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Introduction: In production forests, management can have cascading effects on biodiversity and ecosystem services. Acoustic diversity reflects the diversity of vocalizing animals and has also considerable recreational value for human well-being, but the relationship between acoustic diversity and forest management remains largely unexplored Method: We recorded acoustic diversity on forest plots along a gradient of silvicultural management intensity (SMI) in three regions of Germany. We explored the diurnal and seasonal temporal dynamics in acoustic diversity index (ADI) from March to July using generalized additive mixed models (GAMMs). We further investigated the interrelation between acoustic diversity and silvicultural management intensity, forest structural diversity, as well as tree diversity, bird species richness and abundance using structural equation modeling (SEM). Results: Silvicultural management intensity had significant effects on the temporal dynamics of ADI in May and June from dawn till dusk, but variance explained by SMI was low. We confirmed our hypothesis that ADI was reduced by SMI due to its cascading effects on forest structural diversity and bird species richness and abundance. Discussion: Acoustic diversity indices can provide valuable insights into how forest management affects the acoustic activity of soniferous communities. We discuss how this can indicate both changes in species diversity as well as their vocal activity. We further address potential implications for forest management. [ABSTRACT FROM AUTHOR]

Context. The North American beaver (Castor canadensis) was extirpated from much of its range in the US in the 1800s due to fur trapping and change in land use. However, the species has recolonised much of its former range, including the US state of Ohio. Since 2013, the Ohio Division of Wildlife (ODOW) has monitored trends in beaver colony density via aerial surveys of 40 km × 40 km plots classified as low, medium, or high suitability based on the amount of wetland. Nonetheless, the current classification system may miss important correlates of beaver colony density. Aims. Our study aimed to (1) identify predictors of beaver colony density (number of colonies inferred from aerial counts of lodges) across Ohio, and (2) develop a model-based classification system to improve the efficacy of monitoring efforts. Methods. To predict beaver colony density in Ohio we used an aerial survey dataset of 54 plots (40 km × 40 km) collected by ODOW annually between 2013 and 2020, along with a suite of environmental, anthropogenic, and climate variables in a mixed effects modelling framework. Key results. Beaver colony density was positively associated with wetland and reclaimed surface mine areas and inversely associated with the proportion of agricultural lands. There was a negative interaction between wetland and surface mines; in general, beaver colony density increased with wetland and surface mine area. However, in plots with wetland area >1000 ha, beaver colony density was weakly negatively associated with surface mine area. Using median and interquartile ranges of model-averaged predicted beaver colony density, we developed a new classification of low, moderate and high suitability for both the survey plots and the entire state of Ohio. We found that eastern Ohio had high suitability, while the central and western parts of the state had lower suitability for C. canadensis. Conclusions. Our approach to identifying predictors for beaver colony density at broad spatial scales highlights the importance of reclaimed surface mines and wetlands for beaver populations, while the model-based habitat classification provides ODOW additional information for monitoring and beaver management decisions. Implications. Improved C. canadensis monitoring at the landscape scale using habitat classifications that consider local conditions can both improve annual survey cost-effectiveness and facilitate the sustainable management of this recovering species. [ABSTRACT FROM AUTHOR]

The recovery of mammalian species in the US Midwest through natural recolonization constitutes a conservation success story, yet management remains challenging due to many unknowns related to population dynamics and numeric trends. Abundance is a critical parameter for management decisions, and estimating the density and abundance of elusive species, such as terrestrial carnivores, remains challenging despite recent technological advances. In this study, we evaluated density and abundance of a recovering carnivore species, the bobcat (Lynx rufus) in two areas of Ohio using non‐invasive DNA from scat. The target areas in eastern and southern Ohio have been shown to have uneven dynamics and recolonization success and we expected that this would be reflected in differences in density and abundance. We collected 298 bobcat scats between July 2018 and April 2019 on 150 km of repeated transects. Of these, 102 scats were successfully genotyped, and 55 individuals were identified (33 in eastern Ohio and 22 in southern Ohio). Using Spatially Explicit Capture–Recapture models, we estimated 18.9 ± 4.1 and 10.9 ± 2.7 bobcats/100 km2 in eastern and southern Ohio study areas, respectively. Our results support prior telemetry data which indicated that bobcats in eastern Ohio had smaller home‐ranges than bobcats in southern Ohio, and thus could support a higher density of individuals. The higher densities were similar to other eastern US populations and are much higher than other Midwestern recovering populations. Our results provide a snapshot of the population status and can be used to determine sustainable management strategies for Ohio's bobcat population. [ABSTRACT FROM AUTHOR]

