Interannual variation in a freshwater recreational fishery under the influence of drought, bushfires, floods and a global pandemic
Faith A. Ochwada-Doyle
A B * , Nathan Miles C , Julian M. Hughes A , Jeffrey J. Murphy D , Kate E. Stark E , Michael B. Lowry F , Laurie D. West G and Matthew D. Taylor B F
A New South Wales Department of Primary Industries, Sydney Institute of Marine Science, Chowder Bay Road, Mosman, NSW 2088, Australia.
B University of New South Wales, Kensington, NSW, Australia.
C New South Wales Department of Primary Industries, Narrandera, NSW 2700, Australia.
D New South Wales Department of Primary Industries, Wollongong, NSW, Australia.
E University of Tasmania, Institute of Marine and Antarctic Studies, Hobart, Tas., Australia.
F New South Wales Department of Primary Industries, Port Stephens, NSW, Australia.
G Kewagama Research, Doonan, Qld, Australia.
Marine and Freshwater Research 74(12) 1102-1112 https://doi.org/10.1071/MF22142
Submitted: 17 July 2022 Accepted: 3 July 2023 Published: 3 August 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY)
Abstract
Context: As social–ecological systems, recreational fisheries often vary temporally in response to environmental changes affecting ecological processes and human behaviour. Monitoring such variability in this ecosystem service can guide adaptive management measures for sustainability.
Aims: This novel research for Australian, sought to quantify interannual changes in the freshwater recreational fisheries of five key (i.e. commonly caught) finfish species (Murray cod, Maccullochella peelii; golden perch, Macquaria ambigua; Australian bass, Percalates novemaculeata; brown trout, Salmo trutta; and rainbow trout, Oncorhynchus mykiss) in relation to a series of extreme climate-related events and the COVID-19 pandemic.
Methods: Annual estimates during 2013–14, 2017–18 and 2019–20 of freshwater fishing effort and catch across New South Wales, Australia, were derived from off-site surveys and compared in relation to a severe drought period, the ‘Black Summer’ bushfires, widespread flooding and the COVID-19 pandemic, all of which affected fish productivity or human mobility.
Key results: There were significant declines in fishing effort between 2013–14, the year preceding the extreme environmental events and the pandemic, and 2017–18 and 2019–20. Catch across the five species was also significantly lower in 2019–20. Catch of species such as golden perch and rainbow trout declined from 2013–14 to 2019–20.
Conclusions and implications: This study can inform adaptive measures against societal and climate-related changes in weather by enabling scientists and managers to identify problematic trends.
Keywords: angling, cascading hazards, climate change, general linear mixed effects models, inland fisheries, Murray–Darling Basin, natural disasters, telephone-diary surveys.
Introduction
The world’s fisheries are socio-ecological systems, representing a nexus between ecological processes and human behaviours (Arlinghaus et al. 2017; Taylor and Suthers 2021). Environmental changes can therefore threaten fisheries and their supporting ecosystems by influencing the productivity of fish stocks or by altering behaviours and decision-making among fishers (Dudgeon et al. 2006; Cooke et al. 2021). In freshwater ecosystems, anthropogenic environmental changes that threaten exploited species include over exploitation, pollution, habitat destruction and invasion by exotic species (Dudgeon et al. 2006; Bond et al. 2011; Forsyth et al. 2013; Burgin 2017). These ecosystems are also threatened by natural shifts in temperature, precipitation and runoff patterns (Dudgeon et al. 2006) which may manifest as extreme weather events (Morrongiello et al. 2011a; Scott et al. 2020). Although each of these environmental factors can have substantial independent effects on freshwater species, they can also act synergistically to have major impacts on freshwater fisheries (Leprieur et al. 2008; Rabalais et al. 2010).
At a global scale, the clearest example of this synergy is climate change, which has been accelerated over the past century by human-induced emission of green-house gases (Pachauri and Reisinger 2007; Füssel 2009). Climate change is estimated to threaten ~50% of global freshwater fish species by directly altering species distributions and survival rates (Parmesan and Matthews 2006; Bassar et al. 2016). Alterations to annual precipitation and temperature regimes due to climate change are also likely to amplify the impacts and frequency of localised extreme weather events such as droughts (Milly and Wetherald 2002; Trenberth 2005), storms, floods and wildfires (Füssel 2009; Reid et al. 2019); each of which can affect freshwater fish. Droughts, for example, cause declines in water levels, which can affect fish detrimentally through temperature and oxygen stress or introduction of disease (Morrongiello et al. 2011b; Lennox et al. 2019). This can result in spawning failures, reduced growth, assemblages crowded with predators and competitors and, in the Australian context, promote species invasion (Lennox et al. 2019; Sheldon et al. 2022). Changes in flows and water levels can also result in fish being isolated in fragmented pool habitats of poor water quality. When such extreme events happen in succession, their consequences on freshwater ecosystems and their services can be multiplicative (Alexandra and Finlayson 2020; Kemter et al. 2021). For freshwater stocks in developed countries, recreational fishing is a major ecosystem service (Cooke and Cowx 2006; Arlinghaus et al. 2017) and research documenting temporal changes in this service in relation to extreme weather events enables managers to undertake risk assessment and adaptation towards long-term fisheries sustainability (Hunt et al. 2016; Sainsbury et al. 2018). Although several international studies have explored these relationships in the context of broad climate change effects (Jones et al. 2013; Hunt et al. 2016; Jeanson et al. 2021), there are a limited number of Australian studies examining variation in freshwater recreational fisheries in relation to extreme climate-related events.
In addition to affecting ecosystems that support fisheries, environmental changes often occur over a changing social, economic and political landscape. These societal changes can affect fisher behaviour and decision-making and therefore compound environmental impacts on fisheries (Arlinghaus et al. 2017; Taylor and Suthers 2021). For example, the emergence of the global pandemic caused by the SARS-CoV-2 virus (COVID-19), which has been partly attributed to human-induced environmental changes such as habitat encroachment and urban sprawl (Barouki et al. 2021; Kumar and Ayedee 2021), was an atypical event that had unprecedented impacts on economies, human mobility and use of aquatic ecosystems. It therefore affected the distribution of fishing effort and catch in Australian marine systems and other parts of the world (Coll et al. 2021; Ryan et al. 2021). However, just like the impacts of extreme whether events, there is no published work tracking freshwater recreational fishing in Australia in relation to the societal and behavioural changes caused by COVID-19.
