Biology subjects

Cirtwill, A.

Publications and source records attributed to Cirtwill, A..

4 recordsLinked to original sources

bioRxiv2025

Multi-trophic metacommunity responses to habitatnfragmentation in the Brazilian Atlantic Forest

The structure of ecological communities is profoundly altered by anthropogenic disturbance to landscapes. However, most reported impacts rely on the quantification of diversity estimates for single trophic levels or impacts on key species of interest. In this analysis we integrate measures of community structure, comparisons of interaction networks and measures of {beta}-diversity across four trophic levels: plants, bats, bat ectoparasites and bacteria within the ectoparasites. Our data show that bat, bat fly, and bacterial communities are significantly nested across forest fragments, with specialist consumers in all groups being found in fewer fragments than generalists. We found substantial {beta}-diversity in both species richness and interaction richness across fragments but no decline in interaction redundancy with decreasing fragment size, likely because even intact forest networks had very low redundancy in our dataset. Despite the loss of species and interactions, our data provide support for the conservation value of even the smallest and most disturbed forest fragments where essential seed dispersal services are potentially maintained by Artibeus, Carollia and Sturnira and distinct sets of taxa and interactions are supported. These species may be key in the potential recovery of these habitats, but our data highlight the fragility of these communities which have contracted around these disturbance-tolerant species.

ecology↗

bioRxiv2024

Decline of honeybees and its consequences for beekeepers and crop pollination in western Nepal

O_LIPollination service by insects is globally threatened, yet trends outside of Europe and North America are poorly understood. Therefore, in less-studied regions of the world, beekeeper records can provide valuable insights into changes in pollinator populations. C_LIO_LIWe conducted a questionnaire survey of 116 beekeepers in 10 villages in the Jumla District of western Nepal, where the native honeybee Apis cerana cerana is widely kept as a managed honeybee. We complemented the beekeeper survey with field data on insect-crop visitation, a household income survey, and an interview with a local lead beekeeper. C_LIO_LI76% of beekeepers reported declines in the Apis cerana cerana population. 86% experienced declines in honey yield per hive, and 78% reported declines in the number of beehives per beekeeper. Honey yield per hive fell by 50% between 2012 and 2022, whilst the number of occupied hives decreased by 44%. Beekeepers ranked climate change and declining flower abundance as the most-important drivers of the decline. C_LIO_LIThe drastic bee declines raise concerns for the future food and economic security of this region, where honey sales contribute to 16% of total household farming income. Apis cerana cerana plays a major role in crop pollination and contributes more than 50% of all flower visits to apple, cucumber, and pumpkin. C_LIO_LITo mitigate further declines in this region, we promote the use of pollinator-friendly farming practices including more wild flowers and maintenance of native habitat areas, and well-insulated log or top-bar log hives to buffer bees against extreme temperature fluctuations, which are expected to worsen with climate warming. C_LI

ecology↗

bioRxiv2018

A quantitative framework for investigating the reliability of network construction

Descriptions of ecological networks typically assume that the same interspecific interactions occur each time a community is observed. This contrasts with the known stochasticity of ecological communities: community composition, species abundances, and link structure all vary in space and time. Moreover, finite sampling generates variation in the set of interactions actually observed. Here we develop the conceptual and analytical tools needed to capture uncertainty in the estimation of pairwise interactions. To define the problem, we identify the different contributions to the uncertainty of an interaction and its implications for the estimation of network properties. We then outline a framework to quantify the uncertainty around each interaction. We illustrate this framework using the most extensively sampled network to date. We found significant uncertainty in estimates for the probability of most pairwise interactions which we could, however, limit with informative priors. Through these efforts, we demonstrate the utility of our approach and the importance of acknowledging the uncertainty inherent in network studies. Most importantly, we stress that networks are best thought of as systems constructed from random variables, the stochastic nature of which must be acknowledged for an accurate representation. Doing so will fundamentally change networks analyses and yield greater realism.

ecology↗

bioRxiv2018

Uncovering indirect interactions in bipartite ecological networks

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about networks, we show that this shift is supported by quantitative analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight ecologically important differences missed by the current index paradigm. We extend this finding to empirical plant-pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need for a new paradigm for bipartite ecological networks: one incorporating indirect interactions.

ecology↗