014 by surveying 8 icebergs during 3 expeditions. The results were analyzed to determine iceberg characteristics. Limitations of this method are addressed including its accuracy. Surface imaging system and LIDAR system are developed to profile the above-water iceberg in 2015.
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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.
For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.
Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.
Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.
In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.
For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.
Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.
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Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.