Biology subjects

Dicks, L. V.

Publications and source records attributed to Dicks, L. V..

7 recordsLinked to original sources

bioRxiv2025

Estimating how Site-Level Differences in Acoustic Environments Affect Species Detection by Machine Learning Models

O_LIMachine learning models are vital in species detection from acoustic data, due to the large amount of recordings produced, especially in passive acoustic monitoring studies. However, the acoustic environment of a site can significantly impact the detectability of species using such models, potentially leading to biased estimates of species abundance and distribution. This impact is poorly understood, and current manual validation methods for assessing acoustic detectability are intractable when working with many species, across multiple locations and datasets, due to the intensive time requirements to manually identify false negatives. C_LIO_LIWe introduce a new method, Noise-Augmented Detectability Estimation (NADE), to estimate the impact of site-specific environmental noise on the acoustic detectability of different species. We use vocalisations augmented with noise from the sites themselves to alleviate the need for manual validation of detectability. Our approach produces site- and species-specific estimates of the complex relationship between background noise, vocalisation amplitude, and acoustic detectability when using a machine learning detection model. We evaluate this method using BirdNET on six bird species, in the UK, demonstrating its potential for broader application in acoustic ecology. C_LIO_LIOur results show that there are large differences in the ability of a machine learning model to detect and classify vocalisations across different sites and species. For example: the detectability of loud vocalisations can be 90% at one site and 10% at another; the detectability at a site can be halved during the course of a survey; and that the amplitude of the background noise alone is insufficient to correctly estimate the detectability of a vocalisation. Detectability at a site can also vary considerably by species: a site can have the relatively high detectability for one species but poorer detectability for another. C_LIO_LIBy providing a quantitative measure of how site-specific background noise affects acoustic detectability, NADE could be used to improve the accuracy of species abundance estimates derived from passive acoustic monitoring, helping to identify sites and times where the detectability is likely to be lower. This approach provides a significant step towards making acoustic detectability estimation more feasible, allowing more robust estimates of species abundance and distribution from acoustic data. C_LI

ecology↗

bioRxiv2025

Predicting the responses of the world's bird species to increases in agricultural production

The intensification and expansion of croplands are among the greatest threats to biodiversity, but the likely responses to these changes remain unknown for most species. Using data on responses of 862 bird species to changes in yields of arable crops, we extrapolate vulnerability to agriculture for the worlds other terrestrial birds based on their traits and taxonomy. We estimate that 74-78% of terrestrial bird species globally suffer population declines where natural habitats are replaced by croplands, and that over half cannot persist in cropland at even the lowest current yields. Past impacts of agriculture on birds have been greatest in the tropics, particularly in coastal forest regions of Central and South America and West Africa and in southern and South-East Asia. Using these estimates to model the impacts of future scenarios of agricultural change, we find that continuing current rates of cropland expansion and yield increases (i.e., extrapolating business-as-usual trends to 2050) is expected to have more negative impacts on birds (particularly in Central and South America, Eastern Europe, sub-Saharan Africa and South and East Asia) than a potential alternative of a targeted strategy of closing yield gaps while limiting cropland expansion. However, we also identify biodiverse regions of the world where closing yield gaps may have more severe impacts on birds than business-as-usual, such as the Pampas of South America and parts of the Sahel region in West Africa. The strategy of least impact for a particular area can be predicted from the response characteristics of the communities of species present there, offering opportunities to take account of regional context for designing less damaging global food production systems.

ecology↗

bioRxiv2024

What works to improve species conservation state? An analysis of species whose state has improved and the actions responsible

Understanding the consequences of past conservation efforts is essential to inform the means of maintaining and restoring species. Data from the IUCN Red List for 67,217 comprehensively assessed animal species were reviewed and analysed to determine (i) which conservation actions have been implemented for different species, (ii) which types of species have improved in state and (iii) which actions are likely to have driven the improvements. At least 51.8% (34,847) of assessed species have actions reported, mostly comprising protected areas (82.7%), with more actions reported for both terrestrial tetrapods and warm-water reef-building corals and fewer for fish, dragonflies and damselflies and crustaceans. Species at greater risk of extinction have a wider range of species-targeted actions reported compared to less threatened species, reflecting differences in documentation and conservation efforts. Six times more species have deteriorated rather than improved in their Red List category. Almost all species that improved have conservation actions in place; species that improved in state typically were historically at high risk of extinction, have smaller ranges and lacked a range of reported threats, particularly hunting and habitat loss or degradation. All types of conservation action were associated with improvements in state, especially reintroductions and invasive species control, alongside, for amphibians and birds, area management. This suggests a range of conservation interventions have successfully conserved some species at greatest risk but have rarely recovered populations to resilient levels. Scaling up the extent and intensity of conservation interventions, particularly landscape-scale actions that benefit broadly distributed species, is urgently needed to assist the recovery of biodiversity.

