Explore the vast range of titles available.

Migration has evolved as a strategy to maximize survival and reproductive success, driven by the search for better resources and/or predator avoidance. For ungulates at high latitudes, the search for higher quality and more abundant forage has been proposed as one of the best explanations of seasonal migrations. However, responses vary among populations, species, and ecosystems. In this study, we examine the forage resources associated with an annual migration of a herd of wood bison (Bison bison athabascae) in northeast Alberta, Canada. Timing of this migration corresponds to the neonatal period in late spring during green up when females have a higher nutritional demand imposed by gestation and maternal care of neonates. The objective of this work was to assess how forage quantity (i.e., biomass) and quality (i.e., crude protein and metabolizable energy, ME) differed between the herd's core and neonatal ranges while evaluating differences in their diet. Bison diets during winter in the core range were dominated by graminoids and shrubs, while shrubs and forbs were predominant in diets within the neonatal range from late spring through summer. Overall, the neonatal range during spring had significantly greater biomass (p < 0.001) of shrubs and forbs compared with the core range during the same season, being 1.7 and 3.8 times higher, respectively. The neonatal range also had comparatively more crude protein and ME (p < 0.001) during this season, with crude protein being 2.7 and 3.2 and ME being 3.0 and 3.7 times greater than in the core range for shrubs and forbs, respectively. Conversely, the core range had higher biomass, crude protein, and ME (p < 0.001) available for graminoids compared with the neonatal range during spring. However, graminoids are not particularly common in their diet during the migration period. Our results suggest that bison migration to the neonatal range, coincident with higher quantity and quality of forage, is important for female wood bison, particularly given their increased post‐parturition demands for energy and protein during this critical neonatal period. In this article, we examined the differences in forage quantity and quality between two defined ranges of a wood bison population as an attempt to identify possible factors influencing their migration during the neonatal period. We found significant differences in the forage quantity and quality between ranges, suggesting a link between these factors with bison migration in late spring, which aligns with the higher nutritional requirements that female bison are experiencing during this time of the year.

Our study focused on quantifying available forage and the conditions for avoiding predation provided within the home ranges of Siberian roe deer (Capreolus pygargus). We conducted transect surveys in both winter and summer–autumn home ranges of the Siberian roe deer in the Tieli Forestry Bureau of the Lesser Xing’an Mountains. Our results revealed significant differences: (1) In terms of the quantity and quality of available forage, the summer–autumn home range had substantially more available forage than the winter home range, with meadows and cornfields showing the highest edible biomass in each, respectively. In terms of forage quality, there were differences in hemicellulose, cellulose, and lignin content between the two ranges. (2) In terms of the conditions for avoiding predation, the winter home range had lower vegetation coverage and greater visibility, making escape strategies more viable. In contrast, the summer–autumn home range had denser vegetation and limited visibility, making hiding strategies more viable. Our study offers comprehensive insights into the available forage and the conditions for avoiding predation, which is crucial for wildlife conservation strategies and habitat management in the region, as it directly informs strategies that address the seasonal forage requirements and predation avoidance of these deer, ultimately enhancing their prospects for survival in the area.

Mechanistic explanations of herbivore spatial distribution have focused largely on either resource-related (bottom-up) or predation-related (top-down) factors. We studied direct and indirect influences on the spatial distributions of Serengeti herbivore hotspots, defined as temporally stable areas inhabited by mixed herds of resident grazers. Remote sensing and variation in landscape features were first used to create a map of the spatial distribution of hotspots, which was tested for accuracy against an independent data set of herbivore observations. Subsequently, we applied structural equation modeling to data on soil fertility and plant quality and quantity across a range of sites. We found that hotspots in Serengeti occur in areas that are relatively flat and located away from rivers, sites where ungulates are less susceptible to predation. Further, hotspots tend to occur in areas where hydrology and rainfall create conditions of relatively low-standing plant biomass, which, coupled with grazing, increases forage quality while decreasing predation risk. Low-standing biomass and higher leaf concentrations of N, Na, and Mg were strong direct predictors of hotspot occurrence. Soil fertility had indirect effects on hotspot occurrence by promoting leaf Na and Mg. The results indicate that landscape features contribute in direct and indirect ways to influence the spatial distribution of hotspots and that the best models incorporated both resource- and predation-related factors. Our study highlights the collective and simultaneous role of bottom-up and top-down factors in determining ungulate spatial distributions.

