The impact of a climate dryness on multiscale biodiversity of freshwater macroinvertebrates in wetlands on a salinized landscape

Sean Thomas Atkinson

Bachelor of Science, Environmental Science

Supervisors: Assoc. Professor Belinda J. Robson, Dr. Jane M. Chambers

Environmental and Conservation Sciences

Murdoch University

Submitted May 2019

Salt (not ice) in a Wheatbelt wetland (source: Nicole Carey, 2018)

Declaration

I declare this thesis is my own account of my research and contains as its main content, work which has not been previously submitted for a degree at any tertiary education institution.

Sean Atkinson

Signed: ______Date: 20th May 2019

Abstract Across the globe, Mediterranean climatic regions are shifting to more arid climatic conditions. Climate change affects wetland water regimes through increasing temperatures, decreasing rainfall volumes and timing, changing regional wind patterns and increased evaporation rates. Invertebrates that rely on wetlands risk local extinction unless they have adaptations that can withstand prolonged periods of desiccation. Consequently, prolonged drying, and its effects on physicochemical conditions has the potential to reduce wetland biodiversity. In particular, dryland salinisation will exacerbate salinisation of wetlands. In this study, my aims were to: 1) Determine whether wetlands in the Western Australian Wheatbelt and Great Southern regions showed impacts of climatic drying on wetland water regime and water quality between 1998 and 2011; 2) Determine whether the alpha (local), beta (between wetlands) and gamma (regional) diversity of wetland invertebrates changed over this 13 year period as climatic drying progressed; and 3) Characterize the distribution of aquatic macrophyte assemblages in these wetlands and associate these with patterns in dormant invertebrate assemblages. Aquatic invertebrates and water quality parameters were collected from 17 wetlands in the Wheatbelt and Great Southern regions of Western Australia between 1998 and 2011. Multivariate statistical analyses were used to identify changes in alpha, beta and gamma aquatic invertebrate diversity, and examine patterns in water quality data from 1998 to 2011. Sediment was collected from 12 wetlands and flooded for two months to record emergent invertebrates and germinating macrophytes. Climatic drying caused the 17 wetlands to decline in depth and frequency of dry periods increased. Gamma and alpha richness declined across time, but beta diversity (among wetlands) remained consistently high as each wetland retained a distinct fauna. Salinity and average rainfall partially explained invertebrate richness and assemblage composition in wetlands. The inundation experiment showed few germinating macrophytes or hatching invertebrates: assemblages were too depauperate to establish relationships with other variables. Results support the conclusion that Wheatbelt and Great Southern region wetlands experienced changes in aquatic invertebrate assemblages due to drying water regimes. Western Australia is in an advanced state of climate drying compared to other

Mediterranean regions. The results of this study will inform other Mediterranean regions of the biodiversity outcomes of long-term dryness in wetlands with distinct fauna.

Contents Abstract ...... 3 Introduction ...... 5 Methods ...... 11 Site description ...... 11 Field methods and data preparation ...... 13 Historical data analysis...... 14 Germination Experiment ...... 21 Results ...... 23 Historical data analysis...... 23 Physical variables related to wetland drying ...... 23 Aquatic invertebrate diversity ...... 25 The relationship between macrophytes, algae and aquatic invertebrates ...... 44 Discussion...... 48 Conclusions ...... 57 Acknowledgements ...... 58 References ...... 59 Appendices ...... 73

Introduction Climate drying alters wetland hydrology and water quality In Mediterranean climatic regions, increased aridity brought on by climate change has placed wetland ecosystems at risk of long-term alteration (Barron et al., 2012; Finlayson et al., 2013). Changes in the frequency, depth, and length of inundation initiate a series of interconnected changes to environmental variables governing water quality and habitat suitability, resulting in a syndrome of multiple-stressors on ecosystems (Adams, 2005; Davis et al., 2010). Gradual declines in precipitation have been an ongoing issue since the mid 1970’s in Mediterranean climates across the globe, including California, the Iberian Peninsula, and Western Australia (Cai & Cowan, 2006; Deitch et al., 2017). Shallow open wetlands are naturally exposed to high daily temperature fluctuations (Hamilton, 2010), which may be compounded by an average increase in air temperature of 0.6° C over the past 40 years, inducing higher evaporation rates (Bates et al., 2008b). Temperature differentials between land and wetland surfaces increase wind speeds, further increasing evaporation rates (Yu, 2007). In turn, increased evaporation rates reduce wetland depth, increasing the direct impact of wind. Shallow lakes, such as those typical of inland wetlands of south Western Australia, are susceptible to sediment resuspension due to wind induced wave action, thereby reducing light penetration into the water column (Davis et al., 2010). As a result of all these changes, wetlands become shallower, warmer, more turbid and dry out for longer periods.

Changes in water regime lead to changes in several water quality variables. Reduced rainfall, a result of climate change, will exacerbate dryland salinisation. Dryland salinisation is the result of rising groundwater bringing ions stored in the soil to the surface after deep rooted native vegetation has been cleared for agricultural purposes, and is particularly impactful on groundwater fed wetlands (Pinder, et al., 2000; Pinder, et al., 2005; Canedo-Arguelles, et al., 2013). Increased salinity is strongly linked to changes in water regime through evapoconcentration. (McFarlane & Williamson, 2002; Strehlow et al., 2005; Robertson et al., 2010). Macronutrients such as nitrogen and phosphorus increase through evapoconcentration and are also released when sediments are re-suspended by wind (Cózar et al., 2005; De Vicente et al., 2006). Algal biomass may increase because of this increased availability of

macronutrients (McDougall & Ho, 1991; Rooney & Kalff, 2000; Ouni et al., 2019) and may in turn lead to the nocturnal depletion of dissolved oxygen (Hamilton, 2010). Acidity and Alkalinity may be increased by climatic drying through evapoconcentration (Zalizniak et al., 2009), or acidification through exposure of acid sulphate soils to aeration (Fitzpatrick & Shand, 2008). In turn, these changes may affect the diversity of wetland biota (Figure 1).

Figure 1: Flow diagram showing how climate drying affects wetland water regimes, water quality and habitat connectivity and ultimately, biodiversity. Red boxes indicate factors of drier water regimes that contribute to changes in water quality and reduced habitat connectivity. Modified from Boulton, et al. ( 2014) Direct and indirect Impact of changes in hydrology on invertebrates and macrophytes Climatic drying will have a large direct impact on invertebrate diversity at all scales, influenced by the life history and desiccation-response strategies of different invertebrate species. In many invertebrate species, desiccation resistant life stages enable survival through dry periods, thereby maintaining within-wetland diversity (Brock et al., 2003). Regional diversity is maintained through habitat connectivity. Invertebrates with non-aquatic life stages use temporary wetlands interspersed between perennial waterbodies as stepping stones during wet periods, providing avenues for dispersal. (Robson & Clay, 2005; Boix et al., 2016). Some species of Odonata are able to disperse across enormous distances under the right atmospheric conditions (Anderson, 2009) but more commonly stay close to their natal wetland (McPeek,

1989). Other flying invertebrates, like mosquitoes (Culicidae), will disperse between adjacent wetlands in an effort to find ideal aquatic environments, but only across relatively short distances (Service, 1997). Passive dispersal strategies, such as transport by water birds, terrestrial animals, or via wind, also occur (Vanschoenwinkel et al., 2008; van Leeuwen et al., 2013). Increased distance between wetlands caused by drying out of linking wetlands may make passive dispersal less viable (Bohonak & Jenkins, 2003; Allen, 2007). Increased wetland isolation as a result of climatic drying may therefore lead to greater beta (among wetland) diversity but may ultimately decrease regional (gamma) diversity (Halse & Storey, 1996; Davis & Christidis, 1997; Pinder et al., 2002; Benier & Horwitz, 2003).

Changes in water regime pose the greatest threat to wetland ecosystems, as hydrology is the single most important determinant of wetland processes (Mitsch & Gosselink, 2007). Shorter periods of inundation reduce the chance of population recruitment and expose aquatic organisms to harsher environmental conditions (Brooks, 2000). For example, reductions in frequency and duration of wetland inundation led to a decline in invertebrate richness in wetlands along the Eastern Paroo River in New South Wales (Timms, 1998), and decreased frequency and volume of inundation in ephemeral Western Australian wetlands is associated with reduced macrophyte richness (Brock, 2011).

With prolonged dry periods, wetlands will become more isolated, leading to increased habitat fragmentation which decreases the chances of successful dispersal among wetlands for aquatic species (Woodward et al., 2010). When declining water tables drop below a certain level, permanent wetlands become seasonal. Such extended periods of drying are associated with reduced aquatic plant richness. For example, decreases in inundation across consecutive years in Florida wetlands caused a shift from water plant communities dominated by spikerush (Eleocharis elongata) to those dominated by the sedge Cladium jamaicense (Zweig & Kitchens, 2009). Under such circumstances, permanent shifts from one ecosystem type to another are possible (Sim et al., 2013; Boulton et al., 2014). Macrophytes are thus highly susceptible to changes in wetland hydrology.

The loss of macrophytes due to climatic drying indirectly impacts invertebrates. Denser and more structurally complex macrophyte assemblages are associated with higher aquatic invertebrate diversity and abundance (Tews et al., 2004; Anderson et al., 2011; St. Pierre & Kovalenko, 2014). Therefore, water regime changes that affect macrophyte assemblages also affect invertebrate assemblages (Sim et al., 2013; Carey et al., 2018)

Wetland invertebrates may often show desiccation-resistance, at least in one life stage (Sim et al., 2013; Strachan et al., 2014). Alternatively, refuges from desiccation can be found within wetland sediment (Strachan et al., 2014). Cracks, micro-fissures and depressions in standing wetlands may also provide protection from desiccation, although they may be vulnerable to prolonged drying. For example, adult Heterocypris bosniaca (ostracods) retreat into muddy sediment to survive through dry seasons in Iberian rockpools (Aguilar-Alberola & Mesquita- Joanes, 2011) and several species of southwestern Australian ostracod adults are capable of dormancy in sediments (Strachan et al., 2014). Longer dry periods may lead to longer periods of vulnerability to predation for dormant invertebrates and those in refuges, shorter inundation periods will mean insufficient time to reach breeding or dispersal life stages (Robson et al., 2013b; Strachan et al., 2014). Also, for invertebrate species that rely on environmental cues for their hatching and metamorphosis, changes in water regime could disturb their life cycle, causing hatching or metamorphosis at inopportune times (Wiggins, 1980; Hairston & Kearns, 2002; Strachan et al., 2016a). Western Australian wetland invertebrate communities show short term resilience to altered water regimes (Sim et al., 2013). However, longer periods of dryness coupled with shorter and less predictable periods of inundation may expend invertebrate egg banks, decreasing wetland invertebrate diversity (Strachan et al., 2016a). Thus, changes in wetland hydrology due to climatic dryness may impact invertebrate assemblages in a variety of ways.

Impact of drying-induced changes in salinity, temperature and macronutrients on invertebrates and macrophytes Drier wetland hydrology is accompanied by increased salinity (Davis et al., 2003). Most macrophytes are unable to tolerate salinities above 10-15 gL-1 total dissolved salts (Davis et al., 2003). Beyond this, only a few widely distributed species of Ruppia, Althenia (was Lepilaena),

and salinity obligates such as Halobactium sp. and charophytes persist (Brock, 1981). Some of these plant species (e.g. Ruppia polycarpa) also show a decline in average condition and biomass of plants as salinity increases (Sim et al., 2006a).

Fresher wetlands support greater invertebrate richness than saline wetlands. Australian aquatic insects are often intolerant of salinities higher than 5 gL-1 and, as most wetland assemblages are insect-dominated, those salinities alter invertebrate biodiversity so that faunas become dominated by halotolerant Crustacea (Pinder et al., 2002). Increased salinity driven by climate drying could cause a shift in invertebrate community structure towards domination by halophilic species. Pinder et al. (2002) collected invertebrates from 230 wetlands across the Western Australian wheatbelt, showing that there is a significant drop in species richness in wetlands with salinities higher than 0.03 gL-1. Some invertebrate species can tolerate and even benefit from small increases in sub-lethal salinity levels. For example, the Common Bluetail damselfly (Ischnura heterosticta) undergoes eclosion at a faster rate in salinities between 2.5 and 12 gL-1, than at salinities below 2.5 gL-1 (Kefford et al., 2006). This is rare though, as other species of wetland invertebrates suffer osmotic stress from small increases in salinity. Species such as mayflies and freshwater snails cannot survive small changes in salinity (Kefford & Nugegoda, 2005; Kefford, 2019).

Invertebrates will be exposed to increased water temperature and light through loss of inundation and extended periods of shallowness. This has the potential to drastically alter wetland invertebrate diversity, as some taxa cope better with higher water temperatures than others (Stewart et al., 2013). Numerous studies have investigated the upper thermal tolerances of wetland invertebrate families. Garten & Gentry (1976) found that some North American dragonfly nymphs were able to acclimatize to temperatures of over 40oC. Calosi et al. (2008) found that the European Brown Diving Beetles (Agabus brunneus) were able to cope with temperatures of up to 46oC. In contrast, Stewart et al. (2013) found two south western Australian mayfly species, Offadens soror and Nyungara bunni, had a 50% mortality rate at temperatures of 20.5oC and 21.9oC respectively. Other key invertebrate groups such as earthworms, stoneflies and true flies show upper thermal tolerances between these two extremes (Ernst et al., 1984; Quinn et al., 1994; McKie et al., 2004). Increased exposure to

higher temperatures due to climatic drying may restrict aquatic invertebrate richness to those taxa with higher thermal tolerances.

Changes in hydrology due to climatic dryness can contribute to wetland eutrophication. Upon rewetting, nitrogen and phosphorus stored in the sediment are released into the water column, creating ideal conditions for algal and cyanobacterial blooms that may take up the nutrients quickly (Boers, 1986; Thullen et al., 2008; Smith & Jacinthe, 2014). What may result is an ecosystem dominated by algae and cyanobacteria for short intense periods, rather than one dominated by macrophytes absorbing (and storing) nutrients at a steady pace over longer periods of time. Furthermore, algae and cyanobacteria suspended in the water column reduce the amount of light reaching the sediment, thus reducing the chance for successful macrophyte germination (Anderson et al., 2002; McDougall & Ho, 1991).

