Habitat characteristics or protected area size: What is more important for the composition and diversity of mammals in nonprotected areas?

The margins of protected areas are usually considered to have greater forest degradation, and given that most mammals live outside protected areas, researchers and conservation practitioners are increasingly recognizing that nonprotected areas must be incorporated into conservation strategy. However, the strategy used to manage these areas still involves increasing the size of protected areas, while not considering the habitat characteristics and requirements of the species. In this study, during a 3-year period, camera trap and habitat characteristic surveys were used to estimate composition, diversity, and habitat characteristics of mammals to determine habitat characteristics or increase the size of protected areas what should be considered first for mammals’ conservation in a nonprotected area near the Huangshan Mountains in Anhui Province, China. From June 2017 to October 2019, 18 species of mammals were recorded, more than in any other protected area nearby. The linear model analysis results showed that habitat characteristics of mammals were different and showed a significant correlation with their relative abundance. Most species were related to vegetation characteristics, except primates (Macaca thibetana), and rodents (Leopoldamys edwardsi). Therefore, to establish conservation policies for nonprotected areas, habitat characteristics should be of prime concern, followed by increasing the size of protected areas to provide effective refuge areas for species conservation

UAV disturbance to wildlife data

The data includes UAV audio recordings taken in Wytham Woods, Oxford and secondary data of species audiograms. The data was then analysed using R and the code used for processing is available here - https://github.com/Isladup/acoustic_drone_disturbanc

Advancing remote sensing methods to monitor wildlife

Historically, natural history museums have collected and preserved specimens to provide data on the occurrence and distribution of wildlife populations. Zoologists still track animals by recording footprints, collecting dung and spoor and observing, recording and quantifying behaviour from the ground. However, these traditional observational techniques allow only a few populations to be monitored at once at limited spatial scales and disturbance from the ground can disrupt observation of natural behaviour. We are now in a golden age of technological advances and are able to remotely monitor and track wildlife via a variety of electronic sensors. Significant questions remain about how best to methodologically apply these new technologies for the purposes of wildlife monitoring. In this thesis, I consider challenges of using Earth observation satellites and unmanned aerial vehicles (UAVs) to track wildlife and understand movement in relation to the expanding human footprint and anthropogenic risk. Specifically: (i) I collate and analyse spatially explicit data on the distribution of illegal hunting incidences via a systematic map. I show that hunting increases in proximity to roads, water bodies, and human settlement areas and there is a considerable lack of systematically collected quantitative data. (ii) I investigate acoustic disturbance to understand anthrophony from the species perspective. I create a mitigation method applied in the case of UAV noise using species weighted audiograms (iii) I test whether very high-resolution satellite imagery and machine learning can be used to automate the detection of African elephants in vast heterogeneous landscapes. This is achieved presenting a new method to monitor elephants (iv) I record the spatial relationship of African elephants in relation to the human footprint using GPS tracking data and satellite imagery. I show elephants readily adapt their foraging habits and itineraries, spatially and temporally in relation to human settlement. Accurate and up-to-date data is vital for effective wildlife conservation planning. Remote sensing technologies offer enhanced capabilities to understand the spatial relationship between wildlife and the increasing human footprint. This body of work contributes to the global wildlife conservation effort by devising methods that can enable more reliable data collection at larger spatial scales

What spatially explicit quantitative evidence exists that shows the effect of land tenure on illegal hunting of endangered terrestrial mammals in sub-Saharan Africa? A systematic map protocol

Background Over the last two decades there has been an increase in the demand for land in Sub Saharan Africa, particularly from foreign agribusiness investment to provide food for an increasing human population. The majority of land outside of protected areas in sub-Saharan Africa is under customary tenure. Due to poor land administration in the region, communities living in undocumented land areas tend to be at greater risk of eviction from increasing liberalisation of land markets. To prevent local displacement and disturbance to investment caused by land disputes tenure clarification is growing in importance on national and international agendas. Land conversion can fragment wildlife habitat while reducing the suitable range areas of terrestrial mammal populations on the continent. Simultaneously illegal hunting is on the rise for a wide variety of taxa driven by a demand for food and income from the sale of animal products. To enable a better understanding of how land tenure arrangements impact upon spatial variations in illegal hunting, this protocol sets out the parameters for an evidence map which will collate and analyse the spatially explicit quantitative evidence that exists showing the effect of land tenure on illegal hunting of endangered terrestrial mammals in sub-Saharan Africa. Sub-Saharan Africa is the region of focus as it contains the highest number of terrestrial mammals listed as vulnerable, endangered or critically endangered by the International Union for Conservation of Nature. Taking stock of what methods have been used to gather data and where evidence exists can guide future research in this area while informing conservation interventions. Methods This evidence map will compare: (1) data availability on the spatial distribution of illicit hunting of endangered terrestrial mammals across different land tenure regimes in sub-Saharan Africa; (2) research methodologies that have primarily been used to collect quantitative data on illegal hunting and comparability of existing data; (3) preferences in the research body toward particular taxa and geographical areas, (4) the evidence map will provide an analysis on the influence other environmental and anthropogenic determinants that influence the spatial distribution of illicit hunting incidences, e.g., proximity to roads, water bodies, range patrol bases etc. Eight academic databases and numerous organisation repositories will be searched for relevant studies by three authors. Double screening will be carried out on all articles to locate studies that meet the specified inclusion criteria, for inclusion studies must contain spatially explicit quantitative data on illegal hunting of endangered terrestrial mammals as defined by the International Union for the Conservation of Nature. Relevant information from studies will be extracted to a custom-made extraction form. The resulting map will consist of a narrative synthesis, descriptive statistics and a heat map in the form of a matrix. By providing an overview of the evidence base the resulting map can inform future meta-analyses by showing where there is sufficient comparable data while guiding conservation interventions by indicating geographical areas where species are most at risk