zoology↗

bioRxiv2019

Vulnerable species interactions are important for the stability of mutualistic networks

Species are central to ecology and conservation. However, it is the interactions between species that generate the functions on which ecosystems and humans depend. Despite the importance of interactions, we lack an understanding of the risk that their loss poses to ecological communities. Here, we quantify risk as a function of the vulnerability (likelihood of loss) and importance (contribution to network stability in terms of species coexistence) of 4330 mutualistic interactions from 41 empirical pollination and seed dispersal networks across six continents. Remarkably, we find that more vulnerable interactions are also more important: the interactions that contribute most to network stability are those that are most likely to be lost. Furthermore, most interactions tend to have more similar vulnerability and importance across networks than expected by chance, suggesting that vulnerability and importance may be intrinsic properties of interactions, rather than only a function of ecological context. These results provide a starting point for prioritising interactions for conservation in species interaction networks and, in areas lacking network data, could allow interaction properties to be inferred from taxonomy alone.

ecology↗

bioRxiv2018

Abundance drives generalisation in hummingbird-plant pollination networks

Abundant pollinators are often more generalised than rare pollinators. This could be because abundance drives generalisation: neutral effects suggest that more abundant species will be more generalised simply because they have more chance encounters with potential interaction partners. On the other hand, generalisation could drive abundance, as generalised species could have a competitive advantage over specialists, being able to exploit a wider range of resources and gain a more balanced nutrient intake. Determining the direction of the abundance-generalisation relationship is therefore a chicken-and-egg dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant-hummingbird pollination networks sampled from a variety of locations across the Americas. For the first time we resolve the direction of the abundance-generalisation relationship using independent data on animal abundance. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, a null model analysis suggests this pattern is due to neutral processes: most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality. These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.\n\nDeclarationsFunding - BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP [NE/L002507/1]. JVB was funded by CERL - Engineer Research and Development Center. PKM was funded by the Sao Paulo Research Foundation (FAPESP grant #2015/21457-4). PAC was funded by the David Lack studentship from the British Ornithologists Union and Wolfson College, University of Oxford. CL was funded by the ESDEPED-UAT grant. MAM acknowledges the Consejo Nacional para Investigaciones Cientificas y Tecnologicas (Costa Rica), German Academic Exchange Service and the research funding program LOEWE-Landes-Offensive zur Entwicklung Wissenschaftlicho konomischer Exzellenz of Hesses Ministry of Higher Education, Research, and the Arts (Germany). ROP was funded by CONACyT (project 258364). MAR was supported by the State of Sao Paulo Research Foundation (FAPESP) within the BIOTA/FAPESP, The Biodiversity Institute Program (www.biota.org.br) and the Parcelas Permanentes project, as well as by Coordenacao de Pessoal de Nivel Superior (CAPES), Fundo de Apoio ao Ensino e a Pesquisa (FAEP)/Funcamp/Unicamp and The Nature Conservancy (TNC) of Brazil. LCR was supported by CNPq and Capes. MS was funded by CNPq (grant #302781/2016-1). AMMG is supported through a Marie Skodowska-Curie Individual Fellowship (H2020-MSCA-IF-2016-704409). LVD was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1). AMMG, JS, CR and BD thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96). WJS is funded by Arcadia.

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↗

bioRxiv2018

bmotif: a package for counting motifs in bipartite networks

O_LIBipartite networks are widely-used to represent a diverse range of species interactions, such as pollination, herbivory, parasitism and seed dispersal. The structure of these networks is usually characterised by calculating one or more metrics that capture different aspects of network architecture. While these metrics capture useful properties of networks, they only consider structure at the scale of the whole network (the macro-scale) or individual species (the micro-scale). Meso-scale structure between these scales is usually ignored, despite representing ecologically-important interactions. Network motifs are a framework for capturing this meso-scale structure and are gaining in popularity. However, there is no software available in R, the most popular programming language among ecologists, for conducting motif analyses in bipartite networks. Similarly, no mathematical formalisation of bipartite motifs has been developed.\nC_LIO_LIHere we introduce bmotif: a package for counting motifs, and species positions within motifs, in bipartite networks. Our code is primarily an R package, but we also provide MATLAB and Python code of the core functionality. The software is based on a mathematical framework where, for the first time, we derive formal expressions for motif frequencies and the frequencies with which species occur in different positions within motifs. This framework means that analyses with bmotif are fast, making motif methods compatible with the permutational approaches often used in network studies, such as null model analyses.\nC_LIO_LIWe describe the package and demonstrate how it can be used to conduct ecological analyses, using two examples of plant-pollinator networks. We first use motifs to examine the assembly and disassembly of an Arctic plant-pollinator community, and then use them to compare the roles of native and introduced plant species in an unrestored site in Mauritius.\nC_LIO_LIbmotif will enable motif analyses of a wide range of bipartite ecological networks, allowing future research to characterise these complex networks without discarding important meso-scale structural detail.\nC_LI

ecology↗