The importance of studying alpha, beta and gamma diversity together Alpha diversity is the richness of species at a single location, for example, a single wetland (Whittaker, 1960). Beta diversity is the change in assemblage composition between locations. Two definitions of beta diversity are used in the present study as described by Tuomisto (Tuomisto 2010a; Tuomisto 2010b). Turnover measures changes from one location to another within a region, while variation changes along an environmental, temporal or spatial gradient, in this case, over a period of time. Gamma diversity is the diversity within an entire region, composed of multiple locations (Whittaker, 1960). Gamma and alpha diversity are connected through beta diversity and beta diversity allows us to describe regional diversity with higher resolution. For example, in the context of this study, high gamma diversity may occur in a region with species rich wetlands that have similar assemblages (low beta diversity) or high gamma diversity may result from the summation of species lists from many depauperate wetlands, each having distinct invertebrate assemblages (high beta diversity). Although both scenarios could deliver high gamma diversity, they require very different management. In the first scenario, diversity in the region is highly stable: any change in diversity at an individual wetland will not change gamma diversity. Furthermore, recruitment from other wetlands in the region may allow an individual wetland to recover, if connectivity is sufficient. In the second scenario, the loss of diversity at a single wetland reduces the region’s gamma diversity. Unique

species lost from an individual wetland could be lost forever from that region (Anderson et al., 2011; Tuomisto, 2010a; Tuomisto, 2010b; Vellend, 2001). It is therefore important to quantify patterns of change at all three scales of diversity, simultaneously, when landscape-scale environmental change occurs.

Significance and Aims South-western Australia is in an advanced state of climate drying compared with other Mediterranean regions (Charles, 2010; Deitch et al., 2017). It is therefore ideal for examining the effects of prolonged drying on wetland invertebrates and macrophytes. With this study, I had the opportunity to analyze data from long term monitoring of biotic and abiotic wetland variables at a large geographical scale. Consequently, this study has a larger temporal scale than many other studies of its kind (Brooks, 2000; Halse et al., 2002; Pinder et al., 2002; Serrano & Fahd, 2005; Lyons et al., 2007). Long-term datasets are rare and can provide valuable insight into responses by aquatic invertebrate assemblages in regions facing climate dryness. The large geographic scale of the dataset enables analysis of diversity at multiple scales (i.e. alpha, beta, gamma).

The aims of this study were to: (1) determine whether wetlands in the Western Australian Wheatbelt and Great Southern regions showed increased frequency of drying and altered water quality during the 13 years between 1998 and 2011 (2) determine whether the alpha, beta and gamma diversity of aquatic invertebrates changed over the same time period and (3) characterize the distribution of aquatic macrophyte assemblages in these wetlands and determine whether they are associated with water regime and patterns in dormant invertebrate assemblages.

Methods

Site description The wetlands in this study are located in the Wheatbelt and Great Southern regions, an area covering approximately 194,000 km2 of south west Western Australia (Figure 2) (Department of Primary Industries and Regional Development, 2018). The region has a strong rainfall gradient (300-700 mm of rainfall per annum), with areas in the south and west receiving more rainfall

than those in the north and east. Rainfall has been declining since the mid-1970’s (Bureau of Meteorology, 2019a; Bureau of Meteorology, 2019b) with a decline in rainfall of 15% and a decline in runoff of 55% since 1975 (Bates et al., 2008b). Although some wetlands in this region are naturally saline, other wetlands have been subjected to secondary salinization, acidification, and groundwater rise since at least the mid-20th century, chiefly due to clearing of land for agricultural purposes (Commander, et al., 1994; Department of Agriculture and Food, 2013).

The 17 wetlands in this study (Table 1) are a sub-set of 25 wetlands chosen for study in 1997 by the Department of Conservation and Land Management to inform the Western Australian Salinity Action Plan (Cale et al., 2004). The remaining eight wetlands were removed as identification of invertebrate taxa was incomplete, so data were not suitable for analysis

Table 1: Wetland name, location (latitude, longitude), water regime, salinity category and range, and pH range of the 17 wetlands in this study. Water regime (1) and salinity type (2) are those recorded prior to sampling by Cale et al. (2004). (*) Lake Altham was only inundated once so there was a single salinity and pH level recorded.

Wetland Name Latitude Longitude Water Regime1 Salinity Category2 Salinity Range (μS cm-1) pH range

Lake Bryde 33º 21'03" S 118º 49' 36" E Ephemeral Primary 9 560 - 56 450 7.90 - 10.03 Lake Logue 29º 50'54" S 115º 08' 15" E Seasonal Primary Coastal 1 929 - 34 500 7.83 - 9.15 Lake Coyrecup 33º 42' 31" S 117º 50' 01" E Seasonal Secondary 8 355 - 125 600 7.60 - 9.51 Lake Wheatfield 33º 48' 28" S 121º 55' 24" E Perrenial Primary coastal 9 050 - 12 560 7.76 - 9.35 Lake Altham 33º 24' 01" S 118º 26' 35" E Ephemeral Primary 140 800* 7.87* Noobijup Swamp 34º 24' 01" S 116º 47' 17" E Seasonal Fresh 2 832 - 9 045 4.54 - 7.95 Lake Bennetts 33º 16' 40" S 119º 36' 28" E Ephemeral Primary 11 205 - 114 750 8.02 - 9.90 Lake Ardath 32º 05' 51" S 118º 09' 16" E Seasonal Primary 43 300 - 82 400 3.86 - 7.48 Kulicup Swamp 33º 49' 28" S 116º 40' 13" E Seasonal Fresh 642 - 845 7.53 - 8.31 Lake Campion 31º 05'23" S 118º 16' 14" E Ephemeral Primary 173 400 - 242 000 2.94 - 3.85 Goonaping Swamp 32º 08' 59" S 116º 35' 49" E Seasonal Fresh 190 - 483 6.54 - 8.13 Fraser Lake 31º 14' 48" S 117º 04' 02" E Ephemeral Fresh 629 - 2 150 7.63 - 9.86 Paperbark Swamp 32º 24' 52" S 118º 05' 56" E Ephemeral Fresh 200 - 588 6.85 - 7.73 Lake Dumbleyung 33º 20' 12" S 117º 39' 00" E Ephemeral Primary 35 800 - 221 500 7.36 - 8.34 Yaalup Swamp 33º 44' 55" S 118º 34' 07" E Seasonal Fresh 400 - 4 675 7.21 - 9.21 Lake Pleasant View 34º 49' 30" S 118º 10' 42" E Perrenial Fresh 432 - 1 372 6.18 - 7.75 Lake Ronnerup 33º 14' 59" S 119º 36' 50" E Ephemeral Primary 55 550 - 231 000 7.31 - 9.07

Figure 2. Average annual 1961-1990 isohyet map of south west Western Australia showing the location of the 17 wetlands selected for this study. Modified from Cale et al. (2004). Bryde, Coyrecup, Wheatfield, Paperbark, Dumbleyung, Yaalup, Pleasant View and Ronnerup were sampled in odd years, while Altham, Noobijup, Bennetts, Ardath, Kulicup, Campion and Goonaping were sampled in even years. Fraser and Logue were sampled in 1999, then sampled in even years starting in 2000. Field methods and data preparation A 250 μm mesh pond net was swept vigorously through a number of different invertebrate habitats including the lakebed, open water, woody debris and both emergent and submerged macrophytes, in two 50 metre stretches, totaling a distance of 100 metres per wetland (Cale et al., 2004). Samples were taken in spring and this approach provided a single, very large and representative sample from each wetland at each sampling time and aimed to maximize the

number of species captured (Cale et al., 2004). Invertebrate samples from each wetland were identified to the lowest possible taxonomic level in the laboratory and recorded as presence/absence data. This gives adequate representation to rare but vital taxa and avoids hyper-abundant species from dominating the results and allowed for completion of sampling in a timely fashion (Clarke, 1993). In total, 652 taxa were identified throughout the sampling period. However, 167 taxa were removed from statistical analysis due to possible misidentification or redundancy.

Invertebrate samples and physiochemical variables were collected in spring (late September and early November) every second year, between 1998 and 2011: eight wetlands were sampled in odd years, and the other nine were sampled in even years, in an effort to distribute the cost of sampling across multiple years. Bryde, Coyrecup, Wheatfield, Paperbark, Dumbleyung, Yaalup, Pleasant View and Ronnerup were sampled in odd years, while Altham, Noobijup, Bennetts, Ardath, Kulicup, Campion and Goonaping were sampled in even years. Fraser and Logue were sampled in 1999, then sampled in even years starting in 2000. Both sets were evenly distributed across the landscape to avoid geographic confounding. Prior to analysis, wetlands were grouped in two-year blocks (Appendix 1), hereafter referred to as ‘year-groups’. This was done to ensure that each wetland was represented once per year-group and to ensure that each tested year-group had sufficient data.

Historical data analysis Physical variables This study required the use of more than one measure of wetland dryness to account for the amount of between-wetland variation in the data. High variability is typical of long-term climatic measurements associated with wetland inundation (Allan & Haylock, 1993; Cai & Cowan, 2006; Sivakumar et al., 2014). Average annual rainfall was not correlated with wetland depth gauge and was therefore not used as an indication of climate dryness. Depth gauge readings were converted to a proportional measure of the highest reading recorded during the study at each wetland to rescale depths so that they could be compared (because wetlands varied in depth, Figure 3). Rescaling enabled me to examine the degree of drying in each wetland which would otherwise have been obscured by individual wetland depth-ranges.

Transformation of environmental data such as use of proportional depths and the number of dry samples per year can help reduce variability while maintaining data integrity. (Bureau of Meteorology, 2019c). Several variables were found to be co-linear, were removed from the statistical analyses and are represented by their co-linear variable: bicarbonate was co-linear with alkalinity; total dissolved salts, chloride and sodium were co-linear with field conductivity; and sulphate, potassium and magnesium were co-linear with hardness (Table 2).

Testing for evidence of climate dryness in the historical data A T-test (in SPSS version 24) was used to test for systematic differences between the mean proportional depths in odd and even years before pooling data into bi-annual year groups.

Proportional depths were log10 transformed (following examination of residuals) prior to ANOVA to remove reduce skewness, normality was acceptable. One-way ANOVA (SPSS version

24) was used to determine whether there was a difference in log10 proportional depths among year-groups. Linear regression (SPSS version 24) was used to test the null hypothesis that there was no linear relationship between year-groups and the proportion of dry years.

Gamma diversity Gamma, or regional diversity is here defined as the richness of aquatic invertebrate species summed across all samples across all 17 wetlands. Gamma diversity was analyzed to determine whether the aquatic invertebrate assemblage of the Wheatbelt and Great Southern Regions had changed over time and what part climatic dryness had played in this change. Richness was converted to proportional richness, a proportion of the highest richness at each wetland during the sampling period. Converting to proportional richness allows for direct comparison of richness between wetlands with differing species pools. Richness was log10 transformed to meet the assumptions of ANOVA following examination of residuals; proportional richness did not require transformation. As both proportional depth and the proportion of dry years for each wetland could influence gamma diversity (regional invertebrate richness), proportional richness was pooled across all 17 wetlands within each year-group and plotted against mean proportional depths and the proportion of dry years for each year-group, and analyzed using linear regression (SPSS). Linear regression was also used to test the hypothesis that regional invertebrate richness declined over the time period.

Figure 3: Depth over time of the 17 wetlands included in this study. Each individual wetland has a unique water regime, and it is therefore necessary to normalize depth gauge readings to make wetlands comparable to each other.

Table 2: Physiochemical Properties recorded during sampling in the field and at a later date under laboratory conditions including those that were removed from statistical analysis due to co-linearity. Properties were judged to be colinear when R2 values exceeded 90%.

Physiochemical Property Unit of Measurement Colinear with, and thus removed Correlation (R2)

Depth to Gauge m

Field Conductivity uScm-1

Field pH

Total Filterable Nitrogen ugL-1

Total Filterable Phosphor ugL-1

Temperature °C

Turbidity NTU

Colour CTU

Alkalinity mgL-1

Hardness mgL-1

Silica mgL-1

Calcium mgL-1

Carbonate mgL-1

Bicarbonate mgL-1 Alkalinity 0.972

Total Dissolved Salts gL-1 Field Conductivity 0.957

Chloride mgL-1 Field Conductivity 0.941

Sodium mgL-1 Field Conductivity 0.941

Sulphate mgL-1 Hardness 0.911

Potassium mgL-1 Hardness 0.925

Magnesium mgL-1 Hardness 0.998

Multivariate analyses were conducted in Primer-e v.6. To determine whether there was a difference in aquatic invertebrate gamma diversity across time, I used a non-metric multidimensional scaling (nMDS) ordination based on a Bray-Curtis dissimilarity resemblance matrix to show differences in assemblage composition across year-groups when water was present. Similarity Percentages (SIMPER) analysis was performed to determine which species contributed to differences in assemblage composition within and among year-groups. Aspects of geographic location were examined to determine whether they were associated with patterns in assemblage composition, but no relationships were found (appendix 2) so these analyses are not considered further.

Gamma diversity among year-groups was represented using the PERMDISP function in Primer- E, a technique described by Anderson (2006) and applied in Bini, et al. (2014) and Sarremejane, et al. (2018). PERMDISP measures variance in assemblage composition from the centroid (i.e. multivariate mean). It provides a measure of the distance between the centroid of all the wetlands in a year group and the Bray-Curtis dissimilarity measure for each wetland within the year-group. In this case it provides a measure of gamma diversity, because it is comparing year- groups to each other, and all year-groups contain all 17 wetlands from across the entire study region.

Beta diversity Several tests were used to test the hypothesis that aquatic invertebrate assemblages differed among wetlands. Beta diversity was measured using PERMDISP (based on Bray-Curtis dissimilarity). Individual wetlands were compared to one another within year-groups. nMDS ordination was used to display this variation between wetlands and samples. SIMPER analysis was used to identify which species contributed to the differences between wetlands.

Alpha diversity Wetlands were categorized as having a high, medium or low species richness based on aquatic invertebrate studies carried out in the Wheatbelt and Great Southern regions by Pinder et al. (2000) and Halse et al. (2002): low richness samples had between zero and 15 taxa, medium richness samples had between 16 and 49 taxa and high richness samples hade more than 50

taxa. Two equal time periods were used in this analysis, the first (1998-2004) and last (2005- 2011) halves of the sampling period, to determine whether wetlands had dropped into lower richness categories as the climate grew drier. A 2 x 3 contingency table of the number of wetlands in each richness category in these two time periods was analysed using a chi-square test to test the hypothesis that the number of high, medium and low richness wetlands differed between time periods.

One-way SIMPER analysis was used to identify species contributing to the difference in composition within individual wetlands across all years. Lake Altham was not included in the within-wetland analysis as it was only inundated once. Within-wetland similarity was used to define wetland alpha diversity, with high similarities representing little change over time, and low similarities representing large changes over time. Individual wetlands were described according to their changes in mean depth, mean proportional depth, proportion of dry year groups, mean richness and mean proportional richness.

