Habitat selection and foraging site fidelity in Caspian Terns (Hydroprogne caspia) breeding in the Baltic Sea

Habitat preferences and foraging strategies affect population-level space use and are therefore crucial to understanding population change and implementing spatial conservation and management actions. We investigated the breeding season habitat preference and foraging site fidelity of the under-studied and threatened, Baltic Sea population of Caspian Terns (Hydroprogne caspia). Using GPS devices, we tracked 20 adult individuals at two breeding colonies, in Sweden and Finland, from late incubation through chick-rearing. Analyzing foraging movements during this period, we describe trip characteristics for each colony, daily metrics of effort, habitat use, and foraging site fidelity. We found that daily time spent away from the colony increased throughout the season, with colony-level differences in terms of distance travelled per day. In general, terns selected shallow waters between 0–5 meters in depth with certain individuals using inland lakes for foraging. We show, for the first time, that individual Caspian Terns are faithful to foraging sites throughout the breeding season, and that individuals are highly repeatable in their strategies regarding foraging site fidelity. These results fill important knowledge gaps for this at-risk population, and extend our general knowledge of the breeding season foraging ecology of this widespread species.

Interannual temperature variability is a principal driver of low-frequency fluctuations in marine fish populations

Marine fish populations commonly exhibit low-frequency fluctuations in biomass that can cause catch volatility and thus endanger the food and economic security of dependent coastal societies. Such variability has been linked to fishing intensity, demographic processes and environmental variability, but our understanding of the underlying drivers remains poor for most fish stocks. Our study departs from previous findings showing that sea surface temperature (SST) is a significant driver of fish somatic growth variability and that life-history characteristics mediate population-level responses to environmental variability. We use autoregressive models to simulate how fish populations integrate SST variability over multiple years depending on fish life span and trophic position. We find that simulated SST-driven population dynamics can explain a significant portion of observed low-frequency variability in independent observations of fisheries landings around the globe. Predictive skill, however, decreases with increasing fishing pressure, likely due to demographic truncation. Using our modelling approach, we also show that increases in the mean and variance of SST could amplify biomass volatility and lessen its predictability in the future. Overall, biological integration of high-frequency SST variability represents a null hypothesis with which to explore the drivers of low-frequency population change across upper-trophic marine species.

The Cost-Effectiveness of Supplemental Carnosine in Type 2 Diabetes

In this paper, we assess the cost-effectiveness of 1 g daily of carnosine (an over the counter supplement) in addition to standard care for the management of type 2 diabetes and compare it to standard care alone. Dynamic multistate life table models were constructed in order to estimate both clinical outcomes and costs of Australians aged 18 years and above with and without type 2 diabetes over a ten-year period, 2020 to 2029. The dynamic nature of the model allowed for population change over time (migration and deaths) and accounted for the development of new cases of diabetes. The three health states were ‘Alive without type 2 diabetes’, ‘Alive with type 2 diabetes’ and ‘Dead’. Transition probabilities, costs, and utilities were obtained from published sources. The main outcome of interest was the incremental cost-effectiveness ratio (ICER) in terms of cost per year of life saved (YoLS) and cost per quality-adjusted life year (QALY) gained. Over the ten-year period, the addition of carnosine to standard care treatment resulted in ICERs (discounted) of AUD 34,836 per YoLS and AUD 43,270 per QALY gained. Assuming the commonly accepted willingness to pay threshold of AUD 50,000 per QALY gained, supplemental dietary carnosine may be a cost-effective treatment option for people with type 2 diabetes in Australia.

Failure to account for behavioral variability overestimates bonobo populations and compromises accuracy in population monitoring

Wildlife population monitoring depends on accurate counts of individual animals or artefacts of behavior (e.g., nests or dung), but also must account for potential biases in the likelihood to encounter these animals or artefacts. In indirect surveying, which depends largely upon artefacts of behavior, likelihood to encounter indirect signs of a species is derived from both artefact production and decay. Although environmental context as well as behavior contribute to artefact abundance, variability in behaviors relevant to artefact abundance is rarely considered in population estimation. Here we demonstrate how ignoring behavioral variability contributes to overestimation of population size of a highly endangered great ape endemic only to the Democratic Republic of the Congo, the bonobo (Pan paniscus). Variability in decay of signs of bonobo presence (i.e., nests) is well documented and linked to environmental determinants. Conversely, a single metric of sign production (i.e., nest construction) is commonly used to estimate bonobo density, assumed to be representative of bonobo nest behavior across all contexts. We estimated nest construction rates from three bonobo groups within the Kokolopori Bonobo Reserve and found that nest construction rates in bonobos to be highly variable across populations as well as seasonal within populations. Failure to account for behavioral variability in nest construction leads to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and in the worst cases as high as 80% overestimation. Using bonobo nesting as an example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises our ability to monitor population change or reliably compare contributors to population decline or persistence. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability across time, space, individuals, and populations can play upon precision and accuracy of wildlife population estimation.

