Tracking the spread of the eastern dwarf tree frog (Litoria fallax) in Australia using citizen science

An increasing number of species are establishing populations outside of their native ranges, often with negative ecological and economic impacts. The detection and surveillance of invasive species presents a huge logistical challenge, given the large spatial regions in which new populations can appear. However, data collected through citizen science projects are increasingly recognised as a valuable source for detection and monitoring of invasive species. We use data from a national citizen science project, FrogID, to quantify the spread of the eastern dwarf tree frog (Litoria fallax) outside its historical native range in Australia. Of 48 012 records of L. fallax in the FrogID database, 485 were located far outside the historical native range of the species. L. fallax has established geographically large populations hundreds of kilometres away from its native range, and these appear to be spreading in extent over time. These populations have resulted in novel species co-occurrences, with L. fallax now co-occurring with at least two frog species not present in their native range. Although the impacts of the invasive populations of L. fallax remain unknown, our work highlights the value in leveraging citizen science projects to detect and monitor native species that can become invasive far outside their historical range

Morphometric Variation during Chick Development in Interior Double-crested Cormorants (\u3ci\u3ePhalacrocorax auritus\u3c/i\u3e)

In numerous avian species, egg size is correlated to female body condition, hatchling size and nestling growth. Recent demography studies of Interior Double-crested Cormorants (Phalacrocorax auritus) suggest a migratory divide across the Great Lakes; western populations winter in the Gulf of Mexico region of the southeastern United States (Alabama, Arkansas, Louisiana, and Mississippi) with extensive catfish (Ictalurus punctatus) aquaculture, and eastern populations winter in Florida, where catfish aquaculture is not pervasive. If Double-crested Cormorants have improved their overall body condition through catfish exploitation, then egg and chick sizes should also be affected. Three breeding areas in Ontario (east, central, and west) were selected for empirical measures of size variation. During the breeding seasons of 2006 and 2007, egg, naked young, fledgling, and adult morphometric data were collected. Eggs in eastern areas (volume = 465.8 ± 3.9 cm³) were on average larger than eggs in central (volume = 458.1 ± 3.5 cm³) and western (volume = 451.7 ± 3.5 cm³) areas. However, chicks in eastern areas (culmen = 54.9 ± 0.6 mm) were smaller than chicks in central (culmen = 57.6 ± 0.4 mm) and western (culmen = 59.3 ± 0.3 mm) areas, not only at hatching, but throughout development and fledging. A comprehensive Double-crested Cormorant morphometric gradient that may suggest a potential reproductive advantage for birds exploiting aquaculture facilities is presented

Morphometric Variation during Chick Development in Interior Double-crested Cormorants (\u3ci\u3ePhalacrocorax auritus\u3c/i\u3e)

In numerous avian species, egg size is correlated to female body condition, hatchling size and nestling growth. Recent demography studies of Interior Double-crested Cormorants (Phalacrocorax auritus) suggest a migratory divide across the Great Lakes; western populations winter in the Gulf of Mexico region of the southeastern United States (Alabama, Arkansas, Louisiana, and Mississippi) with extensive catfish (Ictalurus punctatus) aquaculture, and eastern populations winter in Florida, where catfish aquaculture is not pervasive. If Double-crested Cormorants have improved their overall body condition through catfish exploitation, then egg and chick sizes should also be affected. Three breeding areas in Ontario (east, central, and west) were selected for empirical measures of size variation. During the breeding seasons of 2006 and 2007, egg, naked young, fledgling, and adult morphometric data were collected. Eggs in eastern areas (volume = 465.8 ± 3.9 cm³) were on average larger than eggs in central (volume = 458.1 ± 3.5 cm³) and western (volume = 451.7 ± 3.5 cm³) areas. However, chicks in eastern areas (culmen = 54.9 ± 0.6 mm) were smaller than chicks in central (culmen = 57.6 ± 0.4 mm) and western (culmen = 59.3 ± 0.3 mm) areas, not only at hatching, but throughout development and fledging. A comprehensive Double-crested Cormorant morphometric gradient that may suggest a potential reproductive advantage for birds exploiting aquaculture facilities is presented