In the Australian jurisdictions of New South Wales (NSW) and the Australian Capital Territory (ACT), off-site surveys are regularly used to track spatio-temporal patterns of recreational fishing activity (Ochwada-Doyle et al. 2021; Murphy et al. 2022). The freshwater systems of these jurisdictions are primarily recreational-only (Forbes et al. 2020; NSW Department of Primary Industries 2020) and support ~26% of the study area’s total recreational fishing effort (West et al. 2015; Murphy et al. 2020, 2022), making the surveys a vital fisheries-monitoring tool. A standardised survey design was first implemented in NSW and ACT in 2013–14. The survey design was repeated for 2017–18 and 2019–20, a period when COVID-19 spread through NSW and ACT and a series of extreme weather events occurred in the region. These events were (1) the most severe drought recorded in the European history of Australia (Bureau of Meteorology 2020), (2) the ‘Black Summer’ bushfires, which burnt through more land than any fires in the past 25 years (Alexandra and Finlayson 2020; Rural Fire Service 2020) and (3) heavy rainfall and subsequent flooding that led to some of the highest river levels since 1992 (Kemter et al. 2021). This synchronicity created a unique opportunity to track changes in recreational fishing metrics alongside the occurrence of a series of atypical events. This work assessed (1) changes in total fishing effort and the total catch of finfish species in NSW and ACT freshwater systems among 2013–14, 2017–18 and 2019–20, and (2) changes in the species-specific catch of the region’s five most sought-after freshwater finfish. This research aimed to monitor patterns of fishing across 3 years that happened to coincide with atypical environmental and social events, rather than elucidate conclusive causal relationships between the events and the fishery. This research encompassed all freshwaters of NSW and ACT, which can be divided into the following three geographic regions: the Eastern Basin (east of the Great Dividing Range), the Murray–Darling Basin (west of the Great Dividing Range including the ACT) and the South East Basin (the majority of the Snowy Mountains region) (Fig. 1; Murphy et al. 2022). The Murray–Darling Basin, which covers 14% of Australia’s land, is of particular significance in terms of the nation’s water, agriculture and fisheries management (Koehn 2015). It accounts for 66% of Australia’s total agricultural water consumption, supports an agriculture industry valued at A$15 billion year−1, provides habitat for 26 native fish species and supports 80% of the annual freshwater recreational fishing effort in NSW and ACT (Humphries et al. 1999; Koehn 2015; Murphy et al. 2022).
Australian map, indicating the relative sizes and locations of New South Wales (NSW) and the Australian Capital Territory (ACT). Included is a timeline indicating the sequence of social and environmental events that took place within NSW and ACT during the 2017–18 and 2019–20 recreational fishing surveys. Note that a preceding 2013–14 survey is not included in the timeline depicted here (NSW Department of Primary Industries 2019; Alexandra and Finlayson 2020; Bureau of Meteorology 2020; Davey and Sarre 2020; Storen and Corrigan 2020; Wang et al. 2020; Kemter et al. 2021; Huveneers et al. 2021).
Materials and methods
Data collection
This study utilised recreational fishing data collected across all freshwater systems in New South Wales (NSW) and the Australian Capital Territory (ACT; Fig. 1). Data on recreational catch and effort were collected for fishing activity that occurred during the 2013–14, 2017–18 and 2019–20 periods. For all three 12-month periods, the data were collected using an off-site telephone-diary survey methodology that was developed to provide cost-effective, state-wide fishery information over a large spatial scale (Lyle et al. 2002; Henry and Lyle 2003; West et al. 2015).
The telephone–diary approach involved two phases, namely an initial Screening Phase followed by an intensive Diary Phase. These phases are described in greater detail in Murphy et al. (2020) and Murphy et al. (2022). In brief, the Screening Phase was conducted from March to May 2013, from September to October 2017 and from August to October 2019. This phase was conducted as a structured telephone interview of a randomly selected sample of 1–3-year licence holders listed within the NSW Recreational Fishing Licence (RFL) database (Murphy et al. 2020, 2022). The shortcomings of broad-scale offsite surveys that rely on fisher-based databases such as the RFL are discussed in Taylor and Ryan (2020) and Ochwada-Doyle et al. (2021). They include reliance on a sample that is dominated by moderate and highly avid fishers, rather than those who only fish a few times per year. Such designs can also preclude robust estimation of species-specific effort or catch rate (catch per unit effort, CPUE), because of their broad assessment of multiple and varied fishing methods for many species and an inability to disaggregate effort that leads to kept catch versus released catch (Ochwada-Doyle et al. 2022). Furthermore, off-site surveys are generally limited in accuracy and precision when it comes to estimating the catch of infrequently caught species or those caught as part of ‘niche’ recreational fisheries. During the Screening Phase, 1882, 1960 and 1990 RFL households were selected and contacted as part of the net sample for 2013–14, 2017–18 and 2019–20 respectively (Murphy et al. 2020, 2022). The number of RFL households that responded to the complete screening survey in 2013–14 was 1686, compared with 1618 for 2017–18 and 1608 in 2019–20. These households answered questions regarding their intention to fish in the ensuing 12 months to determine their eligibility for the Diary Phase (Murphy et al. 2020, 2022). Profiling information, including age, gender and fishing avidity (measured as a function of estimated fishing frequency in the previous 12 months for residents aged ≥5 years), was also collected for each resident of a sampled household during the Screening Phase (Murphy et al. 2020).
The Diary Phase comprised a longitudinal panel survey that monitored the fishing activity of all residents (aged 5 years or older) within recruited households between June 2013 and May 2014, between October 2017 and September 2018 and between November 2019 and October 2020 (Murphy et al. 2020, 2022). For 2013–14, 87% of eligible households completed the Diary Phase, 89% completed this phase for 2017–18, and 75% completed it for 2019–20 (Murphy et al. 2020, 2022). A single diarist within each household that participated in each year’s Diary Phase recorded basic information after each fishing event undertaken by any household resident (aged ≥5 years) including unlicenced members of the household and those with short-term licences. This information included date, location, start and finishing times and numbers of kept and released fish by species or species group (Murphy et al. 2020, 2022). Throughout the diary period, trained interviewers telephoned diarists at regular, repeated intervals to conduct structured interviews that collected more detailed data on each fishing event (with each fishing event being defined as a single fishing trip made on a single day). These data included fishing method, fishing platform (boat-based or shore-based), waterbody type (freshwater, estuarine or oceanic) and target species. The numbers of fish that were retained (i.e. harvested and kept by anglers) and released (i.e. discarded for any reason) by species or species group were also verified during these interviews (Murphy et al. 2020; Murphy et al. 2022).
Fig. 1 illustrates the sequence, duration, severity and spatial extent of three extreme weather events (wide-spread drought, bushfires and heavy rainfall resulting in flooding) as well as the COVID-related restrictions relative to the timing of the 2017–18 and 2019–20 recreational fishing surveys. This study, involving human participants, was approved by the New South Wales Department of Primary Industries Human Ethics process (INT20/76587).
