Regional land-use and local management create scale-dependent 'landscapes of fear' for a common woodland bird

Context Land-use change and habitat fragmentation are well known drivers of biodiversity declines. In forest birds, it has been proposed that landscape change can cause increased predation pressure that leads to population declines or community change. Predation can also have non-lethal effects on prey, such as creating ‘landscapes of fear’. However, few studies have simultaneously investigated the relative contribution of regional land-use and local management to creating ‘landscapes of fear’. Objectives To quantify the relative contribution of regional land-use and local management to the ‘landscape of fear’ in agricultural landscapes. Methods Bioacoustic recorders were used to quantify Eurasian Wren Troglodytes troglodytes alarm call rates in 32 naturally replicated broadleaf woodlands located in heterogeneous agricultural landscapes. Results Alarm call rates (the probability of an alarm per 10 min of audio) were positively correlated with the amount of agricultural land (arable or pasture) within 500 m of a woodland (effect size of 1) and were higher when livestock were present inside a woodland (effect size of 0.78). The amount of woodland and urban land cover in the landscape also had positive but weak effects on alarm call rates. Woodlands with gamebird management had fewer alarm calls (effect size of − 0.79). Conclusions We found that measures of both regional land-use and local management contributed to the ‘landscape of fear’ in agricultural landscapes. To reduce the impact of anthropogenic activities on ‘fear’ levels (an otherwise natural ecological process), land-managers should consider limiting livestock presence in woodlands and creating traditional ‘buffer strips’ (small areas of non-farmed land) at the interface between woodland edges and agricultural fields

Ecological time lags and the journey towards conservation success

Global conservation targets to reverse biodiversity declines and halt species extinctions are not being met despite decades of conservation action. However, a lack of measurable change in biodiversity indicators towards these targets is not necessarily a sign that conservation has failed; instead, temporal lags in species’ responses to conservation action could be masking our ability to observe progress towards conservation success. Here we present our perspective on the influence of ecological time lags on the assessment of conservation success and review the principles of time lags and their ecological drivers. We illustrate how a number of conceptual species may respond to change in a theoretical landscape and evaluate how these responses might influence our interpretation of conservation success. We then investigate a time lag in a real biodiversity indicator using empirical data and explore alternative approaches to understand the mechanisms that drive time lags. Our proposal for setting and evaluating conservation targets is to use milestones, or interim targets linked to specific ecological mechanisms at key points in time, to assess whether conservation actions are likely to be working. Accounting for ecological time lags in biodiversity targets and indicators will greatly improve the way that we evaluate conservation successes

Dually investigated: the effect of a pressure headcollar on the behaviour, discomfort and stress of trained horses

The Dually™ is a control headcollar designed to improve equine behaviour during handling challenges by applying greater pressure than a standard headcollar. Previous research indicated it did not improve compliance in naïve horses but did result in higher Horse Grimace Scale scores (HGS) indicative of discomfort. However, subjects had not been trained to step forward to release the pressure applied by the headcollar. The current study aimed to determine the effect of training on behaviour and physiology of horses wearing the Dually™ headcollar during handling challenges. To this end, subjects received three training sessions prior to completing two handling tests in which they crossed distinct novel obstacles, one wearing a Dually™ with a line attached to the pressure mechanism and one attached to the standard ring as a control. Behaviour was coded by hypothesis blind researchers: time to cross the obstacle and proactive refusal (moving away from the obstacle) were recorded as indicators of compliance and the Horse Grimace Scale was used to measure discomfort caused by each configuration of the device. Infrared thermography of ocular temperature, heart rate variability (RMSSD and low/high frequency ratios (LF/HF)) and salivary cortisol were measured as indicators of arousal. Data from the previous study on Naïve horses was also included to compare responses to the Dually in Naïve and Trained horses. Training resulted in a decrease in RMSSD (p = 0.002) and an increase in LF/HF (p=0.012), compared to rest, indicating arousal. As per the original study, horses did not complete the tests more quickly in the Dually, compared to control (p=0.698). Trained horses from this study tended to be more proactive in the Dually compared to Controls (p=0.066) and significantly more so than Naïve horses from the previous study (p=0.002) suggesting that behaviour becomes less desirable during early Dually training. Yet, stress and HGS indicators were not higher in the Dually compared to Control during testing. Results suggest the Dually has a negative effect on behaviour but not on stress or discomfort during short handling challenges. Further research is warranted to determine the long-term effect of Dually experience on behaviour and welfare

Achieving international biodiversity targets: learning from local norms, values and actions regarding migratory waterfowl management in Kazakhstan

