Explore the vast range of titles available.

In northern climates, spring is a time of rapid environmental change: for migrating terrestrial animals, melting snow facilitates foraging and travel, and newly emergent vegetation provides a valuable nutritional resource. These changes result in selection on the timing of important life-history events such as migration and parturition occurring when high-quality resources are most abundant. We examined the timing of female caribou (Rangifer tarandus, n = 94) migration and parturition in five herds across 7 yr in Newfoundland, Canada, as a function of two measures of environmental change—snowmelt and vegetation green-up. We generated resource selection functions to test whether caribou selected for areas associated with snowmelt and green-up during migration and following calving. We found that caribou migrated approximately 1 wk prior to snowmelt, with the flush of emergent vegetation occurring during the weeks following parturition. The results indicate that caribou “jump” the green wave of emergent forage and do so by tracking the receding edge of melting snow, likely reducing movement and foraging costs related to snow cover. Our research further broadens the ecological scope of resource tracking in animals. We demonstrate that resource tracking extends beyond resources directly related to foraging to those related to movement. We also show that snowmelt provides an environmental cue that may provide a buffer against changing environmental conditions.

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green‐up is heterogeneous and propagates across space in a wave‐like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher‐quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears Ursus arctos across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions (RSFs), we found that variation in proxies of vegetative forage quality better explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed effects models. Green wave tracking in brown bears was explained by the variation in availability of green‐up within spring home ranges, and how green‐up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non‐migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.

The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade‐off between digestibility and biomass in forage by selecting vegetation at intermediate growth. The green wave hypothesis (GWH) extends the FMH to suggest how spatiotemporal heterogeneity in plant quality shapes migratory movements of herbivores. Growing empirical support for these hypotheses mainly comes from studies in vast landscapes with large‐scale habitat heterogeneity. It is unclear, however, to what extent ungulates surf green waves in human‐altered landscapes with small‐scale heterogeneity in terms of land use and topography. We used plant phenological proxies derived from Sentinel 2 satellite data to analyze the habitat selection of 93 collared red deer (Cervus elaphus) in montane and alpine habitats. Using a step selection analysis, we investigated how plant phenology, that is, the instantaneous rate of green‐up (IRG) and normalized difference vegetation index (NDVI), and a set of variables describing topography and human presence influenced red deer resource selection in open habitats. We learned that red deer selected areas with high biomass at green‐up and avoided habitats with possible exposure to human activity. Additionally, landscape structure and topography strongly influenced spatial behavior of red deer. We further compared cumulative access to high‐quality forage across migrant strategies and found migrants gained better access than residents. Many migratory individuals surfed the green wave, and their surfing behavior, however, became less pronounced with decreasing distance to settlements. Within the constraints of topography and human land use, red deer track spring green‐up on a fine spatiotemporal scale and follow the green wave across landscapes in migration movements. Thus, they benefit from high‐quality forage even in human‐dominated landscapes with small‐scale heterogeneity and vegetation emerging in a heterogenic, dynamic mosaic. In the human‐dominated landscapes of Central Europe, red deer surf the wave of spring green‐up, however, its habitat selection is strongly governed by complex topography, human presence and land use. About two thirds of the population under study exhibited migratory behaviour, thereby gaining better access to high quality forage than residential individuals.

The ability to freely move across the landscape to track the emergence of nutritious spring green-up (termed ‘green-wave surfing’) is key to the foraging strategy of migratory ungulates. Across the vast landscapes traversed by many migratory herds, habitats are being altered by development with unknown consequences for surfing. Using a unique long-term tracking dataset, we found that when energy development occurs within mule deer ( Odocoileus hemionus ) migration corridors, migrating animals become decoupled from the green wave. During the early phases of a coalbed natural gas development, deer synchronized their movements with peak green-up. But faced with increasing disturbance as development expanded, deer altered their movements by holding up at the edge of the gas field and letting the green wave pass them by. Development often modified only a small portion of the migration corridor but had far-reaching effects on behaviour before and after migrating deer encountered it, thus reducing surfing along the entire route by 38.65% over the 14-year study period. Our study suggests that industrial development within migratory corridors can change the behaviour of migrating ungulates and diminish the benefits of migration. Such disruptions to migratory behaviour present a common mechanism whereby corridors become unprofitable and could ultimately be lost on highly developed landscapes. Analysing a long-term tracking dataset of migrating mule deer, the authors show that the expansion of natural gas energy infrastructure over 14 years along a migratory corridor changes deer behaviour and reduces by more than 38% their ability to keep pace with spring vegetation green-up.

The “green wave” hypothesis posits that during spring consumers track spatial gradients in emergent vegetation and associated foraging opportunities. This idea has largely been invoked to explain animal migration patterns, yet the general phenomenon underlies trends in vertebrate reproductive chronology as well. We evaluated the utility of this hypothesis for predicting spatial variation in nest initiation of greater sage‐grouse (Centrocerus urophasianus), a species of conservation concern in western North America. We used the Normalized Difference Vegetation Index (NDVI) to map the green wave across elevation and then compiled dates and locations of >450 sage‐grouse nests from 20 study sites (2000–2014) to model nest initiation as a function of the start of the growing season (SOS), defined here as the maximum daily rate of increase in NDVI. Individual sites were drawn from three ecoregions, distributed over 4.5° latitude, and spanning 2,300 m in elevation, which captured the climatic, edaphic, and floristic diversity of sagebrush ecosystems in the southern half of current sage‐grouse range. As predicted, SOS displayed a significant, positive relationship with elevation, occurring 1.3 days later for each 100 m increase in elevation. In turn, sage‐grouse nest initiation followed SOS by 22 ± 10 days (r2 = .57), with hatch dates falling on or just prior to the peak of the growing season. By timing nesting to the green wave, sage‐grouse chicks hatched when the abundance of protein‐rich invertebrate biomass is hypothesized to be nearing a seasonal high. This adaptation likely represents a strategy for maximizing reproductive success in the arid, variable environments that define sagebrush ecosystems. Given projected changes in climate and land use, these results can be used to predict periods of relative sensitivity to habitat disturbance for sage‐grouse. Moreover, the near real‐time availability of satellite imagery offers a heretofore underutilized means of mapping the green wave, planning habitat restoration, and monitoring range conditions. We tested the hypothesis that sage‐grouse nesting chronology would correspond to the “green wave.” Sage‐grouse nest initiation tracked the start of the growing season (the “green wave”) by 22 ± 10 days, with hatch dates falling on or just prior to the peak of the growing season. This adaptation likely represents a strategy for maximizing reproductive success in the arid and variable environments that define sagebrush ecosystems.

Summary Large herbivores gain nutritional benefits from following the sequential flush of newly emergent, high‐quality forage along environmental gradients in the landscape, termed green wave surfing. Which landscape characteristics underlie the environmental gradient causing the green wave and to what extent landscape characteristics alone explain individual variation in nutritional benefits remain unresolved questions. Here, we combine GPS data from 346 red deer (Cervus elaphus) from four partially migratory populations in Norway with the satellite‐derived normalized difference vegetation index (NDVI), an index of plant phenology. We quantify whether migratory deer had access to higher quality forage than resident deer, how landscape characteristics within summer home ranges affected nutritional benefits, and whether differences in landscape characteristics could explain differences in nutritional gain between migratory and resident deer. We found that migratory red deer gained access to higher quality forage than resident deer but that this difference persisted even after controlling for landscape characteristics within the summer home ranges. There was a positive effect of elevation on access to high‐quality forage, but only for migratory deer. We discuss how the landscape an ungulate inhabits may determine its responses to plant phenology and also highlight how individual behavior may influence nutritional gain beyond the effect of landscape. Herbivores follow the onset of plant growth in spring to obtain a higher quality diet, termed “green‐wave surfing.” We show that landscape characteristics considerably affect nutritional gain of migratory herbivores, but behavioral differences among individuals in the same landscape also play a role for how much deer benefit from green‐wave surfing.

With growth of Urban Road Traffic Volume and the increase of Road Network Density, correlation between adjacent road intersections is becoming more and more obvious. An intersection traffic signal adjustment tends to affect the health of a number of adjacent intersections road traffic flow. Its congestion may over time gradually spread to within a few blocks and regions all around the intersection. Therefore increasingly high demands of urban traffic signal control make a variety of advanced control technology integration, achieve the purpose to adjust a control parameter, in order to achieve dynamic coordination within the city - wide traffic control, to satisfy traffic demands, and then let the road traffic and the transport demand make a new balance. And This article introduces is the use of the green wave effect collaborative strategies adjacent green extension of fuzzy control in order to solve the problem of coupling between intersections road. This algorithm makes Signal Timing to be more flexible.

This work documents how the midlatitude, eddy-driven jets respond to climate change using model output from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The authors consider separately the North Atlantic, the North Pacific, and the Southern Hemisphere jets. The analysis is not limited to annual-mean changes in the latitude and speed of the jets, but also explores how the variability of each jet changes with increased greenhouse gases. All jets are found to migrate poleward with climate change: the Southern Hemisphere jet shifts poleward by 2° of latitude between the historical period and the end of the twenty-first century in the representative concentration pathway 8.5 (RCP8.5) scenario, whereas both Northern Hemisphere jets shift by only 1°. In addition, the speed of the Southern Hemisphere jet is found to increase markedly (by 1.2 m s−1between 850 and 700 hPa), while the speed remains nearly constant for both jets in the Northern Hemisphere. More importantly, it is found that the patterns of jet variability are a strong function of the jet position in all three sectors of the globe, and as the jets shift poleward the patterns of variability change. Specifically, for the Southern Hemisphere and the North Atlantic jets, the variability becomes less of a north–south wobbling and more of a pulsing (i.e., variation in jet speed). In contrast, for the North Pacific jet, the variability becomes less of a pulsing and more of a north–south wobbling. These different responses can be understood in terms of Rossby wave breaking, allowing the authors to explain most of the projected jet changes within a single dynamical framework.

North China Plain is the heartland of modern China. This fertile plain has experienced vast expansion of irrigated agriculture which cools surface temperature and moistens surface air, but boosts integrated measures of temperature and humidity, and hence enhances intensity of heatwaves. Here, we project based on an ensemble of high-resolution regional climate model simulations that climate change would add significantly to the anthropogenic effects of irrigation, increasing the risk from heatwaves in this region. Under the business-as-usual scenario of greenhouse gas emissions, North China Plain is likely to experience deadly heatwaves with wet-bulb temperature exceeding the threshold defining what Chinese farmers may tolerate while working outdoors. China is currently the largest contributor to the emissions of greenhouse gases, with potentially serious implications to its own population: continuation of the current pattern of global emissions may limit habitability in the most populous region, of the most populous country on Earth. Irrigation increases the intensity of heatwaves over the North China Plain but how this will be exacerbated by climate change has not been quantified. Here the authors show that irrigation enhances magnitude of extreme wet-bulb temperature and intensity of heatwaves in this region.