Data analysis
All analyses and graphing described hereafter were executed within the statistical programming software R (ver. 3.61 32 bit, R Foundation for Statistical Computing, Vienna, Austria, see https://www.r-project.org/). Details on the analytical expansion of the core survey data can be found in West et al. (2015) and Murphy et al. (2020). This analysis was based on a stratified random survey design that used single-stage cluster sampling, with the RFL holders representing the primary sampling unit (n = sample size in terms of RFL holders) within a household where the activity of all resident fishers was surveyed. Expansion of information collected from each sampled household to population estimates relied on an integrated approach that calibrated against population benchmarks and adjusted for non-response using logistic generalised linear models (Lyle et al. 2010; West et al. 2015). Expansion and calibration to attain population estimates of catch and associated standard errors (s.e.) were completed using the Survey (Lumley 2010) package, on the basis of the instructions detailed in Lyle et al. (2010). Refer to Lyle et al. (2010) and Lumley (2010) for equations.
The native species Murray cod (Maccullochella peelii), golden perch (Macquaria ambigua) and Australian bass (Percalates novemaculeata), and the introduced species brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss) are among the five most commonly caught finfish species in freshwater river and lake or dam environments of NSW and ACT (Murphy et al. 2022). The expanded estimates of retained and released catch (numbers) of these species were calculated for freshwater environments during each survey period. Both species-specific estimates of catch and total catch estimates across these five species were calculated. It should be noted that seasonal closures to harvesting Australian bass, Murray cod, rainbow trout and brown trout apply in NSW and ACT rivers. Because the closures for each species are applied at the same time each year, annual catch estimates should not be affected by the closures from one year to the next. Expanded estimates of total recreational fishing effort (fisher days) were also calculated for freshwater environments during each survey period.
Using the glmer.nb() function in the lme4 package (ver. 1.1-26, see https://CRAN.R-project.org/package=lme4; Bates et al. 2015, 2020), generalised linear mixed-effects models (GLMMs) assuming a negative binomial distribution were utilised to examine whether species-specific catch, total catch and effort changed among the three survey years, which had three levels, namely 2013–14, 2017–18 and 2019–20 (Maunder and Punt 2004; Coelho et al. 2020). The use of GLMMs enabled us to account for any non-independence among primary sampling units through inclusion of random-effects terms for individual persons and households (Zuur et al. 2009; Morrongiello and Thresher 2015). For catch data from each survey period, separate analyses were conducted for kept and released catch data. The GLMMs took the following form:
where Y represents the catch (numbers kept or released) or effort (fisher days) of a sampled angler after it has been expanded to represent the catch or effort of all anglers in the whole known population that are represented by that sampled angler, β0 is the vertical intercept, β1 is the regression coefficient for the independent parameter Year (x1,ij); a1,i and a2,j represent the random variables associated with Person i and Household j, and εij represents the error term (Quinn and Keough 2002; Coelho et al. 2020). Models were initially fitted assuming both a Poisson and a negative binomial distribution family. Akaike information criteria (AICs) were then generated for each model by using the aictab() function, and were used to select the model that had most appropriate distribution family, whereby the model with the lowest AIC values was deemed most appropriate (Quinn and Keough 2002). The AIC values consistently showed that the negative binomial distribution provided the best fitting models. For each negative binomial model, partial tests within analyses of deviance tables (generated using the Anova() function) were then used to assess the influence of year on catch and effort, whereby Wald tests (α = 0.05) examined the null hypothesis that β1 = 0 (Quinn and Keough 2002; Bates et al. 2015; Duursma and Powell 2016). Where the influence of year in a model was shown to be significant, the summary() function was used to evaluate whether differences between pairs of years were significant at α = 0.05. The relevel() function allowed us to switch reference levels in the models, thereby enabling determination of exactly where significant differences among years lay.
Results
The sample sizes (n = number of RFL holders) used in the survey expansion procedure to estimate the catch or effort for a particular year are shown in Table 1. This also represents the sample size for each level of year in the GLMMs. The models showed that year had a statistically significant relationship with the total effort (in fisher days) exerted by recreational fishers within the freshwaters of NSW and ACT (n = 1225; χ2 = 8.86; d.f. = 2; Pr(>χ2) = 0.01). Effort was highest in 2013–14 and similarly low in 2017–18 and 2019–20 (Fig. 2). Total retained and released catch across the five key species studied were also significantly different among the 3 years, with both components of catch being similarly high in 2013–14 and 2017–18 and lowest in 2019–20 (Fig. 3, Table 2).
| Item | 2013–14 | 2017–18 | 2019–20 |
|---|---|---|---|
| Effort data | |||
| Total effort | 536 | 414 | 275 |
| Catch data | |||
| Australian bass | 43 | 67 | 26 |
| Brown trout | 42 | 43 | 34 |
| Golden perch | 209 | 141 | 68 |
| Murray cod | 222 | 174 | 108 |
| Rainbow trout | 47 | 50 | 30 |
| Key finfish combined | 375 | 307 | 188 |
This also represents the sample size for each level of year in the GLMMs.
Estimated total effort (number of fisher days × 1000) exerted through recreational fishing activity in NSW and ACT freshwaters in 2013–14, 2017–18 and 2019–20. Error bars represent 1 s.e. of the total estimated effort. Significant P-values (α = 0.05) from pairwise comparisons of years are indicated by an asterisk (*), with the associated year in the comparison being labelled.
Estimated freshwater catch (numbers × 1000) of Australian bass, brown trout, golden perch, Murray cod and rainbow trout (a) retained and (b) released through recreational fishing activity in NSW and ACT in 2013–14, 2017–18 and 2019–20. Also shown is the total catch estimated across these five key finfish species. Error bars represent 1 s.e. of the total estimated effort. Significant P-values (α = 0.05) from pairwise comparisons of years are indicated by asterisk (*), with the associated year in the comparison being labelled.
| Item | Retained catch | Released catch | ||||
|---|---|---|---|---|---|---|
| χ2 | d.f. | Pr(>χ2) | χ2 | d.f. | Pr(>χ2) | |
| Australian bass (n = 136) | ||||||
| Year | 1.72 | 2 | 0.42 | 0.40 | 2 | 0.82 |
| Brown trout (n = 119) | ||||||
| Year | 2.43 | 2 | 0.30 | 0.53 | 2 | 0.77 |
| Golden perch (n = 418) | ||||||
| Year | 79.59 | 2 | <2.00E−16* | 32.79 | 2 | 7.58E−08* |
| Murray cod (n = 504) | ||||||
| Year | 1.38 | 2 | 0.50 | 22.47 | 2 | 1.32E−05* |
| Rainbow trout (n = 127) | ||||||
| Year | 7.04 | 2 | 0.03* | 31.06 | 2 | 1.80E−07* |
| Key finfish combined (n = 870) | ||||||
| Year | 27.88 | 2 | 8.85E−07* | 13.82 | 2 | 9.99E−04* |
The models, which assumed a negative binomial distribution, applied the Wald test (α = 0.05) to examine the null hypothesis that a βi = 0, where β is were the regression coefficients for year. Significant P-values are indicated by an asterisk (*).