1. Migratory species are protected under international legislation; their seasonal movements across international borders may therefore present opportunities for understanding how global conservation policies translate to local-level actions across different socio-ecological contexts. Moreover, local-level management of migratory species can reveal how culture and governance affects progress towards achieving global targets. Here, we investigate potential misalignment in the two-way relationship between global-level conservation policies (i.e. hunting bans and quotas) and local-level norms, values and actions (i.e. legal and illegal hunting) in the context of waterfowl hunting in Northern Kazakhstan as a case-study. 2. N Kazakhstan is globally important for waterfowl and a key staging area for arctic-breeding species. Hunting is managed through licences, quotas and seasonal bans under UN-AEWA intergovernmental agreements. To better understand the local socio-ecological context of waterfowl hunting, we take a mixed-methods approach using socio-ecological surveys, informal discussions, and population modelling of a focal migratory goose species to: (1) investigate motivations for hunting in relation to socio-economic factors; (2) assess knowledge of species’ protection status; and (3) predict the population size of Lesser White-fronted Geese (LWfG; Anser erythropus; IUCN Vulnerable) under different scenarios of survival rates and hunting offtake, to understand how goose population demographics interact with the local socio-ecological context. 3. Model results showed no evidence that waterfowl hunting is motivated by financial gain; social and cultural importance were stronger factors. The majority of hunters are knowledgeable about species’ protection status; however, 11% did not know LWfG are protected, highlighting a key area for increased stakeholder engagement. 4. Simulations of LWfG population growth over a 20-year period showed LWfG are highly vulnerable to hunting pressure even when survival rates are high. This potential impact of hunting highlights the need for effective regulation along the entire flyway; our survey results show that hunters were generally compliant with newly introduced hunting regulations, showing that effective regulation is possible on a local level. Synthesis and applications. Here, we investigate how global conservation policy and local norms interact to affect the management of a threatened migratory species, which is particularly important for the protection and sustainable management of wildlife that crosses international borders where local contexts may differ. Our study highlights that to be effective and sustainable in the long-term, global conservation policies must fully integrate local socio-economic, cultural, governance and environmental contexts, to ensure interventions are equitable across entire species’ ranges. This approach is relevant and adaptable for different contexts involving the conservation of wide-ranging and migratory species, including the 255 migratory waterfowl covered by UN-AEWA (United Nations Agreement on the Conservation of African-Eurasian Migratory Waterbirds).Output Status: Forthcoming/Available Onlin

Divergence exists in the subcellular distribution of intramuscular triglyceride in human skeletal muscle dependent on the choice of lipid dye.

Despite over 50 years of research, a comprehensive understanding of how intramuscular triglyceride (IMTG) is stored in skeletal muscle and its contribution as a fuel during exercise is lacking. Immunohistochemical techniques provide information on IMTG content and lipid droplet (LD) morphology on a fibre type and subcellular-specific basis, and the lipid dye Oil Red O (ORO) is commonly used to achieve this. BODIPY 493/503 (BODIPY) is an alternative lipid dye with lower background staining and narrower emission spectra. Here we provide the first quantitative comparison of BODIPY and ORO for investigating exercise-induced changes in IMTG content and LD morphology on a fibre type and subcellular-specific basis. Estimates of IMTG content were greater when using BODIPY, which was predominantly due to BODIPY detecting a larger number of LDs, compared to ORO. The subcellular distribution of intramuscular lipid was also dependent on the lipid dye used; ORO detects a greater proportion of IMTG in the periphery (5 μm below cell membrane) of the fibre, whereas IMTG content was higher in the central region using BODIPY. In response to 60 min moderate-intensity cycling exercise, IMTG content was reduced in both the peripheral (- 24%) and central region (- 29%) of type I fibres (P < 0.05) using BODIPY, whereas using ORO, IMTG content was only reduced in the peripheral region of type I fibres (- 31%; P < 0.05). As well as highlighting some methodological considerations herein, our investigation demonstrates that important differences exist between BODIPY and ORO for detecting and quantifying IMTG on a fibre type and subcellular-specific basis

Real‐time alerts from AI‐enabled camera traps using the Iridium satellite network: A case‐study in Gabon, Central Africa

Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real-time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real-time analysis where there is no reliable cellular or WiFi connectivity. We modified an off-the-shelf camera trap (Bushnell™) and customised existing open-source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end-user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed-canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open-source repositories. Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time-difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5-days or more when the system was incorrectly positioned and unable to connect to the Iridium network. We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real-time use cases including real-time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas

Young, healthy males and females present cardiometabolic protection against the detrimental effects of a 7-day high-fat high-calorie diet

Purpose: High-fat, high-calorie (HFHC) diets have been used as a model to investigate lipid-induced insulin resistance. Short-term HFHC diets reduce insulin sensitivity in young healthy males, but to date, no study has directly compared males and females to elucidate sex-specific differences in the effects of a HFHC diet on functional metabolic and cardiovascular outcomes. Methods: Eleven males (24 ± 4 years; BMI 23 ± 2 kg.m−2; V̇O2 peak 62.3 ± 8.7 ml.min−1.kg−1FFM) were matched to 10 females (25 ± 4 years; BMI 23 ± 2 kg.m−2; V̇O2 peak 58.2 ± 8.2 ml.min−1.kg−1FFM). Insulin sensitivity, measured via oral glucose tolerance test, metabolic flexibility, arterial stiffness, body composition and blood lipids and liver enzymes were measured before and after 7 days of a high-fat (65% energy) high-calorie (+ 50% kcal) diet. Results: The HFHC diet did not change measures of insulin sensitivity, metabolic flexibility or arterial stiffness in either sex. There was a trend towards increased total body fat mass (kg) after the HFHC diet (+ 1.8% and + 2.3% for males and females, respectively; P = 0.056). In contrast to females, males had a significant increase in trunk to leg fat mass ratio (+ 5.1%; P = 0.005). Conclusion: Lean, healthy young males and females appear to be protected from the negative cardio-metabolic effects of a 7-day HFHC diet. Future research should use a prolonged positive energy balance achieved via increased energy intake and reduced energy expenditure to exacerbate negative metabolic and cardiovascular functional outcomes to determine whether sex-specific differences exist under more metabolically challenging conditions

Modeling the potential distribution of the threatened Grey-necked Picathartes Picathartes oreas across its entire range

Understanding the distribution and extent of suitable habitats is critical for the conservation of endangered and endemic taxa. Such knowledge is limited for many Central African species, including the rare and globally threatened Grey-necked Picathartes Picathartes oreas, one of only two species in the family Picathartidae endemic to the forests of Central Africa. Despite growing concerns about land-use change resulting in fragmentation and loss of forest cover in the region, neither the extent of suitable habitat nor the potential species’ distribution is well known. We combine 339 (new and historical) occurrence records of Grey-necked Picathartes with environmental variables to model the potential global distribution. We used a Maximum Entropy modelling approach that accounted for sampling bias. Our model suggests that Grey-necked Picathartes distribution is strongly associated with steeper slopes and high levels of forest cover, while bioclimatic, vegetation health, and habitat condition variables were all excluded from the final model. We predicted 17,327 km2 of suitable habitat for the species, of which only 2,490 km2 (14.4%) are within protected areas where conservation designations are strictly enforced. These findings show a smaller global distribution of predicted suitable habitat forthe Grey-necked Picathartes than previously thought. This work provides evidence to inform a revision of the International Union for Conservation of Nature (IUCN) Red List status, and may warrant upgrading the status of the species from “Near Threatened” to “Vulnerable”

Robust ecological analysis of camera trap data labelled by a machine learning model

1. Ecological data are collected over vast geographic areas using digital sensors such as camera traps and bioacoustic recorders. Camera traps have become the standard method for surveying many terrestrial mammals and birds, but camera trap arrays often generate millions of images that are time‐consuming to label. This causes significant latency between data collection and subsequent inference, which impedes conservation at a time of ecological crisis. Machine learning algorithms have been developed to improve the speed of labelling camera trap data, but it is uncertain how the outputs of these models can be used in ecological analyses without secondary validation by a human. 2. Here, we present our approach to developing, testing and applying a machine learning model to camera trap data for the purpose of achieving fully automated ecological analyses. As a case‐study, we built a model to classify 26 Central African forest mammal and bird species (or groups). The model generalizes to new spatially and temporally independent data (n = 227 camera stations, n = 23,868 images), and outperforms humans in several respects (e.g. detecting ‘invisible’ animals). We demonstrate how ecologists can evaluate a machine learning model's precision and accuracy in an ecological context by comparing species richness, activity patterns (n = 4 species tested) and occupancy (n = 4 species tested) derived from machine learning labels with the same estimates derived from expert labels. 3. Results show that fully automated species labels can be equivalent to expert labels when calculating species richness, activity patterns (n = 4 species tested) and estimating occupancy (n = 3 of 4 species tested) in a large, completely out‐of‐sample test dataset. Simple thresholding using the Softmax values (i.e. excluding ‘uncertain’ labels) improved the model's performance when calculating activity patterns and estimating occupancy but did not improve estimates of species richness. 4. We conclude that, with adequate testing and evaluation in an ecological context, a machine learning model can generate labels for direct use in ecological analyses without the need for manual validation. We provide the user‐community with a multi‐platform, multi‐language graphical user interface that can be used to run our model offline.Additional co-authors: Cisquet Kiebou Opepa, Ross T. Pitman, Hugh S. Robinso