Relationship between physiochemical variables and invertebrate assemblage composition (all wetlands and year-groups) Principle Component Analysis (PCA) using Euclidean distance was used to identify which environmental variables separated wetlands most strongly. Salinity (as represented by field conductivity), isohyets and proportional depth were chosen for further analyses as they exhibited strong influence on the patterns of wetland sample distributions on the PCA plot. These environmental variables were then divided into categories to better relate ecologically meaningful change in those variables to invertebrate species composition. pH influenced a handful of samples, however further analysis using nMDS ordination revealed no patterns and it was therefore discarded (appendix 3). Salinity was grouped into five categories based on invertebrate community responses to salinity levels from Pinder et al. (2005). Wetlands were divided into six categories based on average annual rainfall isohyets calculated from 1961 to 1990 (Bureau of Meteorology, 2019a). Proportional depths were grouped into four equal categories, together with a 5th group representing maximum inundation during the sampling period (Table 3). The nMDS ordination of invertebrate data for the whole dataset (all wetlands

x year-groups) was labelled by salinity category (see below) and isohyet category to visualize patterns.

Table 3: Table showing the categories of the three wetland environmental variables used to examine patterns in the nMDS ordination.

Salinity Isohyet Proportional Depth

Category Range (mS cm-1) Category Range (mm year-1) Category Range Fresh < 5.558 1 < 300 1 0.00-0.25 Brackish 5.559-17.022 2 300-399 2 0.26-0.50 Sub-saline 17.023-46.248 3 400-499 3 0.51-0.75 saline 46.249-130.084 4 500-599 4 0.76-0.99 Hypersaline > 130.085 5 600-700 5 1.00 6 > 700

The following null hypotheses were tested: 1) there was no difference in invertebrate species composition among wetlands (across all year-groups) or among year-groups (across all wetlands) (two-way crossed ANOSIM); 2) there was no difference in invertebrate species composition among wetlands (one-way ANOSIM); 3) there was no difference in invertebrate species composition among isohyet categories (one-way ANOSIM); 4) there was no difference in invertebrate species composition among salinity categories (one-way ANOSIM). SIMPER analysis was used to identify which species were associated with differences in assemblage composition between wetlands and between wetlands in different salinity and isohyet categories.

Relationship between physiochemical variables and invertebrate assemblage composition (all wetlands and year-groups) Principle Component Analysis (PCA) using Euclidean distance was used to identify which environmental variables separated wetlands most strongly. Salinity (as represented by field conductivity), isohyets and proportional depth were chosen for further analyses as they exhibited strong influence on the patterns of wetland sample distributions on the PCA plot. These environmental variables were then divided into categories to better relate ecologically meaningful change in those variables to invertebrate species composition. pH influenced a handful of samples, however further analysis using nMDS ordination revealed no patterns and it was therefore discarded (appendix 3). Salinity was grouped into five categories based on invertebrate community responses to salinity levels from Pinder et al. (2005). Wetlands were

divided into six categories based on average annual rainfall isohyets calculated from 1961 to 1990 (Bureau of Meteorology, 2019a). Proportional depths were grouped into four equal categories, together with a 5th group representing maximum inundation during the sampling period (Table 3). The nMDS ordination of invertebrate data for the whole dataset (all wetlands x year-groups) was labelled by salinity category (see below) and isohyet category to visualize patterns.

Table 3: Table showing the categories of the three wetland environmental variables used to examine patterns in the nMDS ordination.

Salinity Isohyet Proportional Depth

Category Range (mS cm-1) Category Range (mm year-1) Category Range Fresh < 5.558 1 < 300 1 0.00-0.25 Brackish 5.559-17.022 2 300-399 2 0.26-0.50 Sub-saline 17.023-46.248 3 400-499 3 0.51-0.75 saline 46.249-130.084 4 500-599 4 0.76-0.99 Hypersaline > 130.085 5 600-700 5 1.00 6 > 700

The following null hypotheses were tested: 1) there was no difference in invertebrate species composition among wetlands (across all year-groups) or among year-groups (across all wetlands) (two-way crossed ANOSIM); 2) there was no difference in invertebrate species composition among wetlands (one-way ANOSIM); 3) there was no difference in invertebrate species composition among isohyet categories (one-way ANOSIM); 4) there was no difference in invertebrate species composition among salinity categories (one-way ANOSIM). SIMPER analysis was used to identify which species were associated with differences in assemblage composition between wetlands and between wetlands in different salinity and isohyet categories.

Germination Experiment A subset of 11 representative wetlands were selected from the 17 wetlands to determine if there was a relationship between the plant and invertebrate assemblages that emerged from the seed and egg bank (respectively) in wetland sediment. Wetlands were selected to replicate the broad range of water regimes, salinity, acidity, alkalinity and hardness present in the original 25 wetlands in the historical data, however choice was influenced by timing and resources and incorporated wetlands located on government-controlled land only. Yaalup

Lagoon was inaccessible at the sampling time, so I sampled from an adjacent wetland. This wetland was located approximately 300 metres to the north-east of Yaalup Lagoon which, for the purpose of this study we have named Yaalup Salty (Figure 4). This wetland is only included in the germination experiment, as wetland 26.

Figure 4: Wetland 26, Yaalup Salty, indicated by the red arrow, is located approximately 300 metres to the north-east of Yaalup Lagoon and was chosen for its accessibility and extreme salinity, in contrast with other wetlands in the germination experiment. Sediment was sampled over five days in spring 2018, starting 26th November 2018. Temperature (°C), pH and electrical conductivity (mS cm2 -1) were recorded using a YSI Multiparameter Meter Model 556MPS (YSI) at each wetland. Due to the potentially extreme range of electrical conductivity, the YSI was calibrated to 110 mS cm2 -1 and water samples were diluted with fresh water at a ratio of 2:1. Depth was recorded when the depth gauge was immersed. Two sediment cores were collected from each of five sub-sites at each wetland using a 37 mm diameter corer. Criteria for sub-site selection were evidence of past macrophyte activity (to maximize chances for obtaining propagules) and being at least 20 metres apart. Core

samples were between two and five centimetres deep depending on how deep the core sampler could be driven, as these depths have been recognized as the depth to which most viable macrophyte seeds and invertebrate eggs can be found (Brendonck & De Meester, 2003; Sim et al., 2006b). The two core samples were stored side by side in one litre plastic containers, measuring 75 mm x 170 mm 115 mm, and comprised a single sample for analysis. Live samples of any plant material found on the sediment, whether dry or inundated, were taken and stored in a cooler while in the field. These samples were identified using Sainty & Jacobs (2003), the Western Australian online flora database FloraBase (2018), and with the aid of expert staff at the Western Australian Herbarium.

Sediment samples in their plastic containers were placed uncovered in a glasshouse in a random configuration (Appendix 4), inundated with 900 mL of tap water, monitored on a daily basis and water level was maintained. Photos were taken on a fortnightly basis starting in the second week to allow for sediment to settle after transportation and flooding. The experiment ran for nine weeks through December 2018 and January 2019. Invertebrate samples were taken throughout the experiment, preserved in a 70% ethanol solution and stored at 4° C. Once completed, seedlings, samples of benthic microbial mats and a sample of water were taken from each of the samples and stored in a mixture of 20% Ethanol, 5% Glycerol at 4° C. Algae and cyanobacteria was identified using Entwisle et al. (1997). Seedlings were identified using Sainty and Jacobs (2003). Invertebrate samples were identified using Williams (1980), Davis & Christidis (1997), and Gooderham & Tsyrlin (2002).

Results Historical data analysis Physical variables related to wetland drying No significant difference between the mean proportional depths of wetlands in odd and even years was found (t117 = 0.428, p = 0.670). Wetland proportional depths declined significantly in both odd and even years throughout the sampling period (t60 = 3.042, p = 0.004 and t54 = 3.201, p = 0.002 respectively) with similar but modest correlations; 0.132 and 0.158 (for odd and even years respectively) in both year sets (Figure 5). This means that year-groups were a good

representation of longer-scale temporal change in this dataset, and so were used in subsequent analyses.

Figure 5: Mean proportional depths (+ standard error) of wetlands in odd and even years show poor but similar and significant correlations of R2=0.132 and R2=0.156 respectively.

Mean proportional depths differed significantly among year-groups (F6,119 = 3.326, p = 0.005, Figure 6). Pairwise comparisons between year-groups showed that there were significant differences between the first four year-groups and the final year-group, (p = 0.02 - <0.001, Figure 6) because proportional depths declined over the sampling period.

Using the proportion of dry samples to represent climate dryness over time demonstrated a stronger response. The proportion of dry samples taken during each year-group increased over time (t6 = 4.667, p = 0.005) and the correlation between proportion of dry samples and year- groups was strong (R2 = 0.813, Figure 7). The drop in mean proportional depth described above corresponds to an increase in the proportion of dry samples as time progressed.

Figure 6: Mean Proportional depth for each year-group (±1 standard error). Pairwise comparisons showed that the first six year- groups were not significantly different from each other (a) and the last three year-groups were not significantly different from each other (b).

Figure 7: Linear regression of the significant correlation between Year-group and the proportion of dry samples and each year- 2 groups showed (R =0.813, t6=4.667, p=0.005). Aquatic invertebrate diversity Gamma Diversity Regional aquatic invertebrate richness in the 17 wetlands declined considerably from 1998-

2 2011 (R = -0.917, t6 = -7.454, p = 0.001, Figure 8). Pooled regional richness declined steadily

from 323 species in the first year-group (1998-1999) (Appendix 5) to 118 species in the final year-group (2010-2011) (Appendix 6); more than half of the species pool was lost from the wetlands over this time period.

Figure 8: Linear regression showing a strongly negative relationship between pooled invertebrate richness and year-groups (R2 = 0.917, t6 = -7.454, p = 0.001). Regional invertebrate richness was highly correlated with the proportion of dry sampling

2 instances within a year-group (R = 0.969 t6 = -12.507 p < 0.0005, Figure 9). Less than a third of all wetlands, five out of 17, contained water and were sampled in 2010-2011, compared with the 1998-1999 year-group when only one dry wetland was recorded. Although 2004-2005 contained more dry sampling instances than 2002-2003, this time period was wetter on average as indicated by mean proportional depths (Figure 9). Even so, regional richness did not recover beyond that shown in 2002-2003. Therefore, declining proportional depth and an increase in the number of dry wetlands in the sample over time was associated with reduced regional richness.

Figure 9: Pooled regional invertebrate richness plotted against the proportion of dry year-group showed very high and very 2 significant correlation (R = 0.969 t6 = -12.507 p < 0.0005).

Figure 10: Column graph showing mean richness per wetland over time (±1 standard error). Lettering indicates year-groups that were not significantly different from pairwise comparisons (a, b, c). Pairwise comparisons showed that there were significant differences between the first year-group and the last three year-groups as well as the third and seventh year-groups (p = 0.010, p = 0.018, p = 0.009 respectively). There were also significant differences between the second and seventh year-groups as well as the third and seventh year-groups (p = 0.002 and 0.005 respectively).

Mean taxa richness (per wetland) differed among year-groups (F6,119 = 3.779, p = 0.002) showing a transition across time from higher mean richness at the beginning of the time period to lower

mean richness at the end (Figure 10). Mean proportional richness (per wetland) also differed between year-groups (F6,119 = 6.488, p <0.001) with four time periods (a, b, c, d) showing a transition from high to low mean proportional richness across time (Figure 11).

Figure 11: Mean proportional richness per wetland over time (±1 standard error). Lettering indicates year-groups that were not significantly different from pairwise comparisons (a, b, c, d). The results indicate a transition across time from higher mean proportional richness at the beginning of the time period to lower mean proportional richness at the end. When pooled by year-groups, regional invertebrate richness was weakly but significantly

2 correlated with proportional depth (R = 0.124, F6,119 = 4.072, p < 0.0005). Three groups emerged (Figure 12): in the years 1998 to 2003 pooled regional invertebrate richness was highest, but mean proportional depth dropped in 2002-03. Richness then dropped, and remained similar from 2004 to 2009, although mean proportional depth continued to decline. By 2010-11, both richness and depth were at their lowest point. 2010-11 was the driest year on record in southwestern Australia (Bureau of Meteorology, 2013), was the least taxa rich and variance for this year-group was nearly half that of any other year-group.

Figure 12: Pooled regional invertebrate richness was significantly but modestly correlated with the mean proportional depth 2 (±1 standard error) per year-group. (R = 0.124, F6,119 = 4.072, p < 0.0005). Beta diversity High beta diversity (taxonomic distinctness) among wetlands obscured differences in gamma diversity across time in the multivariate analyses. Although there were no consistent differences among year-groups (across all wetlands) (R = 0.057, p = 0.159), wetlands differed strongly (across all year-groups) in their assemblage composition (R = 0.59, p = 0.001). An nMDS ordination further illustrates the absence of clustering of year-groups (Figure 13) but shows strong clustering of samples by wetland (Figure 14). Multivariate dispersion did not differ between year groups (F6,73 = 0.5523, p = 0.833) indicating that variation in invertebrate assemblages across all 17 wetlands did not change consistently between 1998-2011, even though gamma diversity declined.

Wetland invertebrate richness differed significantly across all year groups (F16,63 = 6.283, p = 0.001) with more saline wetlands showing greater temporal variation than fresher wetlands (Figure 14). Some wetlands such as Goonaping Swamp, Kulicup Swamp and Lake Pleasant View differed little over the sampling period relative to other wetlands in the dataset, such as Lake

Campion and Lake Ronnerup whose taxonomic compositions tended to be quite dissimilar between year-groups.

There was a moderate but significant correlation between the mean proportional depth of a wetland over the entire period and the mean proportional richness of that wetland (R2 = 0.425, t14 = 3.217, p = 0.006, Figure 15). Wetlands in the study such as Lake Wheatfield and Lake Pleasant View, that maintained a high proportion of their maximum depth or were not often dry retained a higher proportional taxa richness in their aquatic invertebrate communities (Figure 14). The pattern of distribution of wetlands along the regression line in Figure 15 shows that more ephemeral fresh wetlands such as Yaalup Lagoon, Paperbark Swamp and Fraser Lake displayed similar responses to ephemeral saline and hypersaline wetlands such as Lake Coyrecup and Campion in proportional invertebrate richness (Figure 15). This indicates that drying affected all assemblages regardless of salinity category.

Figure 13: Two Dimensional nMDS ordination plot using Bray Curtis dissimilarity of all samples across all 17 wetlands. Samples are represented by the year-group in which they were sampled (Stress = 0.14). When mean richness was plotted instead against mean proportional depth it showed a similar

2 correlation (R =0.498, t14=3.728, p=0.002, Figure 16). Wetlands that maintained depths closer to their maximum showed higher mean invertebrate richness. However, for mean richness, wetlands were arranged along the regression line in order of decreasing salinity (Figure 16). More saline wetlands showed lower mean richness than did fresher wetlands regardless of

their mean proportional depth. Lake Ardath was an outlier (Figure 16) probably because the invertebrate community was already limited by low pH (pH ~4).

Figure 14: Two Dimensional nMDS ordination plot using Bray Curtis Dissimilarity of the 17 wetlands representing all sampling instances in which water was present and thus aquatic invertebrates were present in the wetland. (stress = 0.14).