Analysis of the species-specific data showed variation among the five species in terms of the relationship between year and retained or released catch. In terms of retained catch, golden perch and rainbow trout showed significant differences among the years (Fig. 3a, Table 2). The retained catch numbers for golden perch were highest in 2013–14 and lowest in 2019–20 (Fig. 3a, Table 2). The retained catch numbers for rainbow trout were highest in 2013–14 and 2017–18 and lowest in 2019–20 (Fig. 3a, Table 2). Golden perch, Murray cod and rainbow trout showed a significant difference in the numbers released among the 3 years (Fig. 3b, Table 2). The released numbers of golden perch were highest in 2013–14 and lowest in 2019/20 (Fig. 3b, Table 2). For Murray cod, the released catch numbers were highest in 2017–18 and low during 2013–14 and 2019–20 (Fig. 3b, Table 2). For rainbow trout, numbers released were highest in 2017–18 and lowest in 2019–20 (Fig. 3b, Table 2). This study’s raw data are provided in the Supplementary Tables S1–S7.
Discussion
Recreational fishing is a dominant ecosystem service within freshwater bodies in many industrialised nations (Cooke et al. 2015; Hunt et al. 2016) and understanding how this fishery may be influenced by environmental change under projected climate scenarios is imperative for adaptive management to improve sustainability (Jeanson et al. 2021). This study uncovered interannual variability in an expansive freshwater recreational fishery that occurred in conjunction with a series of extreme climate-related environmental events as well as a global pandemic, which altered human behaviour and economies and was linked to anthropogenic environmental changes (Barouki et al. 2021; Kumar and Ayedee 2021).
Using examples from this study, the following discussion demonstrates how recreational fisheries may be governed by a unique complex of socio-ecological parameters in a fluctuating world (Arlinghaus et al. 2017). However, it must be noted that unequivocal causal relationships cannot be inferred here due to the absence of a randomly selected set of ‘control sites’ where recreational fishing activity was monitored over the same time period in the absence of the extreme weather events and the societal disruptions in question. Such sites may have enabled application of a before–after–control–impact (BACI) design to the study’s analyses (Underwood 1992). Many of the putative relationships and mechanistic processes described below are therefore exploratory in nature.
Changing climates in arid regions such as Australia are anticipated to increase temperatures and decrease rainfall and river flows, resulting in more frequent and extended drought conditions (Reid et al. 2019). The past two decades have seen south-eastern Australia experience some of its worst historical droughts (Bond et al. 2008; NSW Department of Primary Industries 2019). In freshwater bodies, the combination of elevated temperatures, low oxygen concentrations, increased stratification and low-flow or stagnant conditions observed during drought can lead to isolation of populations within poor or toxic conditions, causing extensive fish-kills (Bond et al. 2008; Vertessy et al. 2019; Sheldon et al. 2022). In the summer periods of 2018–19 and 2019–20, for example, fish-kill events that lead to the loss of millions of native fish in the Darling–Baaka River were attributed to hypoxia in a protracted period of low-flow associated with climatic events (Stocks et al. 2022). Species observed among the fish-kills included golden perch and Murray cod (Stocks et al. 2022). Although the drought-related fish-kills initially affected populations of these species, no significant changes in golden perch and Murray cod abundances were observed 18 months after the fish-kills. The fish-kills would have, therefore, affected the numbers of golden perch and Murray cod caught only for a short period and are unlikely to have caused the fishery declines observed between 2017–18 and 2019–20 (Stocks et al. 2022). Even so, the fish-kill events of 2019–20 could still have contributed to some immediate reductions in the recreational catch of these species during that year. Unlike for golden perch, which is kept and released at numbers relatively similar to those of Murray cod (Murphy et al. 2020, 2022), catch-and-release practices are common and increasing in popularity for Murray cod because of restrictive regulations (e.g. slot limit of 55–75 cm) and changing attitudes towards voluntary release (Douglas et al. 2010; Murphy et al. 2020, 2022). For Murray cod, any potential fishery impacts may have, therefore, been easier to detect in the released catch.
In many parts of the world, the frequency and intensity of bushfires has increased in recent years and is projected to escalate with expected climatic and land-use changes (Bixby et al. 2015; Nunes et al. 2017). In NSW and ACT (~816 000 km2), the ‘Black Summer’ bushfires of 2019–20 burned through ~57 000 km2. This was nearly double the area of any previous bushfires (Alexandra and Finlayson 2020; Davey and Sarre 2020). Fires may alter freshwater ecosystems by destroying riparian and wetland vegetation, resulting in nutrient mobilisation, changed microclimatic regimes, modified biogeochemistry, and increased runoff, erosion, ash and sediment inputs into waterways (Bixby et al. 2015; Nunes et al. 2017). Each of these processes may harm aquatic fish and limit availability of prey items (periphyton, phytoplankton and macroinvertebrates) (Bixby et al. 2015; Nunes et al. 2017). In a North American study, Rosenberger et al. (2015) found that older rainbow trout was least abundant in streams within burned watersheds and most abundant in streams with unburned watersheds. Rainbow trout from burned watersheds also had faster growth, earlier maturity and lower lipid content than did those in unburned watersheds (Rosenberger et al. 2015). Although our comparisons encompass a shorter period, similar processes may have contributed to the reduced retained and released catch observed for rainbow trout in 2019–20 compared with 2013–14 and 2017–18.
Intensified water cycling associated with a mean global temperature increase of as little as 1.5°C is anticipated to increase the magnitude of floods (Talbot et al. 2018). Accordingly, many eastern Australian river systems experienced the highest water levels recorded in the past 30 years following recent flood events (Alexandra and Finlayson 2020; Bureau of Meteorology 2020; Kemter et al. 2021). Because flood duration and magnitude are correlated with the availability of suitable fish habitat (King et al. 2003) and the density and diversity of piscivore prey species (Luz-Agostinho et al. 2009), floods may influence the abundance of fish within important freshwater systems such as the Murray–Darling Basin (Harris and Gehrke 1994; King et al. 2003). Using experiments in ponds, Gehrke et al. (1993) demonstrated how the lethal concentrations of chemical leachates from riparian vegetation and the hypoxic, acidic conditions that follow flooding can limit habitat suitability and affect freshwater fish such as larval and juvenile golden perch. Even so, it remains unknown whether these adverse conditions affect the presence of adult fish of catchable size to a similar extent. Many other contributing factors may be linked to the significantly lower annual recreational catch numbers observed for golden perch in 2019–2020 than in 2017–18. For example, flood events can affect access to fishing areas, which may decrease angler satisfaction and cause a shift in angling effort (Cahill et al. 2018; Birdsong et al. 2021).