Estimating sampling biases in citizen science datasets

The rise of citizen science (also called community science) has led to vast quantities of species observation data collected by members of the public. Citizen science data tend to be unevenly distributed across space and time, but the treatment of sampling bias varies between studies, and interactions between different biases are often overlooked. We present a method for conceptualizing and estimating spatial and temporal sampling biases, and interactions between them. We use this method to estimate sampling biases in an example ornithological citizen science dataset from eBird in Brisbane City, Australia. We then explore the effects of these sampling biases on subsequent model inference of population trends, using both a simulation study and an application of the same trend models to the Brisbane eBird dataset. We find varying levels of sampling bias in the Brisbane eBird dataset across temporal and spatial scales, and evidence for interactions between biases. Several of the sampling biases we identified differ from those described in the literature for other datasets, with protected areas being undersampled in the city, and only limited seasonal sampling bias. We demonstrate variable performance of trend models under different sampling bias scenarios, with more complex biases being associated with typically poorer trend estimates. Sampling biases are important to consider when analysing ecological datasets, and analysts can use this method to ensure that any biologically relevant sampling biases are detected and given due consideration during analysis. With appropriate model specification, the effects of sampling biases can be reduced to yield reliable information about biodiversity.Peer reviewe

Fighting the flames: site-specific effects determine species richness of Australian frogs after fire

Context Fire has played an integral role in regulating patterns of biodiversity for millions of years. However, anthropogenic disturbance and climate change has altered fire activity – driving increases in both fire severity and scale. The effect fire now has on the persistence of biodiversity is poorly known, especially for frogs. Studies examining frog responses to fire usually have small sample sizes, focus upon small geographic areas and are based on low-severity fires, which can mean results are not applicable to high-severity fires, such as those expected under future climate change. Aims Our aims were to examine (1) persistence of frog species, measured by species richness, up to 18 months post-fire, and (2) the effects of varying fire severity on frog species richness and recovery, where we expected higher fire severity to lead to lower species richness after fire. Methods Using large-scale citizen science data from the Australian Museum’s FrogID project, coupled with remotely sensed fire data, we present a spatially and taxonomically broad analysis examining post-fire recovery responses for Australian frog species after the 2019/2020 ‘Black Summer’ bushfires. Key results We reveal no overall decrease in the species richness of Australian frogs both in the short- and long-term post-fire. Furthermore, species richness did not decline with increasing fire severity. Instead, species richness and its response to fire was highly site-specific. Conclusions We provide evidence that widespread and common Australian frog species have persisted post-fire in most sites and concluded that this is potentially due to their ability to shelter from fire adequately and/or La Niña-driven high rainfall offering conditions conducive to breeding activity and persistence. Implications We show how citizen science provides critical data for conservation, especially in response to unprecedented disturbance events, such as the 2019/2020 megafires. Our research also highlights the need for ongoing and targeted scientific monitoring, especially for less common or threatened species

First record of Solomons Nightjar Eurostopodus nigripennis for Malaita, with a description of its nest site

Solomons Nightjar Eurostopodus nigripennis, listed as Vulnerable by BirdLife International, has previously been recorded only from the north and central Solomon Islands. Even within the species' known range there are few records, limiting knowledge of its ecology. We provide photographic evidence of a Solomons Nightjar nest in a streambed on the island of Malaita at an altitude of c.270 m - the first record on this large island. This observation, combined with traditional local knowledge, suggests that the species may have a wider range of nesting habitat than previously documented, and that further surveys in collaboration with local tribespeople could be important for conservation efforts

Using citizen science to identify Australia’s least known birds and inform conservation action

Citizen science is a popular approach to biodiversity surveying, whereby data that are collected by volunteer naturalists may help analysts to understand the distribution and abundance of wild organisms. In Australia, birdwatchers have contributed to two major citizen science programs, eBird (run by the Cornell Lab of Ornithology) and Birdata (run by Birdlife Australia), which collectively hold more than 42 million records of wild birds from across the country. However, these records are not evenly distributed across space, time, or taxonomy, with particularly significant variation in the number of records of each species in these datasets. In this paper, we explore this variation and seek to determine which Australian bird species are least known as determined by rates of citizen science survey detections. We achieve this by comparing the rates of survey effort and species detection across each Australian bird species? range, assigning all 581 species to one of the four groups depending on their rates of survey effort and species observation. We classify 56 species into a group considered the most poorly recorded despite extensive survey effort, with Coxen?s Fig Parrot Cyclopsitta coxeni, Letter-winged Kite Elanus scriptus, Night Parrot Pezoporus occidentalis, Buff-breasted Buttonquail Turnix olivii and Red-chested Buttonquail Turnix pyrrhothorax having the very lowest numbers of records. Our analyses provide a framework to identify species that are poorly represented in citizen science datasets. We explore the reasons behind why they may be poorly represented and suggest ways in which targeted approaches may be able to help fill in the gaps.Publisher PDFPeer reviewe