Assessment оf the Economic Potential of Change in the Population of Modern Ukraine

The influence of the macroeconomic factor on the long-term trends of reproduction the population of Ukraine since independence is considered. Based on the author’s concept of “demoeconomic niche” the results of calculation of two options for estimating the “current” (per year) economic potential of population changes in Ukraine on the criteria of conditionally autonomous consumption of population and the actual subsistence level (including necessary payments) were analyzed. The potential for population decline according to the first criterion is considered as a pessimistic (maximum) estimate (–30 million in 2019), according to the second - as an optimistic estimate (–2 million in 2019). The aim of the study was to perform a statistical analysis of the relationship between demographic and economic indicators of population reproduction in Ukraine and their relationship with certain options for assessing the economic potential of population change to determine their greater or lesser relevance to demographic and economic realities. Novelty: the assessment of the economic potential of population change is performed within the economic and demographic methodology developed and maintained by the author (based on the macroeconomic concept of “demoeconomic niche”). Research methods: to study the statistical relationship between indicators used methods of correlation and regression analysis (linear models), as well as a comparative analysis of the results of calculations with the actual dynamics of demographic and economic indicators. Calculations were made by means of PPP STATISTICA 8.0. A statistical analysis of the relationship between demographic and economic indicators and their relationship with the studied options for assessing the economic potential of Ukraine population change was performed to determine compliance with demographic and economic realities. All-time series of indicators (30 and 22 years) subjected to statistical analysis are translated into a single form of annual increments to ensure comparability, as a percentage of the value of the initial year of analysis. The direct linear relationship of GDP changes with the dynamics of the total fertility rate and average life expectancy at birth was recorded, and close feedback - with the dynamics of the migration balance. It is noticed that changes in GDP and the total fertility rate for the whole and rural population have cophase quasi cyclic fluctuations with a 3-4 year lag of reaction delay. It is shown that the assessment of the economic potential of population change by the criterion of conditionally autonomous consumption of population is closely statistically dependent on macroeconomic indicators and economic dynamics. The assessment based on the criterion of the actual subsistence level (including necessary payments) depends more closely on the indicators that directly reflect the well-being of households. It turned out that the adequacy of the assessment based on the criterion of conditionally autonomous consumption of population gradually decreases over time due to the peculiarities of the calculation algorithm, growing inaccuracy can only be neglected at intervals of +/-5 years from the base year. The adequacy of the assessment according to the criterion of the actual subsistence level (including necessary payments) depends on the correspondence to the real cost of life values for each year of the observation period, these values need to be clarified.

Ecological value of different vegetated strip types in providing valuable insect-rich habitats for grey partridge chicks

The intensification and specialisation of agriculture has contributed to farmland wildlife decline, including farmland birds. Grey partridge is a farmland species which has experienced a significant decline across Europe in recent decades. Chick survival rate is a key determinant of grey partridge population change and depends essentially on the availability of insect food. In this study, ground-dwelling and canopy-dwelling insects were collected using pitfall trapping and sweep netting methodologies, respectively, on different strip types in an area established for the conservation of grey partridge. The aim was to further our understanding of the value of different vegetated strip types in providing insect-rich habitats for grey partridge chicks. Overall, wildflower strip (WS) provided the greatest insect abundance. Significantly more ground-dwelling insects were found on WS, natural regeneration (NS) and leguminous strips (LS) than on grass strip (GS). Canopy-dwelling insects were also significantly more abundant on WS compared to all other strip types. This study highlights that WSs may represent important habitats in providing insect-rich food for grey partridge chicks and sowing these strips may therefore play a key role in decreasing chick mortality and supporting grey partridge conservation. It also demonstrates that other different vegetated strip types may still provide strip-specific insect taxa, in addition to other valuable resources. This study recommends a complex mosaic of different strip types to provide key resources for grey partridge, such as insect and plant food, nesting habitats and overwinter cover.