Following the drought of 2018–19, the bushfires in NSW and ACT were the second step in an entire cascade of adverse environmental impacts on freshwater ecosystem services (Kemter et al. 2021). The subsequent heavy rainfall events in 2020 triggered increased surface runoff, transported ash and eroded soil, enhancing sedimentation and deterioration of water quality in freshwater systems (Nunes et al. 2017; Silva et al. 2020; Legge et al. 2022). This link between sequential drivers has been widely described as a ‘cascade’ of environmental events; characterised by an initial impact that triggers other destructive impacts (Alexandra and Finlayson 2020; Kemter et al. 2021). For example, Verkaik et al. (2013) demonstrated how the response of freshwater communities to fire is often mediated by interactions with preceding droughts or subsequent flood events. Here, the significantly reduced numbers of retained and released recreational catch across all key finfish species and for specific species such as golden perch in 2019–20 may have been the overall result of cascading environmental impacts (Zampatti et al. 2022).
COVID-19 introduced another factor in the cascade of events affecting freshwater ecosystem services and may have influenced fisher behaviour. As governments tried to control the spread of the disease, measures were taken that restricted human movement and led to temporary cessation of non-essential activities, such as tourism and social gatherings (Storen and Corrigan 2020; Fernández-González et al. 2021). Although recreational fishing was allowed in NSW and ACT, enforceable public health orders prohibited travel outside an individual’s local government area. This reduced intra-state tourism and limited fishing to waterbodies within 5–10 km of a fisher’s residence. For metropolitan areas of some Australian jurisdictions, a reduction in fishing participation was subsequently reported (Ryan et al. 2021). Similar observations were reported from Canada during the early phases of the pandemic (Howarth et al. 2021). State border closures largely precluded inter-state fishers from fishing in NSW and ACT and this was expected to reduce fishing effort further. However, freshwater recreational effort did not decrease significantly between the period directly before the pandemic (2017–18) and the period following its spread (2019–20). In fact, the percentage of freshwater fishing effort that was attributed to fishers from bordering states (Queensland and Victoria) was lower in 2017–18 (~15%) than in 2019–10 (~27%) (Murphy et al. 2022). Furthermore, the estimated total number of people that participated in freshwater fishing declined by ~12% from 2013–14 (119 502 ± s.e. 5473 fishers) to 2017–18 (105 613 ± s.e. 5128 fishers), and then declined by only ~8% from 2017–18 to 2019–20 (97 135 ± s.e. 6712 fishers). This suggests a general decline in freshwater recreational fishing activity within NSW and ACT over recent years that may be unrelated to the pandemic and, perhaps to a lesser extent, independent of the extreme weather events. This decline is commensurate with the catch and effort trends observed for recreational fisheries in other Australian jurisdictions (Ryan et al. 2019) and for commercial fisheries within NSW (NSW Department of Primary Industries Commercial Fisheries, unpubl. data). The fact that a significant reduction in effort was detected only between 2013–14 and each of 2017–18 and 2019–20 for this study suggests that the effect of the cascade of extreme weather events that occurred after 2013–14 may have had a larger impact on freshwater recreational effort than did the pandemic.
Conclusions and implications for management
The utility of off-site survey data in monitoring interannual variation in recreational fishing, alongside extreme environmental and societal changes was clearly demonstrated here. Environmental change may affect freshwater catch and effort through ecological fluctuations in fish productivity driven by climate-related events, and through alterations to fishers’ behaviours resulting from socio-economic changes (van Putten et al. 2017; Cooke et al. 2021). The overall ongoing threat of such changes to aquatic systems and the way we use them necessitate adaptive initiatives to manage inland recreational fisheries (Hunt et al. 2016; Howarth et al. 2021; Jeanson et al. 2021). Studies such as this facilitate such adaptation because they enable policy makers and scientists to identify problematic trends and make projections that assist in building strategies to address future ecological and societal stressors (Arlinghaus et al. 2019; Jeanson et al. 2021).
Acknowledgements
We acknowledge the Aboriginal Traditional Custodians of land and waters on which this research was undertaken and recognise their continuous connection with these ecosystems. We show our respect to Elders past, present and emerging. We also thank C. Gallen, A. Steffe, V. Cole, S. Wotherspoon and L. Doyle for their invaluable advice on the analyses and reporting of this data. Our gratitude is also extended to the numerous survey staff from Kewagama Research who assisted in collecting, entering and editing the raw data.
References
Alexandra J, Finlayson CM (2020) Floods after bushfires: rapid responses for reducing impacts of sediment, ash, and nutrient slugs. Australasian Journal of Water Resources 24(1), 9-11.
| Crossref | Google Scholar |
Arlinghaus R, Alós J, Beardmore B, Daedlow K, Dorow M, Fujitani M, Hühn D, Haider W, Hunt LM, Johnson BM, Johnston F, Klefoth T, Matsumura S, Monk C, Pagel T, Post JR, Rapp T, Riepe C, Ward H, Wolter C (2017) Understanding and managing freshwater recreational fisheries as complex adaptive social-ecological systems. Reviews in Fisheries Science & Aquaculture 25(1), 1-41.
| Crossref | Google Scholar |
Arlinghaus R, Abbott JK, Fenichel EP, Carpenter SR, Hunt LM, Alós J, Klefoth T, Cooke SJ, Hilborn R, Jensen OP, Wilberg MJ, Post JR, Manfredo MJ (2019) Governing the recreational dimension of global fisheries. Proceedings of the National Academy of Sciences 116(12), 5209-5213.
| Crossref | Google Scholar |
Barouki R, Kogevinas M, Audouze K, Belesova K, Bergman A, Birnbaum L, Boekhold S, Denys S, Desseille C, Drakvik E, Frumkin H, Garric J, Destoumieux-Garzon D, Haines A, Huss A, Jensen G, Karakitsios S, Klanova J, Koskela I-M, Laden F, Marano F, Franziska Matthies-Wiesler E, Morris G, Nowacki J, Paloniemi R, Pearce N, Peters A, Rekola A, Sarigiannis D, Šebková K, Slama R, Staatsen B, Tonne C, Vermeulen R, Vineis P (2021) The COVID-19 pandemic and global environmental change: emerging research needs. Environment International 146, 106272.
| Crossref | Google Scholar |
Bassar RD, Letcher BH, Nislow KH, Whiteley AR (2016) Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout. Global Change Biology 22(2), 577-593.