Figure 15: Scatterplot of the mean proportional richness of each of the 17 wetlands by mean proportional depths of each wetland (R2=0.425) (±1 standard error). Wetlands are colour coded by salinity category as described in Table 3. Wetlands for which all sampling instances were within one salinity category are represented by a circle. Those wetlands that span more than one salinity are represented by a triangle and by the colour of the maximum salinity category reached in the historical data.

Figure 16: Scatterplot of the mean richness of each of the 17 wetlands by mean proportional depths of each wetland (R2=0.498) (±1 standard error). Wetlands are colour coded by salinity category as described in Table 3. Wetlands for which all sampling instances were within one salinity category are represented by a circle. Those wetlands that span more than one salinity are represented by a triangle and by the colour of the maximum salinity category reached in the historical data.

Relationships between physiochemical variables and invertebrate assemblage composition Pairwise comparisons showed no clear pattern in dissimilarities among salinity categories. Therefore, the strongest pattern in the invertebrate dataset (across all times and wetlands) was that each wetland showed a fauna distinct from any other wetland. Geographic distance between wetlands alone did not appear to be a factor in dissimilarity in assemblage composition between wetlands. For example, Bennett’s Lake and Lake Ronnerup are less than two kilometres apart had an average dissimilarity 83.61%, while Noobijup swamp and Fraser Lake had an average dissimilarity of 85.1% and are 350 kilometres apart.

Depth and field conductivity showed strong opposing effects on water quality variance in all wetlands (Figure 17), with axis 1 (the horizontal axis) accounting for 26.4% of the variation among samples. Paperbark Swamp which, while fresh, appeared to be strongly influenced by total phosphorus and by an atypically high silica concentration of 240 mgL-1 in 2005 (Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand, 2000)

Figure 17: Principle component analysis using Euclidean Distance of measured field and laboratory physiochemical properties of the 17 wetlands. Sampling instances are colour coded by Wetland. Principle component axis 1 (the horizontal axis) explained 26.4% of the variation in samples, while principle component 2 (the vertical axis) explained 18.6% of the variation.

When grouped according to isohyets (based on mean annual rainfall 1961-1990), wetlands that received higher annual rainfall tended to have higher taxa richness than wetlands that received less rainfall (Figure 18). Wetland invertebrate assemblages were significantly different among isohyet categories (R = 0.444, p = 0.001). Only one pairwise comparison between isohyets was not significantly different (Table 5): Group 2 (300-400 mm) and Group 4 (500- 600mm) overlapped because these groups were large and invertebrate assemblages were very variable within them (Figure 19). Wetlands in the two wettest locations (>600 mm pa, Goonaping Swamp, Kulicup Swamp and Noobijup Swamp) maintained distinct invertebrate assemblages that showed little temporal variation relative to wetlands in areas receiving less rainfall (Figure 19). SIMPER results indicated that similarities within isohyets increased from 6.36 in the lowest rainfall zone, to > 44.24 in areas receiving 600 mm rainfall per annum.

Figure 18: Mean invertebrate richness across all samples (±1 standard error), categorized by isohyet (see Figure 2, as described in Table 3) including samples from dry wetlands. Number of wetlands (n) in each isohyet displayed above each bar.

Figure 19: nMDS ordination plot using Bray Curtis Dissimilarity of invertebrate assemblages in all 17 wetlands coded according to isohyet category; 1: <300 mm pa, 2: 300-400 mm pa, 3: 400-500 mm pa, 4: 500-600 mm pa, 5: 600-700 mm pa, 6: >700 mm pa (Stress=0.14). Wetlands receiving more rainfall have more stable invertebrate assemblages and are less variable through time than those receiving less rainfall.

Salinity, as represented by field conductivity in this study, showed the strongest association with invertebrate diversity of all environmental variables. Differences in invertebrate assemblages between salinity categories (Table 3), were large and highly significant (R = 0.727, p = 0.001) (Table 5). Fresher wetlands such as Lake Pleasant View, Goonaping Swamp and Kulicup Swamp tended to have stable

invertebrate assemblages, changing little over the sampling period. Whereas more saline wetlands such as Lake Dumbleyung, Lake Ronnerup and especially Lake Campion, tended to have much more temporally variable invertebrate assemblages (as shown by the wide spread of points in Figure 20). Richness and species turnover both play a role in the differences among salinity categories. All salinity groups had low within-group similarities: groups 1 -4 had 28.22-36.44% similarity while Group 5, (hypersaline wetlands), had an average similarity of only 11.83%. Only seven species made up 90% of the contributions to similarity in Group 5 showing the low taxa richness in these wetlands, where the fairy shrimp Parartemia longicaudata accounted for more than 41% of the similarity. Group 1 by comparison had 106 species contributing to 90% of the average similarity with no one species contributing more than 4.32%. Richness dropped rapidly across salinity categories from, on average, 59.34 species in the fresh wetlands to 18.83 species on average in sub-saline wetlands and as low as 4.54 species on average in hypersaline wetlands (Figure 21).

Table 5: Pairwise comparisons of isohyet and salinity categories using one-way ANOSIM. Isohyet categories are measured in millimetres per year. Salinity categories are numbered as per table 3.

Significance Significance Ishoyet Categories R Salinity Categories R Level % Level %

< 300 300-400 0.602 0.1 1 2 0.447 0.1 < 300 400-500 0.869 0.1 1 3 0.85 0.1 < 300 500-600 0.921 0.1 1 4 0.948 0.1 < 300 600-700 0.663 0.8 1 5 0.9 0.1 < 300 > 700 0.945 0.1 2 3 0.687 0.2 300-400 400-500 0.291 0.1 2 4 0.741 0.1 300-400 500-600 0.094 6.9 2 5 0.523 0.1 300-400 600-700 0.29 1.7 3 4 0.033 36.3 300-400 > 700 0.441 0.1 3 5 0.042 35.1 400-500 500-600 0.822 0.1 4 5 0.278 0.1 400-500 600-700 0.952 0.1 400-500 > 700 0.969 0.1 500-600 600-700 0.385 0.2 500-600 > 700 0.56 0.1 600-700 > 700 0.983 0.1

These large difference in invertebrate assemblages among salinity categories could have obscured temporal trends in wetland invertebrate assemblages. Each salinity category was thus analysed

individually (where data was sufficient: freshwater, saline, hypersaline wetlands), to determine whether time or extent of drying could be associated with patterns in assemblages within salinity categories. Potentially, temporal change or the effects of drying water regimes could affect assemblages differently depending on salinity levels. However, Invertebrate assemblages did not differ among year-groups in freshwater (R =-0.013, p = 0.528), saline (R = -0.085, p = 0.718) or hypersaline wetlands (R = -0.085, p = 0.718)

Figure 20: nMDS ordination plot using Bray-Curtis Dissimilarity showing wetland invertebrate assemblage composition coded by salinity category (as described in Table 3) (Stress=0.14). Fresh wetlands tended to have more stable invertebrate assemblages than more saline wetlands.

Figure 21: Column graph showing mean richness of aquatic invertebrates by salinity category (±1 standard error) (as described in Table 3). The number of samples in each salinity category (n) are displayed above each bar. Salinity categories based on Pinder et al. (2005).

Invertebrate assemblages from wetlands in different salinity categories (across all year-groups) were dissimilar in most cases (Table 5). Noobijup Swamp, (a freshwater wetland that reached brackish conditions on one occasion), and Lake Pleasant View (a fresh coastal lake) were the least dissimilar wetlands between salinity categories, at 59%. Hypersaline wetlands were highly dissimilar from fresh, brackish and sub-saline wetlands, with average dissimilarities ranging from 95% between the hypersaline Lake Ronnerup and the sub-saline Lake Logue, up to 99% between the fresh Lake Pleasant view and the hypersaline Lake Altham. Between saline and hypersaline wetlands, Lake Altham and Lake Coyrecup were the least dissimilar from each other at 59.7%, while Lake Bryde and Lake Campion were the most dissimilar at 98.4%. Alpha diversity

2 Alpha diversity was higher in the first than in the last half of the sampling period (χ 2 = 6.509, p = 0.039). More wetlands were classified as having low invertebrate richness in the last half of the sampling period (n = 26) than in the first half (n = 38) (Table 6). While the number of wetlands of medium richness did not change, the number of wetlands with high richness in the second half of the time period was less than 50% of that in the first half (Table 6).

Table 6: Distribution of wetland invertebrate richness comparing the first half of the sampling period, 1998-2004 to the second half of the sampling period, 2005-2011. Categories of richness based on aquatic invertebrate composition data described in Pinder et al. (2005). Each cell contains the number of year-group x wetland combinations for a salinity category and time period.

Invertebrate Richness categories

Low Medium High 0-15 16-49 50+ Totals 1997-2004 26 13 21 60 2005-2011 38 13 10 61 Totals 64 26 31 121

Within-wetland similarities showed that wetland invertebrate assemblages at all wetlands changed over time (Table 7). Kulicup had the highest similarity at 56% but also the highest proportion of dry years (0.714). Fresh and brackish wetlands had higher mean proportional richness, indicating that they maintained their tax richness more readily than wetlands in other salinity categories. Hypersaline wetlands had low mean richness and showed very low invertebrate assemblage similarities across time (Table 7).

Wetland invertebrate assemblages deviated from their normal pattern in hydrologically atypical years (Table 7). For example, the invertebrate assemblages of both Lake Bryde, a shallow saline wetland in the central wheatbelt, and Lake Logue, a deep coastal sub-saline wetland, were most dissimilar from themselves in their most shallow, most saline years, 1999 and 2002 respectively. Lake Coyrecup, a normally shallow, saline wetland, deviated from its typical assemblage in its deepest, least saline year, 2005.

Copepods, amphipods, chironomids, and ostracods were common, found across all years and across the full range of salinity categories. Two species of ostracod hatched at Bennett’s Lake after 6 years of dry samples; Mytilocypris mytiloides and Platycypris baueri. The amphipod Austrochiltonia subtenuis was the most common invertebrate species, identified in 49 out of 80 samples. Persistence was otherwise conditional upon salinity. For example, Coleoptera were found across all years in freshwater wetlands only, except for Necterosoma penicillatus, which persisted in saline conditions at Lake Bryde and Bennett’s Lake. Odonata were collected in all years at Goonaping Swamp, Fraser Lake and Lake Bryde. Trichoptera were not found in

wetlands with salinities higher than brackish. The fairy shrimp Paratemia longicaudata was found only at two hypersaline wetlands: Lake Altham in the one year it was inundated, and Ronnerup Lake in all years except the deepest and least saline year. Nematodes, oligochaetes, Trombidiformes (mites), isopods and decapods were rarely sampled between 1998 and 2011. Although Anostraca were identified in both freshwater and hypersaline wetlands, they were only found in wet years in hypersaline wetlands. Lake Ardath was dominated by a few Diptera and Coleoptera species as well as one halophilic anostracan, Parartemia serventyi but it was otherwise depauperate throughout the sampling period.

Table 7: Wetlands grouped by Salinity category as described in Table 3, listed in order of decreasing within wetland similarity and compared to three measurements of dryness and two measurements of richness. Lake Altham, A freshwater wetland, is not included here as it only had one sampling instance in which the wetland was inundated.

Wetland Within Wetland Similarities Salinity Mean Depth (m) Mean Proportional depth Proportion of Dry year Groups Mean Richness Mean Proportional Richness

Kulicup 56.36 Fresh 0.106 0.530 0.714 63.2 0.878 Goonaping 55.62 0.396 0.660 0.286 58.2 0.797 Paperbark 52.14 1.143 0.847 0.571 57.3 0.882 Pleasant View 51.21 0.866 0.618 0.000 71 0.747 Fraser 50.95 0.683 0.854 0.571 52 0.776 Yaalup 40.38 1.095 0.622 0.429 47.5 0.617

Wheatfield 54.9 Brackish 1.834 0.733 0.000 42.29 0.844 Noobijup 45.38 0.64 0.500 0.000 56.57 0.775

Logue 25.31 Sub-saline 2.15 0.589 0.571 38 0.644

Bennett's 49.57 Saline 1.218 0.412 0.428 18.5 0.425 Ardath 44.85 0.908 0.833 0.286 14.2 0.448 Coyrecup 40.13 0.969 0.425 0.000 17.57 0.429 Bryde 32.56 0.215 0.448 0.571 30.75 0.750

Dumbleyung 42.95 Hypersaline 0.848 0.322 0.286 8 0.364 Ronnerup 28.38 0.267 0.252 0.142 4.5 0.5625 Campion 6.36 0.633 0.361 0.571 3.25 0.575

The relationship between macrophytes, algae and aquatic invertebrates Field samples Three of the 12 wetlands were dry at the time of sampling in late November 2018, Lake Bryde, Kulicup swamp and Lake Campion. Macrophytes were found during field sampling at six out of the 12 wetlands. Kulicup Swamp and Lake Bennett’s only had one species each, the common sedge species Baumea juncea and the saltwater paperbark Melaleuca cuticularis respectively (Figure 22).

Figure 22: A stand of Melaleuca cuticularis near the shoreline of Lake Bennett’s. (Photo: Carey 2018). At the time of the experiment, Lake Bryde appeared to have been dry for some time, with groundwater appearing to be at least two metres down in an adjacent groundwater bore. The desiccated inflorescence of a species of salt-grass resembling Diplachne fusca was found across the lakebed. Lake Bryde was largely dominated by the samphire Muehlenbeckia horrida though living samples were only identified near the edge of the lakebed (Figure 23). Living specimens of Muehlenbeckia horrida were also found at Lake Dumbleyung growing in the shallow littoral zone along with rush Juncus articulatus, and sedge Bolboschoenus caldwellii. Two native species of rush were found at Lake Ronnerup, these being Juncus subsecundus and Baumea juncea

respectively. Two invasive species of macrophyte were identified, saltwater couch Paspalum vaginatum at Lake Wheatfield and barbgrass Parapholis incurva at Lake Ronnerup.

Figure 23: Lake Bryde was dominated by the samphire Muehlenbeckia horrida at the time of sampling in late November 2018, though much of it was dead (Photo: Carey, 2018). Noobijup Swamp was the most species rich wetland sampled, with seven species of macrophyte identified: Baumea arthrophylla and B. juncea with Alisma lanceolatum, Velleia trinervis and Centella asiatica interspersed between stands of sedge species. Polypogon tenellus and Lobelia anceps were found along the edge of the wetland (Figure 24).

Figure 24: Stands of Baumea arthrophylla, Baumea juncea and Lobelia anceps dominated the lakebed at Noobijup swamp. (Photo: Carey, 2018).

Glasshouse Experiment Only two macrophyte seedlings germinated in the glasshouse experiment, a monocotyledon in one of the sediment samples from Lake Bennett’s and a dicotyledon from a sediment sample at Lake Coyrecup. Neither seedling could be identified beyond their basic structure due to their immature developmental stage.

