Optimising habitat creation for woodland birds: the relative importance of local vs landscape scales

Global land-use change and industrialisation has driven biodiversity declines and impaired ecosystem functioning. Recently, there have been large-scale efforts to not only halt habitat loss but create and restore habitat on formerly managed (e.g. agricultural) land. However, although the effects of habitat loss and fragmentation on biodiversity are well understood, our understanding of how biodiversity responds to habitat created in a patchy configuration is not. In particular, little is known about the relative importance of local (e.g. patch size) vs landscape scales (e.g. amount of habitat in the landscape) for restoring biodiversity in created habitat. Here, a long-term, large-scale natural experiment (the Woodland Creation and Ecological Networks project) was used to understand how bird species, communities and behaviour respond to woodland created in a patchy configuration on post-agricultural land. I used a combination of direct and indirect survey methods to quantify bird diversity, abundance and vocal behaviour in post-agricultural woodlands of known age in Great Britain. I show that secondary woodlands favour generalist species and older patches contain more individuals and species due to their vegetation structure. In relative terms, local-scale factors such as patch size made the greatest contribution to bird diversity and abundance. Colonisation events drive community assembly in new habitat, and I found that large-scale (km2) habitat patterns were more important than patch-level factors during colonisation of breeding territories by a long distance migrant bird (Willow Warbler Phylloscopus trochilus). Land management practices surrounding a habitat patch can also affect its perceived quality and relative attractiveness to potential colonisers. Using the Eurasian Wren Troglodytes troglodytes as a model species, I found that high proportions of agricultural land at woodland edges caused an increase in perceived predation risk. In conclusion, I suggest that post-agricultural woodlands rapidly provide valuable habitat for generalist woodland birds. Local, patch-level factors (area, vegetation structure) also appear relatively more important than landscape factors for woodland bird communities. Land-managers seeking to maximise the benefits of woodland creation for birds should thus focus on creating large patches with a diverse vegetation structure

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

Mammal distribution and trends in the threatened Ebo 'intact forest landscape', Cameroon

Intact forest landscapes (IFLs) are globally important for maintaining functional ecosystems. Ebo forest (~1400 km2) in Cameroon is one of the largest remaining IFLs in the Cross-Sanaga-Bioko coastal forest ecoregion and harbours several IUCN Red-Listed threatened mammal species. We evaluated the status, trends, and distribution of mammals ≥ 0.5 kg in the Ebo forest over 12 years using guided recce and camera trap monitoring surveys, as well as local knowledge to inform future land use and conservation planning. Recce monitoring of seven taxa (blue duiker Philantomba monticola, chimpanzee Pan troglodytes, forest elephant Loxodonta cyclotis, putty-nosed monkey Cercopithecus nictitans, medium sized duikers Cephalophus spp., and red river hog Potamochoerus porcus) showed that some are stable or increasing. Indeed, our recent camera trap data confirmed breeding Gorilla gorilla (western gorilla) and elephant. Distribution models for chimpanzees and elephants showed that their populations are concentrated in the centre of the forest, away from human pressure. Some other species, however, including red colobus Piliocolobus preussi, leopard Panthera pardus, African golden cat Caracal aurata, and forest buffalo Syncerus caffer nanus are either close to extirpation or have been extirpated within living memory. We conclude that the Ebo intact forest landscape retains an important mammal community, despite no formal legal protection. Ebo’s future is uncertain, with two commercial logging concessions announced by Cameroon in 2020 and later suspended in response to national and international pressure. It is crucial to maintain Ebo’s integrity to maintain the biodiversity and function of this important part of the Cross-Sanaga-Bioko coastal forest ecoregion

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

Tritophic phenological match-mismatch in space and time

Increasing temperatures associated with climate change may generate phenological mismatches that disrupt previously synchronous trophic interactions. Most work on mismatch has focused on temporal trends, whereas spatial variation in the degree of trophic synchrony has largely been neglected, even though the degree to which mismatch varies in space has implications for meso-scale population dynamics and evolution. Here we quantify latitudinal trends in phenological mismatch, using phenological data on an oak–caterpillar–bird system from across the UK. Increasing latitude delays phenology of all species, but more so for oak, resulting in a shorter interval between leaf emergence and peak caterpillar biomass at northern locations. Asynchrony found between peak caterpillar biomass and peak nestling demand of blue tits, great tits and pied flycatchers increases in earlier (warm) springs. There is no evidence of spatial variation in the timing of peak nestling demand relative to peak caterpillar biomass for any species. Phenological mismatch alone is thus unlikely to explain spatial variation in population trends. Given projections of continued spring warming, we predict that temperate forest birds will become increasingly mismatched with peak caterpillar timing. Latitudinal invariance in the direction of mismatch may act as a double-edged sword that presents no opportunities for spatial buffering from the effects of mismatch on population size, but generates spatially consistent directional selection on timing, which could facilitate rapid evolutionary change

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”

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

Long-term collapse in fruit availability threatens Central African forest megafauna

Afrotropical forests host many of the world’s remaining megafauna, but even here they are confined to areas where direct human influences are low. We use a rare long-term dataset of tree reproduction and a photographic database of forest elephants to assess food availability and body condition of an emblematic megafauna species at Lopé National Park, Gabon. We show an 81% decline in fruiting over a 32-year period (1986-2018) and an 11% decline in body condition of fruit-dependent forest elephants from 2008-2018. Fruit famine in one of the last strongholds for African forest elephants should raise concern for the ability of this species and other fruit-dependent megafauna to persist in the long-term, with consequences for broader ecosystem and biosphere functioning

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