| Crossref | Google Scholar |
Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67(1), 1-48.
| Crossref | Google Scholar |
Bates D, Maechler M, Bolker B, Walker S, Christensen RHB, Singmann H, Dai B, Scheipl F, Grothendieck G, Green P, Fox J, Bauer A, Krivitsky PN (2020) Package ‘lme4’, July 5, 2023, version 1.1-34. Linear mixed-effects models using ‘Eigen’ and S4. Available at https://cran.r-project.org/web/packages/lme4/lme4.pdf
Birdsong M, Hunt LM, Arlinghaus R (2021) Recreational angler satisfaction: what drives it? Fish and Fisheries 22(4), 682-706.
| Crossref | Google Scholar |
Bixby RJ, Cooper SD, Gresswell RE, Brown LE, Dahm CN, Dwire KA (2015) Fire effects on aquatic ecosystems: an assessment of the current state of the science. Freshwater Science 34(4), 1340-1350.
| Crossref | Google Scholar |
Bond NR, Lake PS, Arthington AH (2008) The impacts of drought on freshwater ecosystems: an Australian perspective. Hydrobiologia 600(1), 3-16.
| Crossref | Google Scholar |
Bond N, Thomson J, Reich P, Stein J (2011) Using species distribution models to infer potential climate change-induced range shifts of freshwater fish in south-eastern Australia. Marine and Freshwater Research 62(9), 1043-1061.
| Crossref | Google Scholar |
Bureau of Meteorology (2020) Special Climate Statement 70 update—drought conditions in Australia and impact on water resources in the Murray–Darling Basin. 13 August 2020. (Commonwealth of Australia) Available at http://www.bom.gov.au/climate/current/statements/scs70.pdf
Burgin S (2017) Indirect consequences of recreational fishing in freshwater ecosystems: an exploration from an Australian perspective. Sustainability 9, 280-298.
| Crossref | Google Scholar |
Cahill CL, Mogensen S, Wilson KL, Cantin A, Sinnatamby RN, Paul AJ, Christensen P, Reilly JR, Winkel L, Farineau A, Post JR (2018) Multiple challenges confront a high-effort inland recreational fishery in decline. Canadian Journal of Fisheries and Aquatic Sciences 75(9), 1357-1368.
| Crossref | Google Scholar |
Coelho R, Infante P, Santos MN (2020) Comparing GLM, GLMM, and GEE modeling approaches for catch rates of bycatch species: a case study of blue shark fisheries in the South Atlantic. Fisheries Oceanography 29(2), 169-184.
| Crossref | Google Scholar |
Coll M, Ortega-Cerdà M, Mascarell-Rocher Y (2021) Ecological and economic effects of COVID-19 in marine fisheries from the northwestern Mediterranean Sea. Biological Conservation 255, 108997.
| Crossref | Google Scholar |
Cooke SJ, Cowx IG (2006) Contrasting recreational and commercial fishing: searching for common issues to promote unified conservation of fisheries resources and aquatic environments. Biological Conservation 128(1), 93-108.
| Crossref | Google Scholar |
Cooke SJ, Twardek WM, Lynch AJ, Cowx IG, Olden JD, Funge-Smith S, Lorenzen K, Arlinghaus R, Chen Y, Weyl OLF, Nyboer EA, Pompeu PS, Carlson SM, Koehn JD, Pinder AC, Raghavan R, Phang S, Koning AA, Taylor WW, Bartley D, Britton JR (2021) A global perspective on the influence of the COVID-19 pandemic on freshwater fish biodiversity. Biological Conservation 253, 108932.
| Crossref | Google Scholar |
Davey SM, Sarre A (2020) The 2019/20 Black Summer bushfires. Australian Forestry 83(2), 47-51.
| Crossref | Google Scholar |
Douglas J, Brown P, Hunt T, Rogers M, Allen M (2010) Evaluating relative impacts of recreational fishing harvest and discard mortality on Murray cod (Maccullochella peelii peelii). Fisheries Research 106(1), 18-21.
| Crossref | Google Scholar |
Dudgeon D, Arthington AH, Gessner MO, Kawabata Z-I, Knowler DJ, Lévêque C, Naiman RJ, Prieur-Richard A-H, Soto D, Stiassny MLJ, Sullivan CA (2006) Freshwater biodiversity: importance, threats, status and conservation challenges. Biological Reviews 81(2), 163-182.
| Crossref | Google Scholar |
Fernández-González R, Pérez-Pérez MI, Pérez-Vas R (2021) Impact of the COVID-19 crisis: analysis of the fishing and shellfishing sectors performance in Galicia (Spain). Marine Pollution Bulletin 169, 112463.
| Crossref | Google Scholar |
Forbes JP, Todd CR, Baumgartner LJ, Watts RJ, Robinson WA, Steffe AS, Murphy JJ, Asmus MW, Thiem JD (2020) Simulation of different fishery regulations to prevent population decline in a large freshwater invertebrate, the Murray crayfish (Euastacus armatus). Marine and Freshwater Research 71(8), 962-971.
| Crossref | Google Scholar |
Forsyth DM, Koehn JD, MacKenzie DI, Stuart IG (2013) Population dynamics of invading freshwater fish: common carp (Cyprinus carpio) in the Murray–Darling Basin, Australia. Biological Invasions 15(2), 341-354.
| Crossref | Google Scholar |
Füssel H-M (2009) An updated assessment of the risks from climate change based on research published since the IPCC Fourth Assessment Report. Climatic Change 97(3), 469.
| Crossref | Google Scholar |
Gehrke PC, Revell MB, Philbey AW (1993) Effects of river red gum, Eucalyptus camaldulensis, litter on golden perch, Macquaria ambigua. Journal of Fish Biology 43(2), 265-279.
| Crossref | Google Scholar |
Harris JH, Gehrke PC (1994) Modelling the relationship between streamflow and population recruitment to manage freshwater fisheries. Agricultural Systems and Information Technology 6(1), 28-30.
| Google Scholar |
Henry GW, Lyle JM (2003) The national recreational and indigenous fishing survey. FRDC Project Number 99/158, NSW Fisheries Final Report Series Number 48. (Australian Government Department of Agriculture, Fisheries & Forestry: Canberra, ACT, Australia) Available at https://www.frdc.com.au/sites/default/files/products/1999-158-DLD.pdf
Howarth A, Jeanson AL, Abrams AEI, Beaudoin C, Mistry I, Berberi A, Young N, Nguyen VM, Landsman SJ, Kadykalo AN, Danylchuk AJ, Cooke SJ (2021) COVID-19 restrictions and recreational fisheries in Ontario, Canada: preliminary insights from an online angler survey. Fisheries Research 240, 105961.