Cyanobacteria emerged in all but three wetlands during the glasshouse experiment (Kulicup swamp, Noobijup swamp and Lake Campion). Nine of the 22 species identified in the laboratory were cyanobacteria, forming microbial mats with fungal hyphae, algal spores and single celled algae such as Oocystis sp. and Closterium sp. at six of the 12 wetlands, (Lake Bryde, Paperbark Swamp, Lake Wheatfield, Lake Bennetts, Lake Dumbleyung and Lake Ronnerup). While Lake Ardath, Lake Coyreup and Yaalup Salty, contained cyanobacteria, they did not form microbial mats.

Charophytes emerged at seven out of the 12 wetlands (Figure 25), across an extremely abroad range of salinities. Lake Campion was the most species poor wetland, with only a single charophyte emerging. Chara globularis germinated in samples from the freshest wetland, Kulicup Swamp, while Chara fibrosa germinated from the sediment of the most hypersaline wetland, Yaalup Salty, which recorded a salinity beyond saturation point (the YSI recorded a 1:3 ratio value of 148 mS cm-1. This is likely to be inaccurate but representative, given the YSI was calibrated to 110 mS cm-1).

Figure 25: Richness of flora by functional group as found in the germination experiment and taken from the field, sorted left to right by increasing maximum salinity. ◆ indicates a wetland whose median total phosphorus exceeded the ANZECC guidelines recommended value of 60 ug L -1 during the historical sampling period. ▲ indicates a wetland whose median total nitrogen exceeded the ANZECC guidelines recommended value of 1500 ug L-1 during the historical sampling period. Functional groups are based on Entwisle, et al. (1997) No invertebrates emerged in seven of the 12 wetlands in the glasshouse experiment (Figure 26). Hatching invertebrates were depauperate in the remaining five wetlands. Ostracods were the most common invertebrate hatched in four of the five wetlands, however only one ostracod species, Mytilocypris tasmanica chapmani, was found at more than one wetland. Three different species of ostracod were recorded from Lake Bryde: Candonocypris novaezelandiae, Mytilocypris tasmanica chapmani and Eucypris sp. Lake Bryde also recorded two species of Diptera: Aedes ochlerotatus and Culicinae sp. Lake Bennett’s was the second most specious wetland in the glasshouse experiment, recording four invertebrate species: the diving beetle Hyphydrus elegans, the fairy shrimp Anostraca branchinella, the isopod Haloniscus sp. and an unidentified ostracod in the family Cyprididae. As few plants germinated and few invertebrates emerged from the sediment samples, no formal data analyses were carried out.

Figure 26: Richness of aquatic invertebrates Identified to family as found in the germination experiment, sorted left to right by increasing maximum salinity.

Discussion Wetlands in the Western Australian Wheatbelt and Great Southern regions showed increased frequency of drying during the 13 years between 1998 and 2011 The 17 wetlands in this study showed increased frequency of drying during the 13 years between 1998 and 2011. Rainfall records show that the time period 1997 to 2011 was the driest April to September period on record at that time (Bureau of Meteorology, 2013). This is a continuation of a multi-decadal trend of declining rainfall in south Western Australia since the mid 1970’s (Bates et al., 2008a; Hope et al., 2006). Climatic drying was also noted by Sim et al. (2013) who showed a drying trend between 1989 and 2008 in four Swan Coastal Plain wetlands. Central west Western Australia (an area which incorporates two lakes in this study; Lake Logue and Fraser Lake) experienced a similar but weaker drying trend from 2001-2011 (Fierro and Leslie, 2013). Wetlands were most often dry in the final year-group, 2010-2011. 2010 was the driest year on record for south-western Australia, receiving an average of only 310 mm of rainfall between April and October compared to the long-term average of around 550 mm (Bureau of Meteorology, 2019c). Long-term studies of groundwater tables in this region show marked declines in water table depth. Altogether, these contribute to reduced wetland inundation and evaporation (Allan & Haylock, 1993; Roderick & Farquhar, 2004; Cai & Cowan, 2006; Finlayson et al., 2013; Deitch et al., 2017). My results show that the trend of prolonged and more frequent dry periods in wetlands was detectable over the 13-year period of this

dataset. Therefore, it is likely that drying water regimes influenced wetland invertebrate assemblages during this time.

Gamma and alpha diversity declined, but beta diversity remained high, from 1998 to 2011 Regional (gamma) richness declined over the time period between 1998 and 2011. Few other studies have reported changes in freshwater biodiversity over such a large geographic area and a long period of monitoring. Although there are several studies of aquatic invertebrate assemblages over large spatial scales in the Wheatbelt and Great Southern regions of Western Australia (Halse et al., 1993a; Halse et al., 1993b; Pinder et al., 2002; Blinn et al., 2004; Pinder et al., 2005; Boix et al., 2008), these studies do not provided insight into temporal change. However, Jenkins and Boulton (2007) showed a decline in invertebrate assemblages across a comparable time period in Darling river floodplain wetlands. They found that wetlands that had been dry for six years were, upon re-wetting, on average, approximately one third more taxa rich than those that had been dry for 20 years (38 versus 26 taxa). Regional aquatic invertebrate diversity is therefore likely to decline as wetlands experience longer dry periods.

Invertebrate beta diversity remained high among wetlands from 1998 to 2011. The taxonomic distinctness of wetlands in the wheatbelt and Great Southern Regions appears to be much higher than in the adjacent Swan Coastal Plain (SCP) (Horwitz et al., 2009). This difference may be explained by the vast distances between wetlands in the present study (Wheatbelt and Great Southern regions cover more than 194,000 km2), which may encompass bioregional differences that SCP studies do not. Nevertheless, these highly distinct wetland invertebrate assemblages were surprising, though not unprecedented (e.g. Blinn et al., 2004). Differences due to wetland distinctness were so strong that they comprised the most important pattern in the dataset. Had more wetlands been studied, a more gradual change in invertebrate assemblages across distances may have been detected. Counter to this, assemblages at Bennett’s Lake and Lake Ronnerup were significantly different despite being less than two kilometres apart demonstrating that factors other than distance, such as water regime and water quality, contribute to differences in wetland invertebrate assemblages.

Results showed that alpha diversity of aquatic invertebrates declined from 1998 to 2011 across the Wheatbelt and Great Southern regions. Wetlands deviated from the norm in years with atypical hydrology; i.e. wetlands with normally low richness increased in their deeper years, and vice versa. This is in contrast to the findings of Sim et al. (2013) who found no significant relationship between invertebrate assemblage and drying water regimes on the Swan Coastal Plain over periods of six to 25 years. The two studies differ greatly in the distances between wetlands and the variation in precipitation and salinity. While the nine wetlands in Sim, et al. (2013) were located relatively close to each other and received roughly the same precipitation, wetlands in the present study are dispersed across a very large region, with average annual rainfall ranging between 300 and 700 mm year-1. However, other studies also show that reduced frequency of wetland inundation is associated with reduced taxa richness (Williams et al., 2004; Robson & Clay, 2005).

Many studies have opted to examine the effects of drier water regimes at different scales of diversity by following changes in invertebrate assemblages over short time periods or small areas. Waterkeyn et al. (2008) examined 30 temporary wetlands in a small area in southern France (145, 000 ha) finding that wetlands with shorter hydroperiods reported lower invertebrate richness (lower alpha diversity). Anton-Pardo & Armangol (2014) found that wetland depth was one of many environmental and ecological factors that contributed to changes in aquatic invertebrate alpha diversity in eight lakes in south eastern Spain. To assess gamma diversity in a 365 km2 area of central Oklahoma, Meyer et al. (2015) tracked changes in aquatic invertebrate assemblages over a period of 28 weeks in 58 wetlands and found gamma diversity increased over time as wetlands became more inundated. While these studies do not match the temporal and geographic scale of the present study, they nevertheless show similar ecological outcomes of drier water regimes.

Larger studies that compare intermittent and perennial wetlands support the findings of the present study regarding the impact of drier water regimes. Boix et al. (2008) found that more hydrologically stable wetlands (perennial) were more species rich than less hydrologically stable (intermittent) wetlands distributed across Catalonia, Spain. Gleason & Rooney (2018) investigated beta diversity among 87 pothole wetlands in the Northern Prairie of North

America, an area three and a half times the size of the present study. Seasonal, semi- permanent and permanent wetlands were found to have distinct invertebrate assemblages. Unlike the present study, Gleason & Rooney’s (2018) results were not affected by strong gradients in physiochemical variables. However, they only identified invertebrates to family level, which may mask wetland diversity. Robson & Clay (2005) investigated aquatic invertebrate beta diversity in wetland of differing water regime in a 25,000 km2 region of south eastern Victoria, Australia. They found that seasonal wetlands were less taxa rich than more permanent wetlands. Aquatic invertebrate gamma diversity in temporary ponds in England and Wales is low compared to the present study. Nicolet et al. (2004) found that temporary wetlands in England and Wales supported less than half the number of species in the present study, over a region roughly three quarters the size of the Wheatbelt and Great Southern regions. They did however find that temporary pond invertebrates were a sub-set of permanent wetland invertebrates, indicating a much more homogenous invertebrate assemblage (and therefore lower beta diversity) than in the Wheatbelt and Great Southern regions. Regardless of the differing methods and shorter time frames used in these studies, they support the results in the present study that drier water regimes lead to declines in invertebrate diversity.

Associations between invertebrate fauna and environmental variables Individual variability in environmental variables contributed to within-wetland dissimilarity across time. In some cases, these circumstances obscured changes in assemblages due to water regime change. For example, the invertebrate assemblage at Lake Ardath may have been limited by its relatively low pH of ~4.0. Acidity and Alkalinity may influence invertebrate assemblages. For example, Nicolet et al. (2004) found that pH was the most significant factor contributing to differences in invertebrate assemblages among temporary wetlands in England and Wales, with higher pH being associated with crustaceans, circumneutral pH with gastropods and lower pH being associated with Hemiptera and Trichoptera. Additionally, acidity levels below 4.5 have been shown to limit aquatic invertebrate richness to only a few species in low abundance (Berezina, 2001). Paperbark Swamp was nutrient enriched, and this is known to influence wetland invertebrate communities. Bini et al. (2014) found that invertebrate beta

diversity increased in streams with increased nutrient enrichment and Chessman et al. (2002) developed the SWAMPS index for wetland degradation, including eutrophication, based on the responses of invertebrate taxa. Individual circumstances such as these, however, did not contribute appreciably to the reasons for changes in gamma or beta diversity in the present study.

Drying water regimes may precipitate changes in ecological state at a regional scale in Wheatbelt and Great Southern region wetlands. My results showed stepwise declines in pooled regional richness coinciding with historically low annual rainfall periods (Bureau of Meteorology, 2010; 2012; 2018). Ecological thresholds for aquatic plants and invertebrates have already been investigated for various water quality variables (Dobberfuhl, 2007; Clements et al., 2010; Benoy et al., 2012; Tang et al., 2016). In the present study, water regime thresholds may be related to differences in desiccation resistance among taxa. The most common species found in the wetlands were those often found in wetlands following periods of dryness that exhibit a range of desiccation resistance strategies. These included copepods, which are capable of entering diapause at multiple life stages, also have desiccation-resistant eggs, and are one of the invertebrate groups best adapted for climatic drying (Conover, 1988; Naess & Nilssen, 1991). Ostracods also possess several desiccation resistant strategies including adult diapause (Horne, 1993; Larned et al., 2007; Vargas et al., 2019), or quiescence (a form of short- term diapause), desiccation-resistant eggs and refuge seeking behavior (Strachan et al., 2014). Horne (1993) found that juvenile Candona patzcuro ostracods were able to remain dormant for between 18 and 30 months, depending on temperature. The present study suggests that some ostracod species may remain dormant for up to six years, but more study is needed. Chironomid larvae have long been reported to be highly abundant in all manner of wetlands (Bryce, 1962; Langdon et al., 2006; Langdon et al., 2010). Females produce gelatinous egg masses that are resistant to desiccation, particularly when oviposited among vegetation (Raats & Halpern, 2007; Bartlett et al., 2019) and adults can freely select the most ideal habitat within their range because they can fly. Two amphipod species, Austrochiltonia and Crangonyx pseudogracilis resisted dry periods. Amphipods are known to seek shelter during times of environmental stress (Williams, 1995) and some can survive more than 24 hours without

immersion under humid terrestrial conditions (Morritt, 1987; Marsden, 1991). Or they may use the water table as a means of desiccation resistance and as a pathway between temporary wetlands (Harris et al., 2002). However, the specific means used by both these species to survive drying are not known.

Decapods, isopods, oligochaetes and Odonata were rarely found during the study. Crayfish (Decapoda) can move overland from one wetland to another over short distances (Ramalho & Anastácio, 2015; Thomas et al., 2018) and rely mostly on refuge seeking in burrows for drought resistance (Rice & Chapman, 1971; Crandall & Buhay, 2007). Additionally, both Cherax destructor and Cherax quinquecarinatus have been shown to be intolerant of sub-saline conditions (Mills & Geddes, 1980; Anson & Rouse, 1994). Adults may therefore be forced to seek new refuges under drier, more saline conditions, exposing them to predation from birds and mammals during overland travel (Macneil et al., 1999; Englund & Krupa, 2000). Decapod shrimp (Palaemon australis) have no traits for surviving wetland drying, so when wetlands begin to dry, they will become locally extinct unless reintroduced (Chester & Robson, 2013). Some species of oligochaete are able to create hard outer shells to resist desiccation, although these only succeed over a short time periods and in relatively humid sediment (Maraldo et al., 2009). Only a small number of Odonata worldwide are adapted to saline conditions (Kalkman et al., 2008). Rapid development allows Odonata to reach the mobile adult stage quickly enough to disperse to more ideal wetlands (Stoks et al., 2005). However, many species (especially damselflies) are known to be territorial and do not venture far from their chosen habitat (McPeek, 1989). Additionally, their eggs and larvae seem to require some form of moist refuge to survive (Gooderham & Tsyrlin, 2002; Theischinger & Hawking, 2006). Some damselflies can undergo eclosion under dry conditions, but only in their final larval instar (Chester & Robson, 2013). Although some dragonfly adults are able to fly long distances in search of suitable habitat (Razeng et al., 2016), Odonata may be under greater pressure from climatic drying than other insect species should climatic drying reduce habitat connectedness. Thresholds in invertebrate assemblage composition determined by water regime may exist in wetlands in the Wheatbelt and Great Southern regions, but further research is needed.

In the present study caddisflies (Trichoptera) were found across all inundated years but only in freshwater wetlands because caddisfly larvae can only survive a few hours of exposure to seawater levels of salinity (Williams and Williams, 1998). Caddisflies do employ some desiccation resistant strategies. For example, commonly occurring large shredding Leptoceridae caddisflies seal their cases with silk and become dormant to survive dry periods (Robson et al., 2013a; Wickson et al., 2012). However, survival of dormancy improves if conditions remain cool and damp (Wickson et al., 2012). So, caddisflies may succumb to (climatic drying driven) increases in salinity before wetlands dry out completely, or to loss of sediment moisture during prolonged drying. Although these caddisflies are thought to be good dispersers (Chester et al., 2015), further studies should be undertaken as climatic drying continues to see how well they can keep up with the changes.