A protocol for reproducible functional diversity analyses

The widespread use of species traits in basic and applied ecology, conservation and biogeography has led to an exponential increase in functional diversity analyses, with > 10 000 papers published in 2010-2020, and > 1800 papers only in 2021. This interest is reflected in the development of a multitude of theoretical and methodological frameworks for calculating functional diversity, making it challenging to navigate the myriads of options and to report detailed accounts of trait-based analyses. Therefore, the discipline of trait-based ecology would benefit from the existence of a general guideline for standard reporting and good practices for analyses. We devise an eight-step protocol to guide researchers in conducting and reporting functional diversity analyses, with the overarching goal of increasing reproducibility, transparency and comparability across studies. The protocol is based on: 1) identification of a research question; 2) a sampling scheme and a study design; 3-4) assemblage of data matrices; 5) data exploration and preprocessing; 6) functional diversity computation; 7) model fitting, evaluation and interpretation; and 8) data, metadata and code provision. Throughout the protocol, we provide information on how to best select research questions, study designs, trait data, compute functional diversity, interpret results and discuss ways to ensure reproducibility in reporting results. To facilitate the implementation of this template, we further develop an interactive web-based application (stepFD) in the form of a checklist workflow, detailing all the steps of the protocol and allowing the user to produce a final 'reproducibility report' to upload alongside the published paper. A thorough and transparent reporting of functional diversity analyses ensures that ecologists can incorporate others' findings into meta-analyses, the shared data can be integrated into larger databases for consensus analyses, and available code can be reused by other researchers. All these elements are key to pushing forward this vibrant and fast-growing field of research.Peer reviewe

Treating gaps and biases in biodiversity data as a missing data problem

Big biodiversity data sets have great potential for monitoring and research because of their large taxonomic, geographic and temporal scope. Such data sets have become especially important for assessing temporal changes in species' populations and distributions. Gaps in the available data, especially spatial and temporal gaps, often mean that the data are not representative of the target population. This hinders drawing large-scale inferences, such as about species' trends, and may lead to misplaced conservation action. Here, we conceptualise gaps in biodiversity monitoring data as a missing data problem, which provides a unifying framework for the challenges and potential solutions across different types of biodiversity data sets. We characterise the typical types of data gaps as different classes of missing data and then use missing data theory to explore the implications for questions about species' trends and factors affecting occurrences/abundances. By using this framework, we show that bias due to data gaps can arise when the factors affecting sampling and/or data availability overlap with those affecting species. But a data set per se is not biased. The outcome depends on the ecological question and statistical approach, which determine choices around which sources of variation are taken into account. We argue that typical approaches to long-term species trend modelling using monitoring data are especially susceptible to data gaps since such models do not tend to account for the factors driving missingness. To identify general solutions to this problem, we review empirical studies and use simulation studies to compare some of the most frequently employed approaches to deal with data gaps, including subsampling, weighting and imputation. All these methods have the potential to reduce bias but may come at the cost of increased uncertainty of parameter estimates. Weighting techniques are arguably the least used so far in ecology and have the potential to reduce both the bias and variance of parameter estimates. Regardless of the method, the ability to reduce bias critically depends on knowledge of, and the availability of data on, the factors creating data gaps. We use this review to outline the necessary considerations when dealing with data gaps at different stages of the data collection and analysis workflow

A protocol for harvesting biodiversity data from Facebook

10 pages, 4 figures, supporting Information https://doi.org/10.1111/cobi.14257.-- Data Availability: This article has earned Open Data and Open Materials badges. Data and materials are available at https://doi.pangaea.de/10.1594/PANGAEA.948104The expanding use of community science platforms has led to an exponential increase in biodiversity data in global repositories. Yet, understanding of species distributions remains patchy. Biodiversity data from social media can potentially reduce the global biodiversity knowledge gap. However, practical guidelines and standardized methods for harvesting such data are nonexistent. Following data privacy and protection safeguards, we devised a standardized method for extracting species distribution records from Facebook groups that allow access to their data. It involves 3 steps: group selection, data extraction, and georeferencing the record location. We present how to structure keywords, search for species photographs, and georeference localities for such records. We further highlight some challenges users might face when extracting species distribution data from Facebook and suggest solutions. Following our proposed framework, we present a case study on Bangladesh's biodiversity—a tropical megadiverse South Asian country. We scraped nearly 45,000 unique georeferenced records across 967 species and found a median of 27 records per species. About 12% of the distribution data were for threatened species, representing 27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. If carefully harvested, social media data can significantly reduce global biodiversity knowledge gaps. Consequently, developing an automated tool to extract and interpret social media biodiversity data is a research priorityS.C. and A.B. gratefully acknowledge the support of the German Centre for Integrative Biodiversity Research (iDiv) and the sMon project funded by the German Research Foundation (DFG-FZT 118, 202548816). VS is supported by a Ramón y Cajal research fellowship (RYC2021-033065-I) granted by the Spanish Ministry of Science and Innovation and he also acknowledges the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accredition (CEX2019-000928-S)Peer reviewe