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Time is a fundamental component of ecological processes. How animal behavior changes over time has been explored through well-known ecological theories like niche partitioning and predator–prey dynamics. Yet, changes in animal behavior within the shorter 24-hr light–dark cycle have largely gone unstudied. Understanding if an animal can adjust their temporal activity to mitigate or adapt to environmental change has become a recent topic of discussion and is important for effective wildlife management and conservation. While spatial habitat is a fundamental consideration in wildlife management and conservation, temporal habitat is often ignored. We formulated a temporal resource selection model to quantify the diel behavior of 8 mammal species across 10 US cities. We found high variability in diel activity patterns within and among species and species-specific correlations between diel activity and human population density, impervious land cover, available greenspace, vegetation cover, and mean daily temperature. We also found that some species may modulate temporal behaviors to manage both natural and anthropogenic risks. Our results highlight the complexity with which temporal activity patterns interact with local environmental characteristics, and suggest that urban mammals may use time along the 24-hr cycle to reduce risk, adapt, and therefore persist, and in some cases thrive, in human-dominated ecosystems.

Understanding how biodiversity responds to urbanization is challenging, due in part to the single-city focus of most urban ecological research. Here, we delineate continent-scale patterns in urban species assemblages by leveraging data from a multi-city camera trap survey and quantify how differences in greenspace availability and average housing density among 10 North American cities relate to the distribution of eight widespread North American mammals. To do so, we deployed camera traps at 569 sites across these ten cities between 18 June and 14 August. Most data came from 2017, though some cities contributed 2016 or 2018 data if it was available. We found that the magnitude and direction of most species’ responses to urbanization within a city were associated with landscape-scale differences among cities. For example, eastern gray squirrel (Sciurus carolinensis), fox squirrel (Sciurus niger), and red fox (Vulpes vulpes) responses to urbanization changed from negative to positive once the proportion of green space within a city was >∼20%. Likewise, raccoon (Procyon lotor) and Virginia opossum (Didelphis virginiana) responses to urbanization changed from positive to negative once the average housing density of a city exceeded about 700 housing units/km². We also found that local species richness within cities consistently declined with urbanization in only the more densely developed cities (>∼700 housing units/km²). Given our results, it may therefore be possible to design cities to better support biodiversity and reduce the negative influence of urbanization on wildlife by, for example, increasing the amount of green space within a city. Additionally, it may be most important for densely populated cities to find innovative solutions to bolster wildlife resilience because they were the most likely to observe diversity losses of common urban species.

As land development infringes upon natural landscapes, habitat loss and fragmentation have prompted efforts to understand how wildlife communities respond to anthropogenic land development. However, due to the scarcity of high-resolution imagery of the landscape surveyed by these studies, research on the field has largely relied on low-resolution imagery to estimate how urbanization affects species occupancy or the ability of a species to inhabit a geographical area. This study addresses the issue by asking 1) whether landscape classification based on coarse- or fine-resolution landscape data serves as a more reliable indicator of species occupancy and how the conclusions we draw about the effects of urbanization on species occupancy might change when landscape types are defined by 2) coarse (low-scale) and 3) fine (high-scale) landscape classification. In this study, the term “biological narrative” is used to refer to the interpretation of the magnitude and nature of the effects that different landscapes had on a given species. This was done to better illustrate that different spatial resolutions may help us learn different things about species at a given place. Presence and absence data for five mammalian species were gathered using a 24-camera trapping transect established across Orange County, California over ten seasons between 2018 and 2020. I hypothesized that 1) metrics of landscape structure derived from fine-resolution landscape imagery would be a better indicator of species occupancy across the landscape gradient and that 2) qualitative and quantitative differences across coarse- and fine-scale classification schemes would favor the use of fine-scale landscape imagery to assess the effect of landscape structure in species occupancy. AIC-based model selection however, demonstrated that coarse-resolution metrics were generally stronger predictors for occupancy in large scale studies across all surveyed species, although fine-resolution metrics performed equally well in some species. Results also showed that although parallels exist across biological narratives derived from occupancy models using the simple- and extensive-landscape classification schemes, there were also noticeable differences. The effect of vegetative cover on coyote occupancy for instance, which had a strong positive effect across fine-resolution models but only a weak effect in coarse-resolution models, demonstrate that the use of fine-resolution landscape to tease apart landscape structure elements can advance our understanding of the effect of land development on wildlife by contributing new information about how specific elements of landscape structure influence species occupancy. This study demonstrates that in the absence of fine-resolution landscape imagery, coarse-resolution data can be a strong foundation for studies that aim to determine how urbanization affects wildlife distribution at a larger scale. However, this study also demonstrates that fine-resolution landscape imagery and classifications are necessary to further our understanding of wildlife biology by allowing us to measure how landscape features affect the presence of species. Furthermore, as this study focuses on wildlife ecology at a local scale and presents an accessible methodology for fine scale landscape classification, results derived from comparison of biological narratives across different spatial resolutions can help develop strategies to ameliorate further loss of biodiversity in sensitive habitats.

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining \"wind-on\" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from \"wind-off\" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of \"wind- off\" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of \"wind-off\" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

Time is a fundamental component of ecological processes. How animal behavior changes over time has been explored through well-known ecological theories like niche partitioning and predator-prey dynamics. Yet, changes in animal behavior within the shorter 24-hour light-dark cycle have largely gone unstudied. Understanding if an animal can adjust their temporal activity to mitigate or adapt to environmental change has become a recent topic of discussion and is important for effective wildlife management and conservation. While spatial habitat is a fundamental consideration in wildlife management and conservation, temporal habitat is often ignored. We formulated a temporal resource selection model to quantify the diel behavior of eight mammal species across ten U.S. cities. We found high variability in diel activity patterns within and among species and species-specific correlations between diel activity and human population density, impervious land cover, available greenspace, vegetation cover, and mean daily temperature. We also found that some species may modulate temporal behaviors to manage both natural and anthropogenic risks. Our results highlight the complexity with which temporal activity patterns interact with local environmental characteristics, and suggest that urban mammals may use time along the 24-hour cycle to reduce risk, adapt, and therefore persist in human-dominated ecosystems.

Improving confidence involves putting riders in a learning situation that is controlled but also offers a challenge. All distances in this article can be adjusted according to the level and needs of the trainer, rider and horse. Returning to the trot, you keep the horse straight down the long side toward the single cavalletti that is part of the gymnastic and ride back over the gymnastic. Tn.s allows you to work on the adjustability of your horse by riding the same distance with different striding.

Knowing that you have accomplished every test you faced at home will make it easier to tackle challenges in the ring, even if they are questions you have never seen before. Because horses vary widely in terms of their emotions, experiences and physical abilities, each one must be trained as a unique individual. Improving any horse's rideability requires a combination of identifying his strengths and weaknesses, choosing equipment that best suits him and practicing exercises that target his individual needs. Continue doing this until you produce a nice balance between your leg and rein aids so you're using a comparable amount of pressure and frequency with both aids and don't feel as if you're communicating entirely with your hands or entirely with your legs.

Background The CXCR4-CXCL12 axis plays an important role in the chronic lymphocytic leukemia (CLL)-microenvironment interaction. Overexpression of CXCR4 has been reported in different hematological malignancies including CLL. Binding of the pro-survival chemokine CXCL12 with its cognate receptor CXCR4 induces cell migration. CXCL12/CXCR4 signaling axis promotes cell survival and proliferation and may contribute to the tropism of leukemia cells towards lymphoid tissues and bone marrow. Therefore, we hypothesized that targeting CXCR4 with an IgG1 antibody, PF-06747143, may constitute an effective therapeutic approach for CLL. Methods Patient-derived primary CLL-B cells were assessed for cytotoxicity in an in vitro model of CLL microenvironment. PF-06747143 was analyzed for cell death induction and for its potential to interfere with the chemokine CXCL12-induced mechanisms, including migration and F-actin polymerization. PF-06747143 in vivo efficacy was determined in a CLL murine xenograft tumor model. Results PF-06747143, a novel-humanized IgG1 CXCR4 antagonist antibody, induced cell death of patient-derived primary CLL-B cells, in presence or absence of stromal cells. Moreover, cell death induction by the antibody was independent of CLL high-risk prognostic markers. The cell death mechanism was dependent on CXCR4 expression, required antibody bivalency, involved reactive oxygen species production, and did not require caspase activation, all characteristics reminiscent of programmed cell death (PCD). PF-06747143 also induced potent B-CLL cytotoxicity via Fc-driven antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity activity (CDC). PF-06747143 had significant combinatorial effect with standard of care (SOC) agents in B-CLL treatment, including rituximab, fludarabine (F-ara-A), ibrutinib, and bendamustine. In a CLL xenograft model, PF-06747143 decreased tumor burden and improved survival as a monotherapy, and in combination with bendamustine. Conclusions We show evidence that PF-06747143 has biological activity in CLL primary cells, supporting a rationale for evaluation of PF-06747143 for the treatment of CLL patients.