In contrast, Anostraca of the genera Parartemia and Artemia were found to be most persistent in hypersaline wetlands during inundated years, and this has been observed elsewhere (Pinder et al., 2002; Timms et al., 2014; Williams and Geddes, 2018). The eggs of Anostraca are able to survive long periods of drying (Brendonck, 1996). Although Anostracans were found across all ranges of salinity, they were found across all years only in hypersaline wetlands, suggesting that these two genera evolved to thrive in hypersaline conditions where there is decreased competition and predation from predatory invertebrates (such as large branchiopods) unsuited to hypersaline conditions (Waterkeyn et al., 2011; De Vos et al., 2019). Therefore, understanding the mechanisms by which invert taxa can persist in drying wetlands is important to predict future invert communities in drying regions.

Depauperate and more temporally variable invertebrate assemblages were associated with more saline wetlands in regions with lower average annual rainfall, which contributed to patterns of alpha, beta and gamma diversity. This conclusion is supported by other studies in the Wheatbelt. For example, between 1996 and 2001 Delaney et al. (2016) examined the invertebrate assemblages of 20 wetlands in the wheatbelt, finding that; 1) differences in salinity explained 83% of the difference between wetlands, 2) fresh and brackish wetlands supported higher taxa richness and, 3) saline and hypersaline wetlands had the highest variability in assemblages between years. Observations in the present study support these conclusions. Blinn

et al. (2004) sampled micro-invertebrates from 56 wetlands in the wheatbelt but found none in hypersaline wetlands (138 gL-1) and found freshwater wetlands to be more taxa rich than brackish or saline wetlands. Pinder et al. (2005) found that a small number of halophilic species dominated wetlands in the Western Australian wheatbelt with salinities above 30 gL-1. Freshwater taxa dropped off rapidly at salinities between 4 gL-1 and 10 gL-1. Boix et al. (2008) also found a shift in invertebrate assemblages in Iberian Peninsula wetlands from insect- dominated at low salinities to crustacean-dominated at near marine level salinities. Drier conditions therefore reduce invertebrate diversity indirectly through increases in salinity.

Egg and seed banks in wheatbelt and great southern wetlands may now be depauperate Unfortunately, conclusions cannot be made about the relationship between macrophytes and invertebrates emerging from sediment based on results from the glasshouse inundation trial. Invertebrate richness and abundance were very low when compared to similar experiments conducted in SCP. Using similar sampling methods, Strachan et al. (2016b) identified 55 species of invertebrates emerging in high densities from sediment samples taken from eight SCP wetlands. The present study only identified 14 species from sediment samples from 12 wetlands and densities were low. Proportionally, invertebrate families differed between the two studies. While an equal number of ostracod species were identified in both studies, 12 species of Diptera and seven species of Coleoptera were found by Strachan et al. (2016b), compared with three and two in the present study. Strachan et al. (2016b) focused on fresh to sub-saline wetlands compared to this study, which covered wetlands that ranged from fresh to hypersaline. The SCP wetlands are also inundated for longer periods each year than many of those in the current study. It is therefore is not surprising that the present study was dominated by ostracods, which are resistant to both salinity and drying (Williams, 1980; Horne, 1993; Aguilar-Alberola & Mesquita-Joanes, 2011). However, the diversity of taxa emerging from sediments was surprisingly low and may indicate that prolonged drying has already damaged sediment egg and seed banks.

One potential alternative explanation for the low hatching from the egg bank is that appropriate cues for hatching or breaking dormancy were not provided. Strachan et al. (2016a) showed that some invertebrate species delay hatching for up to 30 days post-inundation.

However, as my trial ran for nine weeks, it seems unlikely that too many taxa were missed for this reason. However, the paucity of hatching macroinvertebrates in sediment samples may also be attributed to inadequate sampling. Halse et al. (2002) found that it took between nine and 15 aquatic invertebrate samples at lakes Bryde, Wheatfield, Logue and Coyrecup before species accumulation graphs started to flatten out. Therefore, insufficient numbers of samples may have been used in the trial.

For aquatic plants, it has been suggested that germination cues interact in complex ways, with possible outcomes being stochastic in nature (Baskin & Baskin, 1998; Brock et al., 2003). One potential reason more macrophytes did not germinate could be that many of the seeds in the samples were not viable. Viability of dormant seeds after a break in dryness varies with species. In an experimental study using the sediments of six wetlands in New South Wales, Brock et al. (2003) found that less than half of all macrophyte species germinated after nine years of dormancy. Dormancy periods may even vary within a single genus. For example, seed dormancy can range from a few weeks to nearly three years in the sedge genus Eleocharis (Bell & Clarke, 2004).

Field sampling and experimental observations in the present study found macrophytes not only at freshwater and saline wetlands (Noobijup Swamp, Kulicup Swamp and Lake Bryde), but also at two hypersaline wetlands, Lakes Ronnerup and Dumbleyung. As salinities increase, wetlands in the Wheatbelt are known to transition from macrophyte-dominated communities at low salinities to benthic microbial mat-dominated systems at high salinities at around 100 gL-1 (~180 mS cm-1) (Brock, 1981; Finlayson et al., 2013). In the present study, microbial mats grew in samples from two brackish and two saline wetlands, matching experimental results reported by Sim et al. (2006b). In contrast with other published material, charophytes in this experiment emerged from fresh and hypersaline wetland samples. Lamprothamnium sp. can survive in salinities up to 50 gL-1 (~91 mS cm-1) and will not germinate in waters with a salinity of 70 gL-1 (12.27 mS cm-1) (Brock, 1981; Sim et al., 2006b). Additionally, Chara (which germinated in this study) is commonly found in fresh and brackish waters (Entwisle et al., 1997). This apparent contradiction may be due to experimental inundation being more dilute than field observations. Unfortunately, I did not measure salinities during the trial, an oversight that limits

interpretation of the trial results. Overall, although the experiment produced results that could not be used to make inferences about the relationship between macrophytes and invertebrates in the Wheatbelt and Great Southern region wetlands under climatic dryness, the low numbers of germinating seeds and emerging invertebrates raises the concern that drying together with salinization may have depleted egg and seed banks in these wetlands. A larger, better replicated study is needed to confirm whether this is the case.

Management Implications

The vast differences in wetland invertebrate assemblages over the Wheatbelt and Great Southern regions shows that wetlands spread across such a large area cannot be managed with the same strategies. Freshwater wetlands in the wheatbelt with salt sensitive taxa have undergone intense conservation efforts to maintain their ecosystems and prevent more saline conditions (Vogwill et al., 2010). However, due to diversions of saline groundwater, Lake Toolibin did not inundate for two decades. When it did inundate (in 2017, after ≈ 20 years dry) it was fresh but contained only a handful of invertebrate species, indicating the loss of the egg bank (Pinder, personal communication May 2019). So, although these conservation measures have prevented the lake becoming saline, most freshwater invertebrate species have been lost due to climatic drying. Consequently, conservation management of wheatbelt wetlands with regard to salinity and drying requires careful, individualized management, if they are to remain both wet and fresh. Invertebrates in saline wetlands with drier water regimes are already adapted to life in harsh conditions, but still need to be monitored, as they represent unique ecosystems that could be lost if climatic drying intensifies.

Conclusions Climatic drying places wetland invertebrates under pressure of desiccation and increasing salinities and is associated with declining alpha and gamma diversity. Although many species can survive these changes, extended periods of dryness lead to the eventual depletion of sediment egg banks, further reducing alpha diversity. Given the high taxonomic distinctness of invertebrate assemblages in these wetlands, loss of alpha diversity also reduces gamma diversity. By 2011, beta diversity had remained high, indicating that the ecological distinctness

of wetland invertebrate assemblages had been sustained despite the loss of species. Sensitive species such as gastropods and isopods may be lost entirely from parts of the study region. Declines in alpha and gamma richness are occurring more slowly in freshwater wetlands in the southwest corner of the study region, as those wetlands experienced less drying than more northern and eastern wetlands. As wetlands continue to experience climatic drying, we can expect to see further declines in aquatic invertebrate diversity across the Wheatbelt and Great Southern Regions and invertebrate assemblages are likely to look very different (i.e. less diverse) in the future.

For some time now there has been a call for researchers to provide “…observational information about changes in species and ecosystems…” and “…conduct assessments with available information” (Dunlop and Brown, 2008). Providing the ecological knowledge required for land managers to effectively manage their wetlands is the first step to successfully maintaining and preserving inland wetlands under changing climate. The issue of climate change has been in the zeitgeist for more than a quarter of a century, over which time long term datasets examining ecosystem function and constitution have been collected. Through an evaluation of long-term data available in regions suffering from climate drying, along with information regarding ecological change in wetlands from across the globe, I have provided a more complete view of the changes that wetlands undergo following more frequent periods of drying. The results of this study can inform environmental decision makers and management bodies of potential ecological consequences of continued drying scenarios in Mediterranean regions so that steps can be taken to mitigate or avoid the most severe outcomes.

Acknowledgements Thanks to Adrian Pinder and David Cale for providing the invertebrate and water quality data from these wetlands for the years 1998-2011 and for their expert knowledge and support during my Honours year. Thanks go to Belinda Robson and Jane Chambers for supervision, and the enormous amount of knowledge and support provided. Special thanks to Nicole Carey for assistance reassurances and photos taken during the fieldwork portion of the project and ongoing support. Invertebrate sampling was carried out under authority from the Department

of Primary Industries and Regional Development, Fish Resources Act 1994 Instrument of Exemption No. 3168, and the Department of Parks and Wildlife, Wildlife Conservation Act 1950 Regulation 17 - License to take fauna for scientific purposes No. 08-002935-1. Flora sampling was carried out under authority from the Department of Wildlife, Wildlife Conservation Act 1950 – License for scientific or other prescribed purposes No. SW019752 and the Conservation and Land Management Regulations 2002 Regulation 4 Written notice of lawful authority No. CE05835.

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Appendices Appendix 1: Sampling schedule for the 17 wetlands included in this study, assigned to year- groups 1 through 7. Samples labeled as dry are those years in which the wetland was visited but found to be dry and thus no invertebrates were sampled.

Biannual Year Group 1 2 3 4 5 6 7

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011 Wetland Wetland Name Code

SPM001 Bryde dry dry dry

SPM002 Logue dry dry dry dry

SPM004 Coyrecup

SPM005 Wheatfield

SPM006 Altham dry dry dry dry dry dry

SPM007 Noobijup

SPM008 Bennetts dry dry dry

SPM009 Ardath dry

SPM011 Kulicup dry dry

SPM012 Campion dry dry

SPM013 Goonapping dry dry

SPM017 Fraser dry dry dry dry

SPM019 Paperbark dry dry dry dry

SPM021 Dumbleyung dry

SPM022 Yaalup dry dry

SPM024 Pleasant View

SPM025 Ronnerup dry

Appendix 2: To determine whether geo-position played a part in determining the differences in aquatic invertebrate assemblage between wetlands over the region, wetlands were selected along north to south and east to west corridors (figure 27). One-way ANOSIM (Primer-E v.6) showed that wetlands along these corridors were not significantly different and as such this test was discarded

Figure 27: Map of south west Western Australia showing the north-south and east-west corridors used to pick wetlands for testing the hypothesis that there is a difference between wetlands running east to west, and north to south. Modified from Cale, et al. (2004). No significant differences were identified, and this test was ultimately discarded.

Appendix 3: nMDS ordination plot using Bray Curtis Dissimilarity showing labelled by pH factor as described in Table 3showing no pattern in pH emerging (stress=0.14).

Appendix 4: Experimental layout of the germination experiment in the Murdoch University Glasshouse Facility, with East towards the top of the diagram.

Ardath 3 Ardath 2 Campion 2 Bennetts 3 Ronnerup 4 Bryde 1 Bryde 3 Ronnerup 2 Noobijup 5 Dumbleyung 3

Campion 1 Campion 3 Paperbark 1 Kulicup 3 Dumbleyung 2 Yaalup 2 Yaalup 1 Bryde 5 Noobijup 4 Noobijup 1

wheatfield 3 Coyrecup 1 Campion 5 Kulicup 2 Kulicup 5 Dumbleyung 5 Wheatfield 1 Paperbark 3 Ronnerup 1 Coyrecup 5

Ardath 1 Bennetts 2 Bennetts 1 Dumbleyung 4 Yaalup 5 Bennetts 4 Yaalup 4 Ronnerup 5 Paperbark 2 Kulicup 1

Coyrecup 2 Ardath 5 Coyrecup 4 Kulicup 4 Yaalup 3 Bryde 4 Ronnerup 3 Wheatfield 4 Bryde 2 Wheatfield 5

Campion 4 Ardath 4 Paperbark 5 Paperbark 4 Dumbleyung 1 Bennetts 5 Wheatfield 2 Coyrecup 3 Noobijup 3 Noobijup 2

Appendix 5: List of invertebrates identified in the 17 wetlands identified from 1998-1999.