| Crossref | Google Scholar |
Humphries P, King AJ, Koehn JD (1999) Fish, flows and flood plains: links between freshwater fishes and their environment in the Murray–Darling River System, Australia. Environmental Biology of Fishes 56(1), 129-151.
| Crossref | Google Scholar |
Hunt LM, Fenichel EP, Fulton DC, Mendelsohn R, Smith JW, Tunney TD, Lynch AJ, Paukert CP, Whitney JE (2016) Identifying alternate pathways for climate change to impact inland recreational fishers. Fisheries 41(7), 362-372.
| Crossref | Google Scholar |
Huveneers C, Jaine FRA, Barnett A, Butcher PA, Clarke TM, Currey-Randall LM, Dwyer RG, Ferreira LC, Gleiss AC, Hoenner X, Ierodiaconou D, Lédée EJI, Meekan MG, Pederson H, Rizzari JR, van Ruth PD, Semmens JM, Taylor MD, Udyawer V, Walsh P, Heupel MR, Harcourt R (2021) The power of national acoustic tracking networks to assess the impacts of human activity on marine organisms during the COVID-19 pandemic. Biological Conservation 256, 1-13.
| Crossref | Google Scholar |
Jeanson AL, Lynch AJ, Thiem JD, Potts WM, Haapasalo T, Danylchuk AJ, Beard TD, Arlinghaus R, Hunt LM, Young N, Cooke SJ (2021) A bright spot analysis of inland recreational fisheries in the face of climate change: learning about adaptation from small successes. Reviews in Fish Biology and Fisheries 31(2), 181-200.
| Crossref | Google Scholar |
Jones R, Travers C, Rodgers C, Lazar B, English E, Lipton J, Vogel J, Strzepek K, Martinich J (2013) Climate change impacts on freshwater recreational fishing in the United States. Mitigation and Adaptation Strategies for Global Change 18(6), 731-758.
| Crossref | Google Scholar |
Kemter M, Fischer M, Luna LV, Schönfeldt E, Vogel J, Banerjee A, Korup O, Thonicke K (2021) Cascading hazards in the aftermath of Australia’s 2019/2020 Black Summer wildfires. Earth’s Future 9, e2020EF001884.
| Crossref | Google Scholar |
King AJ, Humphries P, Lake PS (2003) Fish recruitment on floodplains: the roles of patterns of flooding and life history characteristics. Canadian Journal of Fisheries and Aquatic Sciences 60(7), 773-786.
| Crossref | Google Scholar |
Koehn JD (2015) Managing people, water, food and fish in the Murray–Darling Basin, south-eastern Australia. Fisheries Management and Ecology 22(1), 25-32.
| Crossref | Google Scholar |
Kumar A, Ayedee N (2021) An interconnection between COVID-19 and climate change problem. Journal of Statistics and Management Systems 24(2), 281-300.
| Crossref | Google Scholar |
Legge S, Rumpff L, Woinarski JCZ, Whiterod NS, Ward M, Southwell DG, Scheele BC, Nimmo DG, Lintermans M, Geyle HM, Garnett ST, Hayward-Brown B, Ensbey M, Ehmke G, Ahyong ST, Blackmore CJ, Bower DS, Brizuela-Torres D, Burbidge AH, Burns PA, Butler G, Catullo R, Chapple DG, Dickman CR, Doyle KE, Ferris J, Fisher D, Gallagher R, Gillespie GR, Greenlees MJ, Hohnen R, Hoskin CJ, Hunter D, Jolly C, Kennard M, King A, Kuchinke D, Law B, Lawler I, Lawler S, Loyn R, Lunney D, Lyon J, MacHunter J, Mahony M, Mahony S, McCormack RB, Melville J, Menkhorst P, Michael D, Mitchell N, Mulder E, Newell D, Pearce L, Raadik TA, Rowley JJL, Sitters H, Spencer R, Valavi R, West M, Wilkinson DP, Zukowski S (2022) The conservation impacts of ecological disturbance: time-bound estimates of population loss and recovery for fauna affected by the 2019–2020 Australian megafires. Global Ecology and Biogeography 31(10), 2085-2104.
| Crossref | Google Scholar |
Lennox RJ, Crook DA, Moyle PB, Struthers DP, Cooke SJ (2019) Toward a better understanding of freshwater fish responses to an increasingly drought-stricken world. Reviews in Fish Biology and Fisheries 29(1), 71-92.
| Crossref | Google Scholar |
Leprieur F, Beauchard O, Blanchet S, Oberdorff T, Brosse S (2008) Fish invasions in the world’s river systems: when natural processes are blurred by human activities. PLOS Biology 6(2), e28.
| Crossref | Google Scholar |
Luz-Agostinho KDG, Agostinho AA, Gomes LC, Júlio HF Jr, Fugi R (2009) Effects of flooding regime on the feeding activity and body condition of piscivorous fish in the Upper Paraná River floodplain. Brazilian Journal of Biology 69, 481-490.
| Crossref | Google Scholar |
Maunder MN, Punt AE (2004) Standardizing catch and effort data: a review of recent approaches. Fisheries Research 70(2–3), 141-159.
| Crossref | Google Scholar |
Milly PCD, Wetherald RT (2002) Macroscale water fluxes 3. Effects of land processes on variability of monthly river discharge. Water Resources Research 38(11), 17-1-17-12.
| Crossref | Google Scholar |
Morrongiello JR, Thresher RE (2015) A statistical framework to explore ontogenetic growth variation among individuals and populations: a marine fish example. Ecological Monographs 85(1), 93-115.
| Crossref | Google Scholar |
Morrongiello JR, Beatty SJ, Bennett JC, Crook DA, Ikedife DNEN, Kennard MJ, Kerezsy A, Lintermans M, McNeil DG, Pusey BJ, Rayner T (2011a) Climate change and its implications for Australia’s freshwater fish. Marine and Freshwater Research 62(9), 1082-1098.
| Crossref | Google Scholar |
Morrongiello JR, Crook DA, King AJ, Ramsey DSL, Brown P (2011b) Impacts of drought and predicted effects of climate change on fish growth in temperate Australian lakes. Global Change Biology 17(2), 745-755.
| Crossref | Google Scholar |
NSW Department of Primary Industries (2019) Climate – NSW state seasonal update. NSW State Seasonal Update. [January–March, June–December] (NSW DPI) Available at https://www.dpi.nsw.gov.au/dpi/climate/seasonal-conditions-and-drought/nsw-state-seasonal-update
NSW Department of Primary Industries (2020) Background on the Inland Restricted Fishery. Vol. 2020. (NSW DPI) Available at https://www.dpi.nsw.gov.au/fishing/commercial/fisheries/inland-restricted/background-on-the-inland-restricted-fishery
Nunes B, Silva V, Campos I, Pereira JL, Pereira P, Keizer JJ, Gonçalves F, Abrantes N (2017) Off-site impacts of wildfires on aquatic systems: biomarker responses of the mosquitofish Gambusia holbrooki. Science of The Total Environment 581–582, 305-313.