The spatial distribution of illegal hunting of terrestrial mammals in Sub-Saharan Africa: a systematic map

Background There is a rich body of literature addressing the topic of illegal hunting of wild terrestrial mammals. Studies on this topic have risen over the last decade as species are under increasing risk from anthropogenic threats. Sub-Saharan Africa contains the highest number of terrestrial mammals listed as vulnerable, endangered or critically endangered. However, the spatial distribution of illegal hunting incidences is not well documented. To address this knowledge gap, the systematic map presented here aims to answer three research questions: (1) What data are available on the spatial distribution of illegal hunting of terrestrial mammals in Sub-Saharan Africa in relation to environmental and anthropogenic correlates i.e. proximity to roads, water bodies, human settlement areas, different land tenure arrangements and anti-poaching ranger patrol bases? (2) Which research methodologies have primarily been used to collect quantitative data and how comparable are these data? (3) Is there a bias in the research body toward particular taxa and geographical areas? Methods Systematic searches were carried out across eight bibliographic databases; articles were screened against pre-defined criteria. Only wild terrestrial mammals listed as vulnerable, endangered or critically endangered by the International Union for Conservation of Nature (IUCN) whose geographical range falls in Sub-Saharan Africa and whose threat assessment includes hunting and trapping were included. To meet our criteria, studies were required to include quantitative, spatially explicit data. In total 14,325 articles were screened at the level of title and abstract and 206 articles were screened at full text. Forty-seven of these articles met the pre-defined inclusion criteria. Results Spatially explicit data on illegal hunting are available for 29 species in 19 of the 46 countries that constitute Sub-Saharan Africa. Data collection methods include GPS and radio tracking, bushmeat household and market surveys, data from anti-poaching patrols, hunting follows and first-hand monitoring of poaching signs via line transects, audio and aerial surveys. Most studies have been conducted in a single protected area exploring spatial patterns in illegal hunting with respect to the surrounding land. Several spatial biases were detected. Conclusions There is a considerable lack of systematically collected quantitative data showing the distribution of illegal hunting incidences and few comparative studies between different tenure areas. The majority of studies have been conducted in a single protected area looking at hunting on a gradient to surrounding village land. From the studies included in the map it is evident there are spatial patterns regarding environmental and anthropogenic correlates. For example, hunting increases in proximity to transport networks (roads and railway lines), to water sources, to the border of protected areas and to village land. The influence of these spatial features could be further investigated through meta-analysis. There is a diverse range of methods in use to collect data on illicit hunting mainly drawing on pre-existing law enforcement data or researcher led surveys detecting signs of poaching. There are few longitudinal studies with most studies representing just one season of data collection and there is a geographical research bias toward Tanzania and a lack of studies in Central Africa

Determination of optimal flight altitude to minimise acoustic drone disturbance to wildlife using species audiograms

Unmanned aerial vehicles (UAVs) are increasingly important in wildlife data collection but concern over wildlife disturbance has led several countries to ban their use in National Parks. Disturbance is an animal welfare concern and impedes scientific data collection through provoking aberrant behaviour. Dealing with the issue of disturbance will enable wildlife researchers to use UAV technology more effectively and ethically. Here we present a novel method to determine optimal flight altitude for minimising drone disturbance for wildlife using species audiograms. We recorded sound profiles of seven common UAV systems in the horizontal and vertical planes at 5-m increments up to 120 m. To understand how mammals perceive UAV sound, we used audiograms of 20 species to calculate the loudness of each UAV for each species across the measured distances. These calculations filter the UAV noise based on the sensitivity of species’ hearing over the relevant frequency spectrum. We have devised a method to optimise the trade-off between image spatial resolution and flight altitude. We calculated the lowest point at which either the UAV sound level decreases below an acceptable threshold, here chosen as 40 dB, weighted according to species’ hearing sensitivity, or disturbance cannot be significantly further minimised by flying higher. The latter is quantified as the point above which each additional 5 m of flight altitude causes on average less than 0.05 dB decrease in sound pressure level. Reliable data on appropriate flight altitudes can guide policy regulations on flying UAVs over wildlife, thus enabling increased use of this technology for scientific data collection and for wildlife conservation purposes. The methodology is readily applicable to other species and UAV systems for which sound recordings and audiograms are available