Class Order Family Genus Species (Or Lowest order ID) Aphanoneura - Aeolosomatidae - Aeolosomatidae Arachnida Mesostigmata - - Mesostigmata Arachnida Sarcoptiformes - - Oribatida sp. Arachnida Trombidiformes - - Trombidioidea Arachnida Trombidiformes Arrenuridae Arrenurus Arrenurus (Arrenurus) balladoniensis Arachnida Trombidiformes Eylaidae Eylais Eylais sp. Arachnida Trombidiformes Hydryphantidae Diplodontus Diplodontus sp. Arachnida Trombidiformes Limnesiidae Limnesia Limnesia dentifera Arachnida Trombidiformes Limnocharidae Limnochares Limnochares australica Arachnida Trombidiformes Oxidae Oxus Oxus australicus Arachnida Trombidiformes Pezidae - Pezidae Arachnida Trombidiformes Pionidae Acercella Acercella falcipes Arachnida Trombidiformes Unionicolidae Koenikea Koenikea nr australica (=verrucosa) Crustacea Amphipoda Ceinidae Austrochiltonia Austrochiltonia subtenuis Crustacea Amphipoda Melitidae Melita Melita kauerti Crustacea Anostraca Branchipodidae Parartemia Parartemia longicaudata subspecies a (SAP) Crustacea Anostraca Branchipodidae Parartemia Parartemia serventyi Crustacea Anostraca Thamnocephalidae Branchinella Branchinella lyrifera Crustacea Cladocera Chydoridae Alona Alona guttata Crustacea Cladocera Chydoridae Alona Alona n. sp.? (nr. affinis) (SAP) Crustacea Cladocera Chydoridae Alona Alona rigidicaudis Crustacea Cladocera Chydoridae Alona Alona setigera Crustacea Cladocera Chydoridae Alona Alona willisi Crustacea Cladocera Chydoridae Alonella Alonella cf. exigua (SAP) Crustacea Cladocera Chydoridae Alonella Alonella clathratula Crustacea Cladocera Chydoridae Armatalona Armatalona macrocopa Crustacea Cladocera Chydoridae Camptocercus Camptocercus australis Crustacea Cladocera Chydoridae Chydorus Chydorus sp. Crustacea Cladocera Chydoridae Dunhevedia Dunhevedia crassa

Crustacea Cladocera Chydoridae Ephemeroporus Ephemeroporus barroisi s.l. Crustacea Cladocera Chydoridae Graptoleberis Graptoleberis testudinaria Crustacea Cladocera Chydoridae Kurzia Kurzia latissima Crustacea Cladocera Chydoridae Leberis Leberis diaphana vermiculata Crustacea Cladocera Chydoridae Leydigia Leydigia australis Crustacea Cladocera Chydoridae Leydigia Leydigia cf. leydigii (SAP) Crustacea Cladocera Chydoridae Ovatalona Ovatalona cambouei Crustacea Cladocera Chydoridae Ovatalona Ovatalona sp. nov. e (nr. pulchella) (SAP) Crustacea Cladocera Chydoridae Pleuroxus Pleuroxus inermis Crustacea Cladocera Chydoridae Rak Rak labrosus Crustacea Cladocera Chydoridae Rak Rak sp. nov. a (Goonaping) (SAP) Crustacea Cladocera Chydoridae Rak Rak sp. nov. b (Venemores) (SAP) Crustacea Cladocera Daphniidae Ceriodaphnia Ceriodaphnia n. sp. a (Berner sp.#3) (SAP) Crustacea Cladocera Daphniidae Ceriodaphnia Ceriodaphnia n. sp. b (Berner sp.#2) (SAP) Crustacea Cladocera Daphniidae Daphnia Daphnia carinata Crustacea Cladocera Daphniidae Daphnia Daphnia cephalata Crustacea Cladocera Daphniidae Daphnia Daphnia pusilla Crustacea Cladocera Daphniidae Daphnia Daphnia queenslandensis Crustacea Cladocera Daphniidae Daphnia Daphnia sp. a (SAP) (ex Daphniopsis) Crustacea Cladocera Daphniidae Daphnia Daphnia truncata Crustacea Cladocera Daphniidae Daphnia Daphnia wardi Crustacea Cladocera Daphniidae Scapholeberis Scapholeberis kingi Crustacea Cladocera Daphniidae Simocephalus Simocephalus elizabethae Crustacea Cladocera Daphniidae Simocephalus Simocephalus gibbosus Crustacea Cladocera Daphniidae Simocephalus Simocephalus victoriensis Crustacea Cladocera Ilyocryptidae Ilyocryptus Ilyocryptus cf. raridentatus (SAP) Crustacea Cladocera Ilyocryptidae Ilyocryptus Ilyocryptus spinifer Crustacea Cladocera Macrotrichidae Macrothrix Macrothrix breviseta Crustacea Cladocera Macrotrichidae Macrothrix Macrothrix indistincta Crustacea Cladocera Macrotrichidae Macrothrix Macrothrix sp. a (of RJS) (SAP) Crustacea Cladocera Moinidae Moina Moina micrura s.l. Crustacea Cladocera Sididae Diaphanosoma Diaphanosoma unguiculatum

Crustacea Cladocera Sididae Latonopsis Latonopsis brehmi Crustacea Conchostraca Limnadiidae Eulimnadia Eulimnadia vinculuma Crustacea Conchostraca Lyncaeidae Lynceus Lynceus sp. Crustacea Copepoda - - Harpacticoida sp. 2 (SAP) Crustacea Copepoda Ameiridae Nitocra Nitocra sp. 2 (SAP) Crustacea Copepoda Ameiridae Nitocra Nitocra sp. 4 (SAP) Crustacea Copepoda Ameiridae Nitocra Nitocra sp. 5 (nr reducta) (SAP) Crustacea Copepoda Canthocamptidae - Australocamptus sp. 5 (SAP) Crustacea Copepoda Canthocamptidae - Canthocamptidae sp. 4 (SAP) Crustacea Copepoda Canthocamptidae Canthocamptus Canthocamptus australicus Crustacea Copepoda Canthocamptidae Mesochra Mesochra nr flava Crustacea Copepoda Centropagidae Boeckella Boeckella robusta Crustacea Copepoda Centropagidae Boeckella Boeckella triarticulata Crustacea Copepoda Centropagidae Calamoecia Calamoecia attenuata Crustacea Copepoda Centropagidae Calamoecia Calamoecia clitellata Crustacea Copepoda Centropagidae Calamoecia Calamoecia sp. 342 (ampulla variant) (CB) Crustacea Copepoda Centropagidae Calamoecia Calamoecia tasmanica subattenuata Crustacea Copepoda Centropagidae Calamoecia Calamoecia trilobata Crustacea Copepoda Centropagidae Gladioferens Gladioferens imparipes Crustacea Copepoda Cyclopidae Apocyclops Apocyclops dengizicus Crustacea Copepoda Cyclopidae Australocyclops Australocyclops australis Crustacea Copepoda Cyclopidae Australocyclops Australocyclops palustrium Australoeucyclops darwini (ex Paracyclops sp 1 nr Crustacea Copepoda Cyclopidae Australoeucyclops timmsi) Crustacea Copepoda Cyclopidae Halicyclops Halicyclops sp. 1 (nr ambiguus) (SAP) Crustacea Copepoda Cyclopidae Macrocyclops Macrocyclops albidus Crustacea Copepoda Cyclopidae Meridiecyclops Meridiecyclops baylyi Crustacea Copepoda Cyclopidae Mesocyclops Mesocyclops brooksi Crustacea Copepoda Cyclopidae Microcyclops Microcyclops varicans Crustacea Copepoda Cyclopidae Pescecyclops Pescecyclops sp. 4 (=sp. 11 = arnaudi sensu Sars variant) Pescecyclops sp. 434 (Stuart's original arnaudi sensu Crustacea Copepoda Cyclopidae Pescecyclops Sars)

Pescecyclops sp. 442=462=465=CB2 (salinarum in Crustacea Copepoda Cyclopidae Pescecyclops Morton) Crustacea Copepoda Laophontidae Onychocamptus Onychocamptus bengalensis Crustacea Decapoda Palaemonidae Palaemonetes Palaemonetes australis Crustacea Decapoda Parastacidae Cherax Cherax destructor Crustacea Decapoda Parastacidae Cherax Cherax preissii Crustacea Decapoda Parastacidae Cherax Cherax quinquecarinatus Crustacea Isopoda Oniscidae Haloniscus Haloniscus searlei Crustacea Isopoda Philosciidae - Philosciidae Crustacea Isopoda Sphaeromatidae Exosphaeroma Exosphaeroma sp. Crustacea Ostracoda Candonidae Candonopsis Candonopsis tenuis Crustacea Ostracoda Cyprididae Alboa Alboa worooa Crustacea Ostracoda Cyprididae Australocypris Australocypris bennetti Crustacea Ostracoda Cyprididae Australocypris Australocypris insularis Crustacea Ostracoda Cyprididae Bennelongia Bennelongia australis lineage Crustacea Ostracoda Cyprididae Bennelongia Bennelongia barangaroo lineage Crustacea Ostracoda Cyprididae Caboncypris Caboncypris nunkeri Crustacea Ostracoda Cyprididae Candonocypris Candonocypris novaezelandiae Crustacea Ostracoda Cyprididae Candonocypris Candonocypris sp. 682 (?novaezelandiae) (SAP) Crustacea Ostracoda Cyprididae Cypretta Cypretta aff. globosa Crustacea Ostracoda Cyprididae Cypretta Cypretta baylyi Crustacea Ostracoda Cyprididae Cypretta Cypretta sp. 527 (SAP) Crustacea Ostracoda Cyprididae Cypretta Cypretta sp. 648 (=684 of SAP) Crustacea Ostracoda Cyprididae Cypricercus Cypricercus salinus Crustacea Ostracoda Cyprididae Cypricercus Cypricercus sp. 415 (=Bennelongia OS101) Crustacea Ostracoda Cyprididae Diacypris Diacypris compacta Crustacea Ostracoda Cyprididae Diacypris Diacypris dictyote Crustacea Ostracoda Cyprididae Diacypris Diacypris 'gunyidi' (ms name) (SAP) Crustacea Ostracoda Cyprididae Diacypris Diacypris spinosa Crustacea Ostracoda Cyprididae Heterocypris Heterocypris tatei Crustacea Ostracoda Cyprididae Ilyodromus Ilyodromus amplicolis Crustacea Ostracoda Cyprididae Ilyodromus Ilyodromus sp. 255 (south-west, CB)

Crustacea Ostracoda Cyprididae Ilyodromus Ilyodromus sp. 566 (aff. amplicolis) (south-west, SAP) Crustacea Ostracoda Cyprididae Ilyodromus Ilyodromus sp. 630 (SAP) Crustacea Ostracoda Cyprididae Lacrimicypris Lacrimicypris kumbar Crustacea Ostracoda Cyprididae Mytilocypris Mytilocypris ambiguosa Crustacea Ostracoda Cyprididae Mytilocypris Mytilocypris mytiloides Crustacea Ostracoda Cyprididae Platycypris Platycypris baueri Crustacea Ostracoda Cyprididae Reticypris Reticypris clava Crustacea Ostracoda Cyprididae Reticypris Reticypris sp. 556 (n. sp.) (SAP) Crustacea Ostracoda Cyprididae Reticypris Reticypris walbu Crustacea Ostracoda Cypridopsidae Sarscypridopsis Sarscypridopsis aculeata Crustacea Ostracoda Cypridopsidae Sarscypridopsis Sarscypridopsis aff. aculeata (165) (south-west, SAP) Crustacea Ostracoda Cytherideidae Cyprideis Cyprideis australiensis Crustacea Ostracoda Ilyocyprididae Ilyocypris Ilyocypris australiensis Crustacea Ostracoda Ilyocyprididae Ilyocypris Ilyocypris 'spiculata' (ms name) (SAP) Crustacea Ostracoda Leptocytheridae Leptocythere Leptocythere lacustris Crustacea Ostracoda Limnocytheridae Gomphodella Gomphodella aff. maia (SAP) Crustacea Ostracoda Limnocytheridae Limnocythere Limnocythere dorsosicula Crustacea Ostracoda Limnocytheridae Limnocythere Limnocythere mowbrayensis Crustacea Ostracoda Limnocytheridae Limnocythere Limnocythere sp. 447 (aff. porphyretica) (SAP) Crustacea Ostracoda Limnocytheridae Paralimnocythere Paralimnocythere sp. 262 (south-west) (ridged) Crustacea Ostracoda Notodromadidae Kennethia Kennethia cristata Crustacea Ostracoda Notodromadidae Kennethia Kennethia sp. 670 (SAP) Crustacea Ostracoda Notodromadidae Newnhamia Newnhamia sp. 295 (south-west, SAP) Crustacea Ostracoda Notodromadidae Newnhamia Newnhamia sp. FC (south-west, SAP) Desmospongiae - Spongillidae - Spongillidae Gastropoda Basommatophora Ancylidae Ferrissia Ferrissia petterdi Gastropoda Basommatophora Planorbidae Glyptophysa Glyptophysa sp Gastropoda Basommatophora Planorbidae Isidorella Isidorella sp. Gastropoda Neotaeniglossa Pomatiopsidae Coxiella Coxiella sp. Hirudinea - Glossiphoniidae Placobdelloides Placobdelloides sp. Hydrozoa - Clavidae Cordylophora Cordylophora sp. Hydrozoa - Hydridae Hydra Hydra sp.

Insecta Coleoptera Curculionidae - Curculionidae Insecta Coleoptera Dytiscidae Allodessus Allodessus bistrigatus Insecta Coleoptera Dytiscidae Antiporus Antiporus gilberti Insecta Coleoptera Dytiscidae Antiporus Antiporus occidentalis Insecta Coleoptera Dytiscidae Eretes Eretes australis Insecta Coleoptera Dytiscidae Hyderodes Hyderodes crassus Insecta Coleoptera Dytiscidae Hyphydrus Hyphydrus elegans Insecta Coleoptera Dytiscidae Lancetes Lancetes lanceolatus Insecta Coleoptera Dytiscidae Limbodessus Limbodessus inornatus Insecta Coleoptera Dytiscidae Limbodessus Limbodessus shuckhardi Insecta Coleoptera Dytiscidae Megaporus Megaporus howittii Insecta Coleoptera Dytiscidae Megaporus Megaporus solidus Insecta Coleoptera Dytiscidae Necterosoma Necterosoma penicillatus Insecta Coleoptera Dytiscidae Onychohydrus Onychohydrus scutellaris Insecta Coleoptera Dytiscidae Paroster Paroster niger Insecta Coleoptera Dytiscidae Rhantus Rhantus suturalis Insecta Coleoptera Dytiscidae Spencerhydrus Spencerhydrus pulchellus Insecta Coleoptera Dytiscidae Sternopriscus Sternopriscus browni Insecta Coleoptera Dytiscidae Sternopriscus Sternopriscus multimaculatus Insecta Coleoptera Dytiscidae Uvarus Uvarus pictipes Insecta Coleoptera Haliplidae Haliplus Haliplus fuscatus Insecta Coleoptera Heteroceridae - Heteroceridae Insecta Coleoptera Hydraenidae Ochthebius Ochthebius sp. Insecta Coleoptera Hydrochidae Hydrochus Hydrochus australis Insecta Coleoptera Hydrophilidae Berosus Berosus approximans Insecta Coleoptera Hydrophilidae Berosus Berosus discolor Insecta Coleoptera Hydrophilidae Berosus Berosus macumbensis Insecta Coleoptera Hydrophilidae Berosus Berosus munitipennis Insecta Coleoptera Hydrophilidae Enochrus Enochrus eyrensis Insecta Coleoptera Hydrophilidae Enochrus Enochrus maculiceps Insecta Coleoptera Hydrophilidae Helochares Helochares tenuistriatus Insecta Coleoptera Hydrophilidae Limnoxenus Limnoxenus zelandicus

