Identifying wildlife observations on twitter

Topcats and underdogs: intraguild interactions among three apex carnivores across Asia's forestscapes

Intraguild interactions among carnivores have long held the fascination of ecologists. Ranging from competition to facilitation and coexistence, these interactions and their complex interplay influence everything from species persistence to ecosystem functioning. Yet, the patterns and pathways of such interactions are far from understood in tropical forest systems, particularly across countries in the Global South. Here, we examined the determinants and consequences of competitive interactions between dholes Cuon alpinus and the two large felids (leopards Panthera pardus and tigers Panthera tigris) with which they most commonly co-occur across Asia. Using a combination of traditional and novel data sources (N = 118), we integrate information from spatial, temporal, and dietary niche dimensions. These three species have faced catastrophic declines in their extent of co-occurrence over the past century; most of their source populations are now confined to Protected Areas. Analysis of dyadic interactions between species pairs showed a clear social hierarchy. Tigers were dominant over dholes, although pack strength in dholes helped ameliorate some of these effects; leopards were subordinate to dholes. Population-level spatio-temporal interactions assessed at 25 locations across Asia did not show a clear pattern of overlap or avoidance between species pairs. Diet-profile assessments indicated that wild ungulate biomass consumption by tigers was highest, while leopards consumed more primate and livestock prey as compared to their co-predators. In terms of prey offtake (ratio of wild prey biomass consumed to biomass available), the three species together harvested 0.4-30.2% of available prey, with the highest offtake recorded from the location where the carnivores reach very high densities. When re-examined in the context of prey availability and offtake, locations with low wild prey availability showed spatial avoidance and temporal overlap among the carnivore pairs, and locations with high wild prey availability showed spatial overlap and temporal segregation. Based on these observations, we make predictions for 40 Protected Areas in India where temporally synchronous estimates of predator and prey densities are available. We expect that low prey availability will lead to higher competition, and in extreme cases, to the complete exclusion of one or more species. In Protected Areas with high prey availability, we expect intraguild coexistence and conspecific competition among carnivores, with spill-over to forest-edge habitats and subsequent prey-switching to livestock. We stress that dhole-leopard-tiger co-occurrence across their range is facilitated through an intricate yet fragile balance between prey availability, and intraguild and conspecific competition. Data gaps and limitations notwithstanding, our study shows how insights from fundamental ecology can be of immense utility for applied aspects like large predator conservation and management of human-carnivore interactions. Our findings also highlight potential avenues for future research on tropical carnivores that can broaden current understanding of intraguild competition in forest systems of Asia and beyond.

Deep learning in terrestrial conservation biology

Biodiversity is being lost at an unprecedented rate on Earth. As a first step to more effectively combat this process we need efficient methods to monitor biodiversity changes. Recent technological advance can provide powerful tools (e.g. camera traps, digital acoustic recorders, satellite imagery, social media records) that can speed up the collection of biological data. Nevertheless, the processing steps of the raw data served by these tools are still painstakingly slow. A new computer technology, deep learning based artificial intelligence, might, however, help. In this short and subjective review I oversee recent technological advances used in conservation biology, highlight problems of processing their data, shortly describe deep learning technology and show case studies of its use in conservation biology. Some of the limitations of the technology are also highlighted.

Ecosystem Services Profiles for Communities Benefitting from Estuarine Habitats along the Massachusetts Coast, USA

The Massachusetts Bays National Estuary Partnership is one of 28 programs in the United States Environmental Protection Agency's National Estuary Program (NEP) charged with developing and implementing comprehensive plans for protecting and restoring the biological integrity and beneficial uses of their estuarine systems. The Partnership has recently updated their comprehensive management plan to include restoration targets for coastal habitats, and as part of this effort, the program explored how to better demonstrate that recovery of ecological integrity of degraded ecosystems also provides ecosystem services that humans want and need. An essential step was to identify key stakeholders and understand the benefits important to them. The primary objective of the study presented here was to evaluate variability in beneficial uses of estuarine habitats across coastal communities in Massachusetts Bays. We applied a text mining approach to extract ecosystem services concepts from over 1400 community planning documents. We leveraged a Final Ecosystem Goods and Services (FEGS) classification framework and related scoping tool to identify and prioritize the suite of natural resource users and ecosystem services those users care about, based on the relative frequency of mentions in documents. Top beneficiaries included residents, experiencers and viewers, property owners, educators and students, and commercial or recreational fishers. Beneficiaries had a surprising degree of shared interests, with top ecosystem services of broad relevance including for naturalness, fish and shellfish, water movement and navigability, water quality and quantity, aesthetic viewscapes, availability of land for development, flood mitigation, and birds. Community-level priorities that emerged were primarily related to regional differences, the local job industry, and local demographics. Identifying priority ecosystem services from community planning documents provides a starting point for setting locally-relevant restoration goals, designing projects that reflect what stakeholders care about, and supporting post-restoration monitoring in terms of accruing relevant benefits to local communities.

