Global Hydrology Resource Center

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Do artificial nests simulate nest success of greater sage-grouse?

Artificial nests have been used to study factors affecting nest success because researchers can manipulate them more than natural bird nests. Many researchers have questioned the validity of generalizing the results from artificial nests onto naturally occurring nests. Other studies have assessed the validity of artificial nest studies by simultaneously comparing overall depredation or daily survival rates, depredation timing, predator species, or habitat characteristics of artificial and natural nests. To evaluate how well artificial nests simulated nest success of greater sage-grouse (Centrocercus urophasianus; hereafter, sagegrouse), we used the unique approach of monitoring artificial nests (n = 69) placed in the natural nest bowls of sage-grouse in southern Wyoming, USA, during 2010 to 2011. Brown chicken eggs were placed in natural sage-grouse nests 7 to 14 days after the hatch or depredation of natural sage-grouse nests to compare artificial nest fate to the fate of natural sage-grouse nests. As secondary objectives, we placed cameras next to a subset of artificial nests to identify which predator species were depredating nests, and we assessed the effects of corvid (black-billed magpie [Pica hudsonia] and common raven [Corvus corax]) density, nest-site characteristics (i.e., anthropogenic development, landscape variables, and microhabitat) date of depredation, and presence of a camera near nest bowls on the depredation rate of all artificial nests. We found that depredation of artificial nests paralleled the fate of natural sagegrouse nests. Depredations were more likely to occur earlier in the summer (June to early July rather than late July to early August). Depredation of artificial nests was negligible as time progressed past the typical sage-grouse nesting season, supporting the hypothesis of predators using a search image to detect eggs. We also found that shorter perennial grass height and greater magpie densities were positively associated with the depredation rates of artificial nests. Camera-recorded depredation events verified that 4 badgers (Taxidea taxus), 2 magpies, and 1 domestic cow depredated artificial nests. Artificial nests may give managers insight into the expected nest success rates of sage-grouse in areas of conservation interest. However, care must be taken regarding placement and timing of artificial nests for reliable conclusions to be drawn from artificial nest studies. Furthermore, identifying predators based on artificial nests likely leads to inaccurate assessment of local species composition of nest depredators

Microhabitat Selection by Greater Sage-Grouse Hens During Brood Rearing

Greater sage-grouse (Centrocercus urophasianus) populations have declined throughout the western United States over the past century. Loss of large stands of sagebrush is a major factor leading to the decline of sage-grouse populations. We captured, marked, and tracked hen sage-grouse in Wyoming during the summer of 2012 to study where sage-grouse hens keep their chicks given the dual needs to provide them with food and to keep them safe from avian predators. Vegetation surveys and avian point counts were performed at early season brood locations, late-season brood locations, and random locations. We conducted multinomial models to determine which habitat variables were most informative in predicting site selection by hen sage-grouse. Hens with and without broods selected sites that had more shrub cover during the early-brood season but not during the late-brood season. During the early-brood season, hens without broods avoided sites where there were American kestrels (Falco sparverius) and common ravens (Corvus corax), but brood hens did not avoid these sites. During late-brood season, brood hens chose sites with fewer small-avian predators (e.g., black-billed magpies [Pica hudsonia] and American kestrels), as well as medium-sized avian predators, such as common ravens, Buteo hawks (Buteo spp.), and northern harriers (Circus cyaneus). Our results suggest that habitat selection by sage-grouse hens is focused more on avoiding predators than on finding food

Portraits of Complex Networks

We propose a method for characterizing large complex networks by introducing a new matrix structure, unique for a given network, which encodes structural information; provides useful visualization, even for very large networks; and allows for rigorous statistical comparison between networks. Dynamic processes such as percolation can be visualized using animations. Applications to graph theory are discussed, as are generalizations to weighted networks, real-world network similarity testing, and applicability to the graph isomorphism problem.Comment: 6 pages, 9 figure

ESDIS Standards Office (ESO): Requirements, Standards and Practices

The ESDIS Standards Office assists the ESDIS Project in formulating standards policy for NASA Earth Science Data Systems (ESDS), coordinates standards activities within ESDIS, and provides technical expertise and assistance with standards related tasks within the NASA Earth Science Data System Working Groups (ESDSWG). This poster summarizes information found on the earthdata.nasa.gov site that describes the ESO

Partisan Asymmetries in Online Political Activity

We examine partisan differences in the behavior, communication patterns and social interactions of more than 18,000 politically-active Twitter users to produce evidence that points to changing levels of partisan engagement with the American online political landscape. Analysis of a network defined by the communication activity of these users in proximity to the 2010 midterm congressional elections reveals a highly segregated, well clustered partisan community structure. Using cluster membership as a high-fidelity (87% accuracy) proxy for political affiliation, we characterize a wide range of differences in the behavior, communication and social connectivity of left- and right-leaning Twitter users. We find that in contrast to the online political dynamics of the 2008 campaign, right-leaning Twitter users exhibit greater levels of political activity, a more tightly interconnected social structure, and a communication network topology that facilitates the rapid and broad dissemination of political information.Comment: 17 pages, 10 figures, 6 table

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON