Using density surface models to estimate spatio-temporal changes in population densities and trend

Precise measures of population abundance and trend are needed for species conservation; these are most difficult to obtain for rare and rapidly changing populations. We compare uncertainty in densities estimated from spatio–temporal models with that from standard design-based methods. Spatio–temporal models allow us to target priority areas where, and at times when, a population may most benefit. Generalised additive models were fitted to a 31-year time series of point-transect surveys of an endangered Hawaiian forest bird, the Hawai‘i ‘ākepa Loxops coccineus. This allowed us to estimate bird densities over space and time. We used two methods to quantify uncertainty in density estimates from the spatio–temporal model: the delta method (which assumes independence between detection and distribution parameters) and a variance propagation method. With the delta method we observed a 52% decrease in the width of the design-based 95% confidence interval (CI), while we observed a 37% decrease in CI width when propagating the variance. We mapped bird densities as they changed across space and time, allowing managers to evaluate management actions. Integrating detection function modelling with spatio–temporal modelling exploits survey data more efficiently by producing finer-grained abundance estimates than are possible with design-based methods as well as producing more precise abundance estimates. Model-based approaches require switching from making assumptions about the survey design to assumptions about bird distribution. Such a switch warrants consideration. In this case the model-based approach benefits conservation planning through improved management efficiency and reduced costs by taking into account both spatial shifts and temporal changes in population abundance and distribution.     

Modeling Cumulative Effects of Climate and Development on Moose,Wolf, and Caribou Populations

Wildlife models focused solely on a single strong influence (e.g., habitat components, wildlife harvest) are limited in their ability to detect key mechanisms influencing population change. Instead, we propose integrated modeling in the context of cumulative effects assessment using multispecies population dynamics models linked to landscape-climate simulation at large spatial and temporal scales. We developed an integrated landscape and population simulation model using ALCES Online as the model-building platform, and the model accounted for key ecological components and relationships among moose (Alces alces), grey wolves (Canis lupus nubilus), and woodland caribou (Rangifer tarandus caribou) in northern Ontario, Canada. We simulated multiple scenarios over 5 decades (beginning 2020) to explore sensitivity to climate change and land use and assessed effects at multiple scales. The magnitude of effect and the relative importance of key factors (climate change, roads, and habitat) differed depending on the scale of assessment. Across the full extent of the study area (654,311km² [ecozonal scale]), the caribou population declined by 26% largely because of climate change and associated predator-prey response, which led to caribou range recession in the southern part of the study area. At the caribou range scale (108,378 km²), which focused on 2 herds in the northern part of the study area, climate change led to a 10% decline in the population and development led to an additional 7% decline. At the project scale (8,331 km²), which was focused more narrowly on the landscape surrounding 4 proposed mines, the caribou population declined by 29% largely in response to simulated development. Given that observed caribou population dynamics were sensitive to the cumulative effects of climate change, land use, interspecific interactions, and scale, insights from the analysis might not emerge under a less complex model. Our integrated modeling framework provides valuable support for broader regional assessments, including estimation of risk to caribou and Indigenous food security, and for developing and evaluating potential caribou recovery strategies. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.     

Cushioned versus noncushioned centrifugation: Sperm recovery rate and integrity

It was hypothesized that optimal sperm recovery rate (RR) without damage to the sperm would be obtained after centrifugation without a cushion solution. Semen collected three times from six light breed stallions was extended to 25 × 10⁶ sperm/mL and centrifuged at CON (noncentrifuged), 900NC (no-cushion), 900C (cushion), 1800NC, and 1800C × g for 10 minutes. Sperm concentration, motility (TM and PM), and intact plasma membranes (PLM) and acrosomes (ACR) pre- and postcentrifugation (D0) and after 24 hours (D1) of cooling were evaluated. The RR in the CON (100 ± 0.0), 900NC (93.7 ± 2.9), and 1800NC (96.7 ± 2.6) groups was significantly higher than the 900C (68.7 ± 4.6) and 1800C (79.6 ± 3.5) groups. The D0 TM and PM were not different between the CON, 900NC, 900C, and 1800C, but were lower for the 1800NC group. The D1 TM and PM of the 900NC (75.2 ± 3.8 and 71.1 ± 4.1) and 900C (76.2 ± 3.7 and 72.4 ± 4.0) groups were significantly higher than the 1800NC (71.7 ± 4.1 and 67.3 ± 4.4) and 1800C (71.6 ± 4.1 and 67.2 ± 4.4) groups, and the CON (66.2 ± 4.5 and 60.0 ± 4.8) group was significantly lower than the other groups. The D1 PLM of the CON, 900NC, 900C, 1800NC, and 1800C groups were not different. The ACR on D1 was significantly lower for the CON (93.0 ± 2.4) group compared with all other groups. Optimal RR preserving sperm integrity was obtained in the 900NC group.     

Monitoring population‐level responses of marine mammals to human activities

We provide guidance for monitoring whether human activities affect the physiology or behavior of marine mammals and, if so, whether those effects may lead to changes in survival and reproduction at the population level. We suggest that four elements be included in designing and implementing such a monitoring program. The first is development of a theory of change: a set of mechanistic hypotheses that outline why a given activity might be expected to have one or more measurable effects on individuals and populations, and ideally the magnitude, timing, and duration of the effects. The second element, definition of biologically meaningful effect sizes, ultimately facilitates the development of a monitoring program that can detect those magnitudes of effect with the desired levels of precision. The third element, selection of response variables for monitoring, allows inference to whether observed changes in the status of individuals or populations are attributable to a given activity. Visual observations, passive acoustic and tagging instruments, and direct physical measurements all can provide data that facilitate quantitative hypothesis testing. The fourth element is specification of the temporal sequence of monitoring. These elements also can be used to inform monitoring of the responses of other taxonomic groups to human activities.     

Proteome map of normal rat retina and comparison with the proteome of diabetic rat retina: new insight in the pathogenesis of diabetic retinopathy

We have employed proteomics to establish a proteome map of the normal rat retina. This baseline map was then used for comparison with the early diabetic rat retinal proteome. Diabetic rat retinae were obtained from Dark Agouti rats after 10 wk of streptozotocin-induced hyperglycaemia. Extracted proteins from normal and diabetic rat retinae were separated and compared using 2-DE. A total of 145 protein spots were identified in the normal rat retina using MALDI-MS and database matching. LC-coupled ESI-MS increased the repertoire of identified proteins by 23 from 145 to 168. Comparison with early diabetic rat retinae revealed 24 proteins unique to the diabetic gels, and 37 proteins absent from diabetic gels. Uniquely expressed proteins identified included the HSPs 70.1A and 8, and platelet activating factor. There were eight spots with increased expression and 27 with decreased expression on diabetic gels. Beta catenin, phosducin and aldehyde reductase were increased in expression in diabetes whilst succinyl coA ligase and dihydropyrimidase-related protein were decreased. Identification of such changes in protein expression has given new insights and a more comprehensive understanding of the pathogenesis of diabetic retinopathy, widening the scope of potential avenues for new therapies for this common cause of blindness.