Insecta Coleoptera Hydrophilidae Paracymus Paracymus pygmaeus Insecta Coleoptera Hydrophilidae Paranacaena Paranacaena littoralis Insecta Coleoptera Hygrobiidae Hygrobia Hygrobia wattsi Insecta Coleoptera Limnichidae - Limnichidae Insecta Coleoptera Scirtidae - Scirtidae Insecta Diptera Ceratopogonidae Atrichopogon Atrichopogon sp. 2 (SAP) Insecta Diptera Ceratopogonidae Atrichopogon Atrichopogon sp. 3 (SAP) Insecta Diptera Ceratopogonidae Bezzia Bezzia sp. Insecta Diptera Ceratopogonidae Clinohelea Clinohelea sp. Insecta Diptera Ceratopogonidae Culicoides Culicoides sp. Insecta Diptera Ceratopogonidae Monohelea Monohelea sp. Insecta Diptera Ceratopogonidae Nilobezzia Nilobezzia sp. Insecta Diptera Chironomidae - Orthocladiinae 'woodminer' (SAP) Insecta Diptera Chironomidae Ablabesmyia Ablabesmyia notabilis Insecta Diptera Chironomidae Chironomus Chironomus aff. alternans (V24) (CB) Insecta Diptera Chironomidae Chironomus Chironomus occidentalis Insecta Diptera Chironomidae Chironomus Chironomus tepperi Insecta Diptera Chironomidae Cladopelma Cladopelma curtivalva Insecta Diptera Chironomidae Cladotanytarsus Cladotanytarsus sp. A (SAP) Insecta Diptera Chironomidae Coelopynia Coelopynia pruinosa Insecta Diptera Chironomidae Compterosmittia Compterosmittia? sp. A (SAP) Insecta Diptera Chironomidae Corynoneura Corynoneura sp. Insecta Diptera Chironomidae Cricotopus Cricotopus albitarsus Insecta Diptera Chironomidae Cricotopus Cricotopus 'brevicornis' Insecta Diptera Chironomidae Cricotopus Cricotopus 'parbicinctus' Insecta Diptera Chironomidae Cryptochironomus Cryptochironomus griseidorsum Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes 'CA1' wheatbelt (was lindae) (SAP) Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes conjunctus Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes jobetus Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes pseudoconjunctus Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes sp. A (V47) (SAP) Insecta Diptera Chironomidae Kiefferulus Kiefferulus intertinctus

Insecta Diptera Chironomidae Kiefferulus Kiefferulus martini Insecta Diptera Chironomidae Limnophyes Limnophyes vestitus (V41) Insecta Diptera Chironomidae Paraborniella Paraborniella tonnoiri Insecta Diptera Chironomidae Parachironomus Parachironomus sp. 1 (VSCL35) (SAP) Insecta Diptera Chironomidae Paralimnophyes Paralimnophyes sp. Insecta Diptera Chironomidae Paramerina Paramerina levidensis Insecta Diptera Chironomidae Paratanytarsus Paratanytarsus sp. B (SAP) Insecta Diptera Chironomidae Polypedilum Polypedilum nr. convexum (SAP) Insecta Diptera Chironomidae Polypedilum Polypedilum nubifer Insecta Diptera Chironomidae Procladius Procladius paludicola Insecta Diptera Chironomidae Procladius Procladius sp. (normal claws) Insecta Diptera Chironomidae Procladius Procladius villosimanus Insecta Diptera Chironomidae S03 Orthocladiinae SO3 sp. C (V31) (SAP) Insecta Diptera Chironomidae Tanytarsus Tanytarsus barbitarsis Insecta Diptera Chironomidae Tanytarsus Tanytarsus fuscithorax/semibarbitarsus Insecta Diptera Chironomidae Tanytarsus Tanytarsus nr bispinosus (SAP) Insecta Diptera Culicidae Aedes Aedes camptorhynchus Insecta Diptera Culicidae Anopheles Anopheles annulipes s.l. Insecta Diptera Culicidae Coquillettidia Coquillettidia nr linealis Insecta Diptera Culicidae Culex Culex (Culex) australicus Insecta Diptera Culicidae Culex Culex (Neoculex) sp. 1 (SAP) Insecta Diptera Culicidae Culex Culex latus Insecta Diptera Dolichopodidae - Dolichopodidae Insecta Diptera Empididae - Empididae Insecta Diptera Ephydridae - Ephydridae sp. 1 (SAP) Insecta Diptera Ephydridae - Ephydridae sp. 3 (SAP) Insecta Diptera Ephydridae - Ephydridae sp. 5 (SAP) Insecta Diptera Ephydridae - Ephydridae sp. 6 (SAP) Insecta Diptera Muscidae - Muscidae sp. A (SAP) Insecta Diptera Psychodidae - Psychodinae sp. 2 (SAP) Insecta Diptera Psychodidae - Psychodinae sp. 3 (SAP) Insecta Diptera Scatopsidae - Scatopsidae

Insecta Diptera Sciomyzidae - Sciomyzidae Insecta Diptera Stratiomyidae - Stratiomyidae Insecta Diptera Syrphidae - Syrphidae Insecta Diptera Tabanidae - Tabanidae Insecta Diptera Tipulidae - Tipulidae type A (SAP) Insecta Diptera Tipulidae - Tipulidae type C (SAP) Insecta Ephemeroptera Baetidae Cloeon Cloeon sp. Insecta Ephemeroptera Caenidae Tasmanocoenis Tasmanocoenis tillyardi Insecta Hemiptera Corixidae Agraptocorixa Agraptocorixa eurynome Insecta Hemiptera Corixidae Agraptocorixa Agraptocorixa hirtifrons Insecta Hemiptera Corixidae Agraptocorixa Agraptocorixa parvipunctata Insecta Hemiptera Corixidae Diaprepocoris Diaprepocoris barycephala Insecta Hemiptera Corixidae Micronecta Micronecta gracilis Insecta Hemiptera Corixidae Micronecta Micronecta robusta Insecta Hemiptera Hebridae Hebrus Hebrus axillaris Insecta Hemiptera Hydrometridae Hydrometra Hydrometra strigosa Insecta Hemiptera Mesoveliidae Mesovelia Mesovelia horvathi Insecta Hemiptera Notonectidae Anisops Anisops baylii Insecta Hemiptera Notonectidae Anisops Anisops elstoni Insecta Hemiptera Notonectidae Anisops Anisops gratus Insecta Hemiptera Notonectidae Anisops Anisops hackeri Insecta Hemiptera Notonectidae Anisops Anisops hyperion Insecta Hemiptera Notonectidae Anisops Anisops thienemanni Insecta Hemiptera Notonectidae Paranisops Paranisops endymion Insecta Hemiptera Pleidae Paraplea Paraplea brunni Insecta Hemiptera Saldidae Saldula Saldula brevicornis Insecta Hemiptera Veliidae Microvelia Microvelia (Pacificovelia) oceanica Insecta Lepidoptera - - Lepidoptera (non-pyralid) sp. 3 (SAP) Insecta Neuroptera Sisyridae Sisyra Sisyra sp. Insecta Odonata Aeshnidae Adversaeshna Adversaeschna brevistyla Insecta Odonata Aeshnidae Hemianax Anax papuensis Insecta Odonata Coenagrionidae Austroagrion Austroagrion cyane

Insecta Odonata Coenagrionidae Ischnura Ischnura aurora aurora Insecta Odonata Coenagrionidae Xanthagrion Xanthagrion erythroneurum Insecta Odonata Hemicorduliidae Hemicordulia Hemicordulia tau Insecta Odonata Hemicorduliidae Procordulia Procordulia affinis Insecta Odonata Lestidae Austrolestes Austrolestes aleison Insecta Odonata Lestidae Austrolestes Austrolestes analis Insecta Odonata Lestidae Austrolestes Austrolestes annulosus Insecta Odonata Lestidae Austrolestes Austrolestes aridus Insecta Odonata Libellulidae Austrothemis Austrothemis nigrescens Insecta Odonata Libellulidae Diplacodes Diplacodes bipunctata Insecta Trichoptera Ecnomidae Ecnomina F group Ecnomina F group sp. AV16 (SAP) Insecta Trichoptera Ecnomidae Ecnomina F group Ecnomina F group sp. AV18 (SAP) Insecta Trichoptera Ecnomidae Ecnomina F group Ecnomina F group sp. AV20 (SAP) Insecta Trichoptera Ecnomidae Ecnomus Ecnomus pansus/turgidus Insecta Trichoptera Hydroptilidae Acritoptila Acritoptila globosa Insecta Trichoptera Hydroptilidae Hellyethira Hellyethira litua Insecta Trichoptera Leptoceridae Lectrides Lectrides sp. AV1 Insecta Trichoptera Leptoceridae Notalina Notalina spira Insecta Trichoptera Leptoceridae Notoperata Notoperata tenax Insecta Trichoptera Leptoceridae Oecetis Oecetis sp. Insecta Trichoptera Leptoceridae Symphitoneuria Symphitoneuria wheeleri Insecta Trichoptera Leptoceridae Triplectides Triplectides australis Insecta Trichoptera Leptoceridae Triplectides Triplectides niveipennis Oligochaeta Enchytraeida Enchytraeidae - Enchytraeidae Oligochaeta Opisthopora - - Opisthopora Oligochaeta Tubificida Naididae Ainudrilus Ainudrilus angustivasa Oligochaeta Tubificida Naididae Ainudrilus Ainudrilus nharna Oligochaeta Tubificida Naididae Chaetogaster Chaetogaster diaphanus Oligochaeta Tubificida Naididae Chaetogaster Chaetogaster diastrophus Oligochaeta Tubificida Naididae Dero Dero digitata Oligochaeta Tubificida Naididae Dero Dero furcata Oligochaeta Tubificida Naididae Dero Dero nivea

Oligochaeta Tubificida Naididae Paranais Paranais litoralis Oligochaeta Tubificida Phreodrilidae Insulodrilus Insulodrilus bifidus Oligochaeta Tubificida Pristinidae Pristina Pristina leidyi Oligochaeta Tubificida Pristinidae Pristina Pristina longiseta Turbellaria - - - Turbellaria Turbellaria Temnocephalidea Temnocephalidae Temnocephala Temnosewellia minor Turbellaria Temnocephalidea Temnocephalidae Zygopella Zygopella pista

Appendix 6: List of invertebrates identified in the 17 wetlands identified from 2010-2011.

Class Order Family Genus Species (Or Lowest order ID) Aphanoneura - Aeolosomatidae - Aeolosomatidae Arachnida Sarcoptiformes - - Oribatida sp. Arachnida Trombidiformes Limnocharidae Limnochares Limnochares australica Arachnida Trombidiformes Pezidae - Pezidae Crustacea Amphipoda Ceinidae Austrochiltonia Austrochiltonia subtenuis Crustacea Amphipoda Perthidae Perthia Perthia acutitelson Crustacea Anostraca Artemiidae Artemia Artemia parthenogenetica Crustacea Anostraca Branchipodidae Parartemia Parartemia longicaudata subspecies a (SAP) Crustacea Cladocera Chydoridae Alona Alona setigera Crustacea Cladocera Chydoridae Armatalona Armatalona macrocopa Crustacea Cladocera Chydoridae Kurzia Kurzia longirostris Crustacea Cladocera Daphniidae Daphnia Daphnia carinata Crustacea Cladocera Daphniidae Daphnia Daphnia wardi Crustacea Cladocera Daphniidae Scapholeberis Scapholeberis kingi Crustacea Cladocera Daphniidae Simocephalus Simocephalus elizabethae Crustacea Cladocera Ilyocryptidae Ilyocryptus Ilyocryptus spinifer Crustacea Cladocera Macrotrichidae Macrothrix Macrothrix breviseta Crustacea Copepoda - - Harpacticoida sp. 2 (SAP) Crustacea Copepoda Canthocamptidae - Australocamptus sp. 5 (SAP) Crustacea Copepoda Canthocamptidae Mesochra Mesochra nr flava

Crustacea Copepoda Centropagidae Calamoecia Calamoecia attenuata Crustacea Copepoda Centropagidae Calamoecia Calamoecia clitellata Crustacea Copepoda Centropagidae Calamoecia Calamoecia tasmanica subattenuata Crustacea Copepoda Centropagidae Gladioferens Gladioferens imparipes Australoeucyclops darwini (ex Paracyclops sp 1 nr Crustacea Copepoda Cyclopidae Australoeucyclops timmsi) Crustacea Copepoda Cyclopidae Macrocyclops Macrocyclops albidus Crustacea Copepoda Cyclopidae Meridiecyclops Meridiecyclops baylyi Crustacea Copepoda Cyclopidae Mesocyclops Mesocyclops brooksi Crustacea Copepoda Cyclopidae Paracyclops Paracyclops intermedius Crustacea Copepoda Laophontidae Onychocamptus Onychocamptus bengalensis Crustacea Decapoda Parastacidae Cherax Cherax preissii Crustacea Decapoda Parastacidae Cherax Cherax quinquecarinatus Crustacea Isopoda Oniscidae Haloniscus Haloniscus searlei Crustacea Ostracoda Candonidae Candonopsis Candonopsis tenuis Crustacea Ostracoda Cyprididae Alboa Alboa worooa Crustacea Ostracoda Cyprididae Australocypris Australocypris insularis Crustacea Ostracoda Cyprididae Candonocypris Candonocypris novaezelandiae Crustacea Ostracoda Cyprididae Cyprinotus Cyprinotus cingalensis (ex edwardi) Crustacea Ostracoda Cyprididae Diacypris Diacypris compacta Crustacea Ostracoda Cyprididae Lacrimicypris Lacrimicypris kumbar Crustacea Ostracoda Cyprididae Mytilocypris Mytilocypris mytiloides Crustacea Ostracoda Cyprididae Platycypris Platycypris baueri Crustacea Ostracoda Cypridopsidae Sarscypridopsis Sarscypridopsis aculeata Crustacea Ostracoda Cytherideidae Cyprideis Cyprideis australiensis Crustacea Ostracoda Leptocytheridae Leptocythere Leptocythere lacustris Crustacea Ostracoda Limnocytheridae Gomphodella Gomphodella aff. maia (SAP) Crustacea Ostracoda Limnocytheridae Limnocythere Limnocythere porphyretica Crustacea Ostracoda Notodromadidae Kennethia Kennethia cristata Crustacea Ostracoda Notodromadidae Newnhamia Newnhamia fenestrata Gastropoda - Hydrobiidae Ascorhis Ascorhis occidua Gastropoda Basommatophora Planorbidae Glyptophysa Glyptophysa sp

Gastropoda Neotaeniglossa Pomatiopsidae Coxiella Coxiella sp. Hydrozoa - Hydridae Hydra Hydra sp. Insecta Coleoptera Dytiscidae Lancetes Lancetes lanceolatus Insecta Coleoptera Dytiscidae Limbodessus Limbodessus shuckhardi Insecta Coleoptera Dytiscidae Necterosoma Necterosoma penicillatus Insecta Coleoptera Dytiscidae Spencerhydrus Spencerhydrus pulchellus Insecta Coleoptera Dytiscidae Sternopriscus Sternopriscus storeyi Insecta Coleoptera Hydraenidae Gymnochthebius Gymnocthebius sp. 1 (SAP) Insecta Coleoptera Hydrophilidae Berosus Berosus australiae Insecta Coleoptera Hydrophilidae Berosus Berosus discolor Insecta Coleoptera Hydrophilidae Berosus Berosus majusculus Insecta Coleoptera Hydrophilidae Helochares Helