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Dynamic Island allows you to customize the size of the dynamic island to fit the notch or front camera hole of your device. You can choose the width, length, and position depending on where the camera is. Thanks to this, the space will remain invisible, and notifications will be \"born\" from the notch to the rest of the screen. You can test the animation from the app to see that everything works correctly.

Dynamic Island allows you to customize the size of the dynamic island to fit the notch or front camera hole of your device. You can choose the width, length, and position depending on where the camera is. Thanks to this, the space will remain invisible, and notifications will be "born" from the notch to the rest of the screen. You can test the animation from the app to see that everything works correctly.

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As a bird artist, I am constantly sifting through photo reference, looking for just the right image for my next drawing or painting. I believe that the best bird photos depict dynamic, lively poses. In this post, I share what I look for in an image and why I choose one image over another.

Hi yall. I'm working through the levels and there are background noises in some of the levels (screeching in the ancient statue level, birds squawking in the ship level) and they're so annoying honestly. I've tried to play around with the settings but I can't figure it out. Please help

One of the most contentious questions in evolutionary biology is, how did the Amazon become so rich in species? A new study focused on birds examines how the movements of rivers in the Amazon have contributed to that area's exceptional biological diversity. The research team, led by the American Museum of Natural History, found that as small river systems change over time, they spur the evolution of new species. The findings also reveal previously unknown bird species in the Amazon that are only found in small areas next to these dynamic river systems, putting them at high risk of imminent extinction. The study is detailed today in the journal Science Advances.

"Even though birds can fly, our study confirmed that current rivers across the Southern Amazon rainforest, even relatively small ones, are highly effective at isolating populations of these six species, which leads to genomic divergence and ultimately speciation," said the study's senior author Joel Cracraft, Lamont Curator and curator-in-charge in the Museum's Department of Ornithology.

However, because these rivers move around the landscape at different time scales, their movements can have varying outcomes for bird species: when river rearrangements occur quickly, populations of birds on each side can merge before they've had time to differentiate; when river changes happen slowly, species have a longer time to diverge from one another; and when rivers change at intermediate rates, bird populations diverge and then join back together and co-occur when a river moves.

More information:Lukas J. Musher, River network rearrangements promote speciation in lowland Amazonian birds, Science Advances (2022). DOI: 10.1126/sciadv.abn1099. www.science.org/doi/10.1126/sciadv.abn1099Journal information:Science Advances

Species distribution models (SDM) link species occurrence with a suite of environmental predictors and have a wide range of applications in wildlife science and management by predicting species distributions across landscapes. They provide a powerful tool for land managers when the variable set captures the biological requirements of the species and can be manipulated to account for various management activities [1]. The resulting suitability metrics are most relevant to population dynamics in anthropogenically disturbed ecosystems when linked with measures of reproductive success and applied to a suite of restoration alternatives [2].

Additionally, increasing evidence suggests that changes in long-term habitat quality and prey availability have disparately affected wading bird species with a more constrained foraging niche (i.e., specialists; [17,24]. Across the Everglades, populations of wading bird species that require higher prey concentration, such as tactile foragers (i.e., White Ibis [Eudocimus albus] and Wood Stork [Mycteria americana]; hereafter ibises and storks), have disproportionally decreased from the 1930s to 2001 when compared with populations of visual foragers that favor relatively deeper water and have lower giving-up-densities of prey ([13]; i.e., Great Egret [Ardea alba]; hereafter egrets). This pattern likely indicates an overall decline in prey availability [14]. In addition, the ibis and stork, while similar in foraging strategy, differ in other traits such as prey size selection, foraging flight distance, nest initiation date, and nest cycle length [27] and thus may serve unique functions as indicators.

Here, we developed a modeling framework to predict habitat selection and abundance of three representative species of wading birds (egrets, ibises, and storks) using long-term, spatially explicit observational records combined with high temporal-resolution environmental predictors. This approach served three purposes: (1) to capture changing preference of wading birds across resource gradients, (2) to determine the effect of resource gradients on conspecific attraction, and (3) to evaluate species abundance in terms of the ecological trade-offs associated with the quantity, timing, and distribution of water. Furthermore, models included measures to account for both spatial autocorrelation and the area of available habitat. Using a multi-model approach, we aggregated wading bird foraging distributions over 1) space (temporal model) and 2) time (spatial model) to reduce the noise associated with individual locations and isolate variables representing processes that operate at different spatial and temporal scales. A spatial foraging conditions model (SFC) examined spatial and hydrological dynamics at a fixed spatial scale (i.e., cell) to predict wading bird frequency of use over time, whereas a temporal foraging conditions model (TFC) predicted flock and individual abundance across the landscape from daily habitat selection influenced by hydrological processes. The two models can be used to derive quantitative management indices for variation in patch quality (TFC) and patch abundance (SFC) over the landscape.

Cell use by storks was best predicted by the terms Depth, Depth2, Recession2, DSD, DSD2, HP, HP2, and Depth* DSD (Table 6). The form of the depth response was similar to that of ibis with a peak at low values of depth (~15 cm). Quadratic DSD and hydroperiod terms showed a peak in use at ~450 DSD, a sharp decline thereafter, and an increase in use at longer hydroperiods. Finally, differences in DSD primarily affected use of shallow water, with use increasing under long DSD (> 343 days) and decreasing under short DSD (< 343 days). This corroborates results from the egret and ibis model that higher DSD use was associated with many more birds when the associated high prey density was concentrated in shallow water. After accounting for residual spatial correlation, cell use by storks was higher in ENP and slightly lower in BCNP.

Results confirmed that selection for individual resources (prey availability, concentration, and production) varied given their availability across a decadal gradient of environmental conditions (i.e., dynamic habitat selection). Selection was further influenced by the availability of resources produced over differing temporal scales (daily to multi-annual). This often occurred under low resource availability, but also under circumstances when resources were plentiful and food could be selectively exploited.

We restricted habitat availability (i.e., depths) to observed wading bird foraging ranges, and all species selected locations with shallower water when available landscape depths were at the high and low ends of the hydrological gradient. In the early dry season when most of the landscape is wet, the few shallow areas are targeted by wading birds. In contrast, at the end the dry season, birds select shallower water to exploit concentrated prey resources. These results suggest that selection for water depth can occur in response to both limitation and exploitation over the gradient of landscape conditions. This idea is supported by wading bird resource selection functions, demonstrating that selection of water depths can change with different available conditions [17].

All species used higher recession rates when available, further demonstrating its important function as a prey concentrating process. Selection of higher rates was most evident when recession rate heterogeneity was high, driven by local rainfall events. These temporary interruptions to the drying process can lead to prey dispersal and reduced rates of capture [13,16]. However, this study demonstrates that wading birds can identify locations where disruptions have been minimal. Higher recession rates were also selected in a dryer landscape when these sites could be accessed in shallow water. Similar to depth use, selection occurred when a particular resource was potentially limiting and when it could be exploited.

Peak flock and individual abundance were observed in all species when landscape depth heterogeneity was high and individuals had a variety of depth choices. Under the wettest conditions, high heterogeneity was available to egrets, which can exploit deeper water. For ibis and storks, high depth heterogeneity occurred at the middle one-third of the hydrological gradient and limited ibis and stork abundance under wetter (and dryer) conditions. This reaffirms the importance of a landscape high in spatial heterogeneity from previous reports [13,17,25] and demonstrates that the significant loss of short hydroperiod wetlands may have caused a delay in nesting initiations of searcher species by decreasing the depth heterogeneity at the beginning of particularly wet years [13,25]. This spatial limitation also increases wading bird dependence on high drying rates to provide shallow depths early in the dry season that may have changed the species response to recession rate. While high recession rates were not necessarily a historical requirement of successful breeding, they provide new high quality patches that are exposed in suitable depths and may ease the loss of foraging habitat that would have been suitable under wetter conditions [17,26]. 9af72c28ce