| Crossref | Google Scholar |
Ochwada-Doyle F, Stark K, Hughes J, Murphy J, Lowry M, West L (2021) Temporal and regional variation in catch across an extensive coastal recreational fishery: exploring the utility of survey methods to guide and assess spatio-temporal management initiatives. PLoS ONE 16(7), e0254388.
| Crossref | Google Scholar |
Ochwada-Doyle F, Miles N, Stark K, Hughes J, Murphy J, Lowry M, West L (2022) Spatial variation in species-specific catch and size structures across a large-scale and diffuse freshwater recreational-only fishery. Fisheries Management and Ecology 29(1), 1-15.
| Crossref | Google Scholar |
Rabalais NN, Díaz RJ, Levin LA, Turner RE, Gilbert D, Zhang J (2010) Dynamics and distribution of natural and human-caused hypoxia. Biogeosciences 7(2), 585-619.
| Crossref | Google Scholar |
Reid AJ, Carlson AK, Creed IF, Eliason EJ, Gell PA, Johnson PTJ, Kidd KA, MacCormack TJ, Olden JD, Ormerod SJ, Smol JP, Taylor WW, Tockner K, Vermaire JC, Dudgeon D, Cooke SJ (2019) Emerging threats and persistent conservation challenges for freshwater biodiversity. Biological Reviews 94(3), 849-873.
| Crossref | Google Scholar |
Rosenberger AE, Dunham JB, Neuswanger JR, Railsback SF (2015) Legacy effects of wildfire on stream thermal regimes and rainbow trout ecology: an integrated analysis of observation and individual-based models. Freshwater Science 34(4), 1571-1584.
| Crossref | Google Scholar |
Rural Fire Service (2020) Bushfire Bulletin. Journal of the NSW Rural Fire Service 42(1), 1-60.
| Google Scholar |
Ryan KL, Hall NG, Lai EK, Smallwood CB, Tate A, Taylor SM, Wise BS (2019) State-wide survey of boat-based recreational fishing in Western Australia 2017/18. Fisheries Research Division, Department of Primary Industries and Regional Development (Government of Western Australia), Perth, WA, Australia.
Ryan KL, Desfosses CJ, Denham AM, Taylor SM, Jackson G (2021) Initial insights on the impact of COVID-19 on boat-based recreational fishing in Western Australia. Marine Policy 132, 104646.
| Crossref | Google Scholar |
Sainsbury NC, Genner MJ, Saville GR, Pinnegar JK, O’Neill CK, Simpson SD, Turner RA (2018) Changing storminess and global capture fisheries. Nature Climate Change 8(8), 655-659.
| Crossref | Google Scholar |
Scott M, Lennon M, Tubridy F, Marchman P, Siders AR, Main KL, Herrmann V, Butler D, Frank K, Bosomworth K, Blanchi R, Johnson C (2020) Climate disruption and planning: resistance or retreat? Planning Theory & Practice 21(1), 125-154.
| Crossref | Google Scholar |
Sheldon F, Barma D, Baumgartner LJ, Bond N, Mitrovic SM, Vertessy R (2022) Assessment of the causes and solutions to the significant 2018–19 fish deaths in the Lower Darling River, New South Wales, Australia. Marine and Freshwater Research 73(2), 147-158.
| Crossref | Google Scholar |
Silva LGM, Doyle KE, Duffy D, Humphries P, Horta A, Baumgartner LJ (2020) Mortality events resulting from Australia’s catastrophic fires threaten aquatic biota. Global Change Biology 26(10), 5345-5350.
| Crossref | Google Scholar |
Stocks JR, Ellis IM, van der Meulen DE, Doyle JI, Cheshire KJM (2022) Kills in the Darling: assessing the impact of the 2018–20 mass fish kills on the fish communities of the Lower Darling–Baaka River, a large lowland river of south-eastern Australia. Marine and Freshwater Research 73(2), 159-177.
| Crossref | Google Scholar |
Storen R, Corrigan N (2020) COVID-19: a chronology of state and territory government announcements (up until June 2020). Research Paper Series, 2020–21. (Parliament of Australia, Department of Parliamentary Services) Available at https://parlinfo.aph.gov.au/parlInfo/download/library/prspub/7614514/upload_binary/7614514.pdf
Talbot CJ, Bennett EM, Cassell K, Hanes DM, Minor EC, Paerl H, Raymond PA, Vargas R, Vidon PG, Wollheim W, Xenopoulos MA (2018) The impact of flooding on aquatic ecosystem services. Biogeochemistry 141(3), 439-461.
| Crossref | Google Scholar |
Taylor SM, Ryan KL (2020) Concurrent Western Australian telephone surveys highlight the advantages of sampling from a registry of recreational fishers. ICES Journal of Marine Science 77(6), 2181-2191.
| Crossref | Google Scholar |
Taylor MD, Suthers IM (2021) The socio-ecological system of urban fisheries in estuaries. Estuaries and Coasts 44(7), 1744-1751.
| Crossref | Google Scholar |
Underwood AJ (1992) Beyond BACI: the detection of environmental impacts on populations in the real, but variable, world. Journal of Experimental Marine Biology and Ecology 161(2), 145-178.
| Crossref | Google Scholar |
van Putten IE, Jennings S, Hobday AJ, Bustamante RH, Dutra LXC, Frusher S, Fulton EA, Haward M, Plagányi É, Thomas L, Pecl G (2017) Recreational fishing in a time of rapid ocean change. Marine Policy 76, 169-177.
| Crossref | Google Scholar |
Verkaik I, Rieradevall M, Cooper SD, Melack JM, Dudley TL, Prat N (2013) Fire as a disturbance in mediterranean climate streams. Hydrobiologia 719(1), 353-382.
| Crossref | Google Scholar |
Wang S, Liu Y, Hu T (2020) Examining the change of human mobility adherent to social restriction policies and its effect on COVID-19 cases in Australia. International Journal of Environmental Research and Public Health 17(21), 7930.
| Crossref | Google Scholar |
Zampatti BP, Fanson BG, Baumgartner LJ, Butler GL, Brooks SG, Crook DA, Doyle K, King AJ, Koster WM, Maas R, Sadekov A, Scott P, Strawbridge A, Thiem JD, Tonkin Z, Wilson PJ, Woodhead J, Woods R (2022) Population demographics of golden perch (Macquaria ambigua) in the Darling River prior to a major fish kill: a guide for rehabilitation. Marine and Freshwater Research 73(2), 223-236.
| Crossref | Google Scholar |