The viability of large herbivore populations in the face of climate change, environmental variability, disease and predation will be determined by their freedom to assess and respond to these factors through access to a range of functional seasonal resources and habitats. Their responses will be contingent upon various organismal traits, such as body size, mouth and digestive anatomy, which also facilitate coexistence among sympatric species. In this paper we develop a functional adaptive forage resource framework based on plant biomass, quality and phenology responses on ecological productivity gradients. We show how large herbivores coexist and respond to environmental variability, disease and predation by their foraging responses in relation to functional adaptive resources, as mediated by their anatomical traits. Below a critical body size, where predation limits population size, large herbivores adopt a variety of predation avoidance strategies, which are linked to their anatomical traits and foraging strategies. Mouth anatomy, and its interaction with body size, appears to be the major anatomical trait determining large herbivore selection for grass height. Body size is the major trait determining vulnerability to predators. Ecological productivity gradients underlain by variation in soil moisture availability over the annual cycle support high quality forage in the least productive (driest) regions, which promote growth and reproduction (a fecundity resource). Reserves of adequate quality forage in moderate productivity regions and buffers of low-quality forage in wetter and more productive regions of the gradient prevent loss of body stores over the dry season and starvation during droughts. Fire and grazing contribute towards providing high quality forage by removing old, low-quality material and preventing forage maturation. Consuming a high diversity of plant species distributed across ecological gradients promotes phytochemical diversity in the diet, which functions as medicinal resources to promote health while combating disease and parasites. Large herbivores are becoming increasingly restricted by ecosystem fragmentation in their access to the full range of these functional resource classes. The negative consequences for large herbivore populations of reduced access to these resource classes is compounded by climate change, where conditions are hotter and drought frequency and intensity is expected to be higher.

Large‐scale, high‐severity wildfires are increasingly frequent across the western United States. Fire severity affects the amount of vegetation removed and helps dictate what, where, and how many plants regenerate postfire, potentially altering the available habitat and nutritional landscape for wildlife. To evaluate the effects of fire severity on summer nutritional resources for elk (Cervus canadensis), we collected field data and remotely sensed information in Years 2 and 3 after a large‐scale wildfire to compare forage quality and quantity across forest types and fire severities within the summer range of one elk population in west‐central Montana. To understand the landscape‐level effects of fire severity on nutritional resources, we developed predictive forage quality and quantity models. We used these models to predict nutritional resources across the landscape for four landscape scenarios representing different fire severity patterns (i.e., an unburned landscape, a landscape burned only at low severity, a landscape burned only at high severity, and the observed landscape burned at mixed severity). Shortly after the wildfire, summer forage quality and herbaceous forage quantity increased in both burned mesic and dry mixed‐conifer forests regardless of fire severity. Summer shrub forage quantity was greater in unburned mesic and dry forests, and there was no difference between fire severities in dry forests. Low‐severity burned mesic forests had significantly greater shrub forage quantity compared with high‐severity burned mesic forests. The three predicted burned landscape scenarios had the highest percentage of the summer range with adequate forage quality, which increased throughout the summer. By contrast, the predicted unburned landscape had the lowest percentage of summer range with adequate forage quality, which decreased throughout the summer. Wildfire extended the duration in which elk can access high‐quality forage in the summer in Years 2 and 3 postfire. Therefore, shortly after a large‐scale wildfire, elk may be better able to meet their nutritional requirements, which may positively impact elk body condition, reproductive performance, and survival.

Supplement intake and liveweight (LW) data were collected daily and remotely by digital in-paddock technologies (electronic feeder (EF) and walk-over-weighing scale (WOW)) to study the effect of forage quantity and quality on the intake of a self-fed supplement (molasses-lick blocks (MLB)), LW, liveweight change (LWC), and feeding behaviour of grazing beef cattle. Fifty-two crossbred weaners were rotationally grazed or fed for 254 days on different forages: sudangrass (SG), autumn pastures (P), winter pastures with concentrate (P+C), oat crops (OC), lucerne hay (LH), and oaten hay (OH). Forage quantity and quality were measured on the day of entry (high feed availability) and exit (low feed availability) stages of grazing or hay delivery. The intake of MLB was 111% higher (p < 0.05) at low compared to high feed availability, and this was also reflected in the feeding behaviour of animals (e.g., greater feeding frequency and rate). Moreover, there was a large temporal variability of daily MLB intake (Coefficient of variation (CV) = 146.41%). Supplementing MLB improved LWC only with SG, P, or OH (p < 0.05). The behaviour of animals around MLB reflects changes in feed quantity and quality and could be used to enhance cattle grazing and nutritional management in real time.

Allometric scaling law predicts that herbivores respond differently to the availability of resources, mediated by body size. However, studies of allometric responses have often focused on animals with a relatively large difference in body size. Here, using a correlative field study, habitat use by two herbivorous species, the Bean Goose (Anser fabalis) and the Greater White-fronted Goose (A. albifrons), with a relatively small difference in body size was investigated during the wintering period. Both a generalized linear mixed model and a mixed logistic regression model showed that both species selected lower lying areas that were recently exposed, and, as expected, the smaller Greater White-fronted Goose showed a stronger selection of foraging habitat than the larger Bean Goose. Sward height also influenced habitat selection by both species, and the smaller species selected shorter swards than the larger species. In terms of forage quality, both models failed to detect a significant effect of nitrogen content on goose habitat selection. A logistic regression model showed that structural heterogeneity of the sward negatively correlated with the patch selection of the smaller species, but for the larger species such a correlation was not found. In agreement with our hypotheses, our results provide some preliminary indication that coexistence of the two goose species studied here might be mediated by an allometric response even if the difference in body size is relatively small.