Establishing protected areas (PAs) is a major measure of biodiversity conservation, and various methods have been explored to assess PAs' effectiveness. However, those methods mainly compared the relative changes in land cover between treated samples inside the PAs and their matched samples outside the PAs, which would produce misjudgments, especially in some climax communities with a relatively steady state. Thus, in this study, we constructed an integrated framework through a series of assessments according to the state, trend, and relative change of each PA to explore the conservation effectiveness of PAs in the Three Parallel Rivers Region in China from 2000 to 2020. Here, "state" refers to the difference among samples from within and outside the PA, assessed through yearly sample mean comparison. "Trend" means linear regression of mean forest area of each PA throughout the assessment period. "Relative change" means the difference in the mean value of the slope of forest changes between the treated samples inside each PA and their matched control samples outside of PAs. The entire forest area within all PAs in the Three Parallel Rivers Region showed a significant increasing trend from 2000 to 2020 (R2 = 0.919, P<0.05). Among all the PAs, twelve (86%) had a positive effect on protecting the forest ecosystem, and two had a nonsignificant effect. Among the factors affecting the state and relative change in PAs' forests, the annual total precipitation was the most important, followed by distance to the nearest road. Moreover, the management-level variable was an essential factor in the state of PAs' forest ecosystems, which indicated that national PAs (nature reserves and natural parks) were in a better state than local (provincial-and county-level) nature reserves. Overall, the conservation effectiveness of forests in PAs was assessed at a regional scale in the Three Parallel Rivers Region, implying that our framework would be additional useful in regions with high biodiversity and steady ecosystems. This framework better avoids underestimating conservation effectiveness assessment tasks than traditional methods do. Thus, we posit that this framework is suitable for future global or country-level assessments. [ABSTRACT FROM AUTHOR]

Wildlife data gathered by different monitoring techniques are often combined to estimate animal density. However, methods to check whether different types of data provide consistent information (i.e., can information from one data type be used to predict responses in the other?) before combining them are lacking. We used generalized linear models and generalized linear mixed-effects models to relate camera trap probabilities for marked animals to independent space use from telemetry relocations using 2 years of data for fishers (Pekania pennanti) as a case study. We evaluated (1) camera trap efficacy by estimating how camera detection probabilities are related to nearby telemetry relocations and (2) whether home range utilization density estimated from telemetry data adequately predicts camera detection probabilities, which would indicate consistency of the two data types. The number of telemetry relocations within 250 and 500 m from camera traps predicted detection probability well. For the same number of relocations, females were more likely to be detected during the first year. During the second year, all fishers were more likely to be detected during the fall/winter season. Models predicting camera detection probability and photo counts solely from telemetry utilization density had the best or nearly best Akaike Information Criterion (AIC), suggesting that telemetry and camera traps provide consistent information on space use. Given the same utilization density, males were more likely to be photo-captured due to larger home ranges and higher movement rates. Although methods that combine data types (spatially explicit capture-recapture) make simple assumptions about home range shapes, it is reasonable to conclude that in our case, camera trap data do reflect space use in a manner consistent with telemetry data. However, differences between the 2 years of data suggest that camera efficacy is not fully consistent across ecological conditions and make the case for integrating other sources of space-use data.