'Small Data' for big insights in ecology

Big Data science has significantly furthered our understanding of complex systems by harnessing large volumes of data, generated at high velocity and in great variety. However, there is a risk that Big Data collection is prioritised to the detriment of 'Small Data' (data with few observations). This poses a particular risk to ecology where Small Data abounds. Machine learning experts are increasingly looking to Small Data to drive the next generation of innovation, leading to development in methods for Small Data such as transfer learning, knowledge graphs, and synthetic data. Meanwhile, meta-analysis and causal reasoning approaches are evolving to provide new insights from Small Data. These advances should add value to high-quality Small Data catalysing future insights for ecology.

Environmental sustainability in the online media discourses of Saudi Arabia: A corpus-based study of keyness, intertextuality, and interdiscursivity

This paper investigates the online discourses on "sustainability" and explores how environmental sustainability has been constructed within the Saudi online discourse. In doing so, the study focuses on the potential of the Saudi Green Initiative (SGI), along with Green Riyadh and King Salman Park, to promote sustainability awareness in the kingdom. The corpus of the study comprises news articles and Twitter hashtags. In addition, the study uses corpus-based discourse analysis to examine the keyness and intertextuality. The results of the study convey a contextualized national identity while communicating internationally within discursive circles. It is also identified that interdiscursivity is central in the corpus, although the discourse of action especially dominated other smaller discourses, such as consequences/risks, economy, and tourism. The results also indicate the prominent construction of officials, which could be linked to the dynamics of change in the Saudi scene. Finally, the study emphasizes the action-oriented nature of such discourse while drawing attention to some of the challenging issues to long-term advocacy in the country.

Citizen Science Helps Uncover the Secrets to a Bat-Friendly Swimming Pool in an Urban Environment

For urban environments to support bat communities, resources need to be readily available. For example, bats typically use urban water sources such as drainage ditches and ponds; however, these sources can be ephemeral. During these periods, bats have utilized residential swimming pools, although they only appear to drink at pools when access to more natural equivalents are limited. This posed the question “can we make residential swimming pools friendlier for a diversity of bat species?” Using citizen science to determine which pool characteristics influenced bat activity, we distributed a questionnaire to residents in a suburban neighborhood in Fort Worth, TX, United States. It focused on observations of bat activity and the features of the pools and immediate surroundings. We distributed the questionnaire through social media, local presentations, and by mail throughout 2019 and 2020. We then used classification trees to determine which characteristics in combination influenced bat activity at the pools. We generated three different trees for bats observed (1) flying around the property and backyard, (2) above the swimming pool, and (3) drinking at the pool. We found that more bats were observed at unlit pools without bush or shrub borders. Furthermore, among pools with borders, activity was lowest at pools with textured interiors and ≥6 trees visible. The presence of features, such as fountains, then contributed to a reduction in bat observations in backyards and the presence of pets appeared to further reduce activity specifically over the pools. Where bats were observed drinking, this activity was reported the least at pools with bush or shrub borders, textured interiors, and trees <5 m and >10 m from the edge of the pools. Our study revealed that certain characteristics of residential swimming pools encouraged bat activity, while others discouraged them. Thus, it may be possible to make swimming pools more bat-friendly. For example, turning lights off in the evening when backyards are not in use and reducing clutter around pools could have an immediate positive impact on local bat populations. The implementation of such recommendations could improve urban habitats for bats overall and alleviate some of the negative implications of continued urbanization.