To better address the issue of multi-threshold image segmentation, this paper proposes a hybrid adaptive crayfish optimization algorithm with differential evolution for color multi-threshold image segmentation (ACOADE). Due to the insufficient convergence ability of the crayfish optimization algorithm in later stages, it is challenging to find a more optimal solution for optimization. ACOADE optimizes the maximum foraging quantity parameter p and introduces an adaptive foraging quantity adjustment strategy to enhance the randomness of the algorithm. Furthermore, the core formula of the differential evolution (DE) algorithm is incorporated to balance ACOADE’s exploration and exploitation capabilities better. To validate the optimization performance of ACOADE, the IEEE CEC2020 test function was selected for experimentation, and eight other algorithms were chosen for comparison. To verify the effectiveness of ACOADE for threshold image segmentation, the Kapur entropy method and Otsu method were used as objective functions for image segmentation and compared with eight other algorithms. Subsequently, the peak signal-to-noise ratio (PSNR), feature similarity index measure (FSIM), structural similarity index measure (SSIM), and Wilcoxon test were employed to evaluate the quality of the segmented images. The results indicated that ACOADE exhibited significant advantages in terms of objective function value, image quality metrics, convergence, and robustness.

Understanding behavioral strategies employed by animals to maximize fitness in the face of environmental heterogeneity, variability, and uncertainty is a central aim of animal ecology. Flexibility in behavior may be key to how animals respond to climate and environmental change. Using a mechanistic modeling framework for simultaneously quantifying the effects of habitat preference and intrinsic movement on space use at the landscape scale, we investigate how movement and habitat selection vary among individuals and years in response to forage quality–quantity tradeoffs, environmental conditions, and variable annual climate. We evaluated the association of dynamic, biotic forage resources and static, abiotic landscape features with large grazer movement decisions in an experimental landscape, where forage resources vary in response to prescribed burning, grazing by a native herbivore, the plains bison (Bison bison bison), and a continental climate. Our goal was to determine how biotic and abiotic factors mediate bison movement decisions in a nutritionally heterogeneous grassland. We integrated spatially explicit relocations of GPS‐collared bison and extensive vegetation surveys to relate movement paths to grassland attributes over a time period spanning a regionwide drought and average weather conditions. Movement decisions were affected by foliar crude content and low stature forage biomass across years with substantial interannual variation in the magnitude of selection for forage quality and quantity. These differences were associated with interannual differences in climate and growing conditions from the previous year. Our results provide experimental evidence for understanding how the forage quality–quantity tradeoff and fine‐scale topography drives fine‐scale movement decisions under varying environmental conditions. This manuscript evaluates movement‐based habitat selection of adult female bison in an experimental landscape managed with prescribed fire. Using extensive field sampling of vegetation quality and quantity, we model biweekly vegetation dynamics to understand bison movement paths over seven growing seasons. We employ a mechanistic movement model to determine selection of static and dynamic habitats in average and below‐average forage production seasons.

Semi‐natural grasslands represent ecosystems with high biodiversity. Their conservation depends on the removal of biomass, for example, through grazing by livestock or wildlife. For this, spatially explicit information about grassland forage quantity and quality is a prerequisite for efficient management. The recent advancements of the Sentinel satellite mission offer new possibilities to support the conservation of semi‐natural grasslands. In this study, the combined use of radar (Sentinel‐1) and multispectral (Sentinel‐2) data to predict forage quantity and quality indicators of semi‐natural grassland in Germany was investigated. Field data for organic acid detergent fibre concentration (oADF), crude protein concentration (CP), compressed sward height (CSH) and standing biomass dry weight (DM) collected between 2015 and 2017 were related to remote sensing data using the random forest regression algorithm. In total, 102 optical‐ and radar‐based predictor variables were used to derive an optimized dataset, maximizing the predictive power of the respective model. High R2 values were obtained for the grassland quality indicators oADF (R2 = 0.79, RMSE = 2.29%) and CP (R2 = 0.72, RMSE = 1.70%) using 15 and 8 predictor variables respectively. Lower R2 values were achieved for the quantity indicators CSH (R2 = 0.60, RMSE = 2.77 cm) and DM (R2 = 0.45, RMSE = 90.84 g/m²). A permutation‐based variable importance measure indicated a strong contribution of simple ratio‐based optical indices to the model performance. In particular, the ratios between the narrow near‐infrared and red‐edge region were among the most important variables. The model performance for oADF, CP and CSH was only marginally increased by adding Sentinel‐1 data. For DM, no positive effect on the model performance was observed by combining Sentinel‐1 and Sentinel‐2 data. Thus, optical Sentinel‐2 data might be sufficient to accurately predict forage quality, and to some extent also quantity indicators of semi‐natural grassland. Radar (Sentinel‐1) and multispectral (Sentinel‐2) data were evaluated for mapping semi‐natural grassland forage quantity and quality indicators in Germany. The predictor dataset was optimized using permutation‐based variable importance, maximizing the predictive power of the random forest regression models. Simple ratios between the narrow near‐infrared and red‐edge region were among the most important variables. The model performance was only marginally increased by including Sentinel‐1 data.