Freshwater biodiversity is declining at a fast pace despite significant efforts directed toward the management and conservation of aquatic systems. Eastern hellbenders are one of North America's most iconic stream amphibian species, a sentinel of stream health, and are experiencing rapid population declines throughout most of their range. Common conservation strategies include headstarting; however, the success of this strategy for rebuilding hellbender populations and the most optimal release scenarios have largely been unassessed. We use a cohort of 205 animals released in several Ohio watersheds to evaluate the success of headstarting and reintroduction efforts over 3 years. Using PIT‐tag surveys over 25 occasions between July 2018 and November 2021 and capture–recapture models, we found that 3‐year apparent survival post‐release was 0.162 ± 0.061, with lower survival in year 1 (0.383 ± 0.058) and greater in years 2 (0.696 ± 0.086) and 3 (0.609 ± 0.154). Using demographic simulations, we found that releasing cohorts of N = 100 individuals at fewer suitable sites several times (e.g., 3 releases, 2 or 3 years apart) would be a better strategy compared to single release events across multiple sites. Additional simulations showed that eastern hellbender headstarting programs using wild eggs can be highly beneficial in producing more animals reaching adulthood (up to 7 times, if survival in captivity is assumed to be 100%) compared to development in the wild. This study emphasizes the need to monitor the success of reintroduction programs and provides evidence that headstarting can be a viable strategy for rebuilding eastern hellbender populations. [ABSTRACT FROM AUTHOR]

Chelydra serpentina, a species introduced to China for aquaculture purposes, is commonly found in its natural habitats within the country. The invasion of C. serpentina poses potential threats to both the biodiversity of China and human health. The potential distribution of C. serpentina has been simulated using the species distribution model - MaxEnt, incorporating global distribution data, climate, and land cover variables. Our simulations encompasses both current conditions and four future climate change scenarios. Currently, the potential distribution is concentrated in central, eastern, and southeastern regions of China, with the central and eastern regions facing the highest risk of invasion. Under future climate change scenarios, the distribution area may expand by 30-90%, and multiple provinces will face a more severe threat of invasion. This study presents the inaugural simulation of the potential invasion range of C. serpentina under current climatic conditions. Moreover, it reveals that climate change is likely to contribute to the expansion of its invasive range, thus furnishing a reference foundation for scientific prevention and control measures. We propose integrating citizen science and eDNA technologies into species monitoring to enhance the efficiency of detecting invasive species. This research has filled the gap in the research on the invasive distribution range of C. serpentina in China and globally, while also providing novel perspectives on the invasion control of this species. [ABSTRACT FROM AUTHOR]

Bobcats (Lynx rufus) were extirpated from many midwestern states in the mid‐1800s owing to habitat loss and overharvesting. Recently, bobcats have recolonized Ohio, USA, and neighboring states and given their furbearer status elsewhere, there is interest in opening a harvest season; however, demographic factors and viability of this population are currently unknown. We developed a spatial population simulation model to assess the long‐term viability of the bobcat population in Ohio in the face of 2 human‐induced factors limiting population growth: potential harvest and road mortality. We combined habitat suitability and road mortality risk data with vital rates for bobcats from Ohio and other populations to simulate possible scenarios for Ohio's population. Our baseline scenario simulations showed no risk of extinction for Ohio's bobcat population in the next 40 years, but population trajectories were lower and exhibited greater uncertainty when we modeled the population with a lower maximum density of animals per cell. At low harvest intensity (αh = 0.05), the bobcat population also exhibits low risk of extinction. When harvest intensity increases (αh = 0.1, 0.15) or when adults (≥2 yr) are targeted by harvest, simulations show declining populations, greater uncertainty in projections, and possible risk of extirpation. Our models indicated that if harvest and road mortality are additive, then the bobcat population could withstand marginal increases in road mortality (αr = 0.1) at low harvest intensity (αh = 0.05). Future increases in road mortality with higher harvest intensity (αh = 0.1, 0.15) were unsustainable. Our results can be used by wildlife managers to assist with decisions on population‐level management. This simulation model can easily be adapted for other large mammals and can be modified to assess a variety of ecological and anthropogenic influences to wildlife populations. [ABSTRACT FROM AUTHOR]

The paper describes blended learningapproach to teaching resistor measurement. It is basedon “Learning by Doing” paradigm: interacticesimulation, laboratory plants, real experimentsaccessed by Web Publishing Tools under LabVIEW.Studying and experimenting access is opened for 24hours a day, 7 days a week under Moodle bookingsystem.

The goal of this work is to study theperformances of a hybrid controller used to controlDC Motor drive with a single-phase power factorcorrection rectifier. This study is made usingcomputer simulation (Simulink). The first part isdevoted to the control system of the DC Motors. Inthe second part, the design of the hybrid controllerwill be presented. The third part is the design ofthe fast response single-phase boost power factorcorrection rectifier. The last parts are devoted tosimulation and experimental results.