Identifying mechanisms of population change in two threatened grizzly bear populations

<p>Identifying the mechanisms causing population change is essential for conserving small and declining populations. Substantial range contraction of many carnivore species has resulted in fragmented global populations with numerous small isolates in need of conservation. Here I investigate the rate and possible agents of change in two threatened grizzly bear (Ursus arctos) populations in southwestern British Columbia, Canada. I use a combination of population vital rates estimates, population trends, habitat quality analyses, and comparisons to what has been described in the literature, to carefully compare among possible mechanisms of change. First, I estimate population density, realized growth rates (λ), and the demographic components of population change for each population using DNA based capture-recapture data in both spatially explicit capture-recapture (SECR) and non-spatial Pradel robust design frameworks. The larger population had 21.5 bears/1000km2 and between 2006 and 2016 was growing (λPradel = 1.02 ± 0.02 SE, λsecr = 1.01 ± 4.6 x10-5 SE) following the cessation of hunting. The adjacent but smaller population had 6.3 bears/1000km2 and between 2005 and 2017 was likely declining (λPradel = 0.95 ± 0.03 SE, λsecr = 0.98 ± 0.02 SE). Estimates of apparent survival and recruitment indicated that lower recruitment was the dominant factor limiting population growth in the smaller population. Then I use data from GPS-collared bears to estimate reproduction, survival and projected population change (λ) in both populations. Adult female survival was 0.96 (95% CI: 0.80-0.99) in the larger population (McGillvary Mountains or MM) and 0.87 (95% CI: 0.69-0.95) in the small, isolated population (North Stein-Nahatlatch or NSN). Cub survival was also higher in the MM (0.85, 95%CI: 0.62-0.95) than the NSN population (0.33, 95%CI: 0.11-0.67). This analysis identifies both low adult female survival and low cub survival as the demographic factors associated with population decline in the smaller population. By comparing the vital rates from these two populations with other small populations, I suggest that when grizzly bear populations are isolated, there appears to be a tipping point (de Silva and Leimgruber 2019) around 50 individuals, below which adult female mortality, even with intensive management, becomes prohibitive for population recovery. This analysis provides the first detailed estimates of population vital rates for a grizzly bear population of this size, and this information has been important for subsequent management action. To determine whether bottom-up factors (i.e. food) are limiting population growth and recovery in the small isolated population I use resource selection analysis from GPS collar data. I develop resource selection functions (RSF) for four dominant foraging seasons: the spring-early summer season when bears feed predominantly on herbaceous plants and dig for bulbs, the early fruit season where they feed on low elevation berries and cherries, the huckleberry season and the post berry season when foraging behaviours are most diverse but whitebark pine nuts are a relatively common food source. The differences in overall availability of high-quality habitats for different food types, especially huckleberries, between populations suggests that season specific bottom-up effects may account for some differences in population densities. Resource selections are a very common tool used for estimating resource distribution and availability, however, their ability to estimate food abundance on the ground are usually not tested. I assessed the accuracy of the resulting RSF models for predicting huckleberry presence and abundance measured in field plots. My results show that berry specific models did predict berry abundance in previously disturbed sites though varied in accuracy depending on how the models were categorized and projected across the landscape. Finally, I combine spatially explicit capture-recapture methods and models developed from resource selection modelling to estimate the effect of seasonal habitat availability and open road density, as a surrogate for top-down effects, on the bear density in the two populations. I found that population density is most strongly connected to habitats selected during a season when bears fed on huckleberries, the major high-energy food bears eat during hyperphagia in this area, as well as a large baseline difference between populations. The abundance of high-quality huckleberry habitat appears to be an important factor enabling the recovery of the larger population that is also genetically connected to other bears. The adjacent, smaller and genetically isolated population is not growing. The relatively low abundance of high-quality berry habitat in this population may be contributing to the lack of growth of the population. However, it is likely that the legacy of historic mortality and current stochastic effects, inbreeding effects, or other Allee effects, are also contributing to the continued low density observed. While these small population effects may be more challenging to overcome, this analysis suggests that the landscape can accommodate a higher population density than that currently observed.</p>

Identifying mechanisms of population change in two threatened grizzly bear populations

<p>Identifying the mechanisms causing population change is essential for conserving small and declining populations. Substantial range contraction of many carnivore species has resulted in fragmented global populations with numerous small isolates in need of conservation. Here I investigate the rate and possible agents of change in two threatened grizzly bear (Ursus arctos) populations in southwestern British Columbia, Canada. I use a combination of population vital rates estimates, population trends, habitat quality analyses, and comparisons to what has been described in the literature, to carefully compare among possible mechanisms of change. First, I estimate population density, realized growth rates (λ), and the demographic components of population change for each population using DNA based capture-recapture data in both spatially explicit capture-recapture (SECR) and non-spatial Pradel robust design frameworks. The larger population had 21.5 bears/1000km2 and between 2006 and 2016 was growing (λPradel = 1.02 ± 0.02 SE, λsecr = 1.01 ± 4.6 x10-5 SE) following the cessation of hunting. The adjacent but smaller population had 6.3 bears/1000km2 and between 2005 and 2017 was likely declining (λPradel = 0.95 ± 0.03 SE, λsecr = 0.98 ± 0.02 SE). Estimates of apparent survival and recruitment indicated that lower recruitment was the dominant factor limiting population growth in the smaller population. Then I use data from GPS-collared bears to estimate reproduction, survival and projected population change (λ) in both populations. Adult female survival was 0.96 (95% CI: 0.80-0.99) in the larger population (McGillvary Mountains or MM) and 0.87 (95% CI: 0.69-0.95) in the small, isolated population (North Stein-Nahatlatch or NSN). Cub survival was also higher in the MM (0.85, 95%CI: 0.62-0.95) than the NSN population (0.33, 95%CI: 0.11-0.67). This analysis identifies both low adult female survival and low cub survival as the demographic factors associated with population decline in the smaller population. By comparing the vital rates from these two populations with other small populations, I suggest that when grizzly bear populations are isolated, there appears to be a tipping point (de Silva and Leimgruber 2019) around 50 individuals, below which adult female mortality, even with intensive management, becomes prohibitive for population recovery. This analysis provides the first detailed estimates of population vital rates for a grizzly bear population of this size, and this information has been important for subsequent management action. To determine whether bottom-up factors (i.e. food) are limiting population growth and recovery in the small isolated population I use resource selection analysis from GPS collar data. I develop resource selection functions (RSF) for four dominant foraging seasons: the spring-early summer season when bears feed predominantly on herbaceous plants and dig for bulbs, the early fruit season where they feed on low elevation berries and cherries, the huckleberry season and the post berry season when foraging behaviours are most diverse but whitebark pine nuts are a relatively common food source. The differences in overall availability of high-quality habitats for different food types, especially huckleberries, between populations suggests that season specific bottom-up effects may account for some differences in population densities. Resource selections are a very common tool used for estimating resource distribution and availability, however, their ability to estimate food abundance on the ground are usually not tested. I assessed the accuracy of the resulting RSF models for predicting huckleberry presence and abundance measured in field plots. My results show that berry specific models did predict berry abundance in previously disturbed sites though varied in accuracy depending on how the models were categorized and projected across the landscape. Finally, I combine spatially explicit capture-recapture methods and models developed from resource selection modelling to estimate the effect of seasonal habitat availability and open road density, as a surrogate for top-down effects, on the bear density in the two populations. I found that population density is most strongly connected to habitats selected during a season when bears fed on huckleberries, the major high-energy food bears eat during hyperphagia in this area, as well as a large baseline difference between populations. The abundance of high-quality huckleberry habitat appears to be an important factor enabling the recovery of the larger population that is also genetically connected to other bears. The adjacent, smaller and genetically isolated population is not growing. The relatively low abundance of high-quality berry habitat in this population may be contributing to the lack of growth of the population. However, it is likely that the legacy of historic mortality and current stochastic effects, inbreeding effects, or other Allee effects, are also contributing to the continued low density observed. While these small population effects may be more challenging to overcome, this analysis suggests that the landscape can accommodate a higher population density than that currently observed.</p>

Which Residential Clusters of Walkability Affect Future Population from the Perspective of Real Estate Prices in the Osaka Metropolitan Area?

In Japan, where the population is declining and aging significantly, walkability has attracted attention as a way to improve residents’ lifestyles. Therefore, it is essential to identify the residential clusters where walkability improvement would contribute to the maintenance of the population in order to select urban areas for the implementation of walkable designs. This study aimed to identify the residential clusters in which walkability affects the future population from the perspective of real estate prices. The reason for focusing on real estate prices is that they are expected to be a confounding factor connecting walkability and the future population. The method we used was to analyze the structural equation modeling of the impact of walkability index, real estate prices, and future population change ratio. This analysis was based on the neighborhood association scale. This study clarified that effective residential clusters are the business center cluster and the sprawl cluster. In the business center cluster and the sprawl cluster, the price of apartments for sale is the real estate value, through which the walkability index positively impacts the future population change ratio. This means that it is expected to contribute to the maintenance of the future population through a combination of walkable designs and housing policies that encourage people to change their residence types to apartments for sale when rebuilding old building stock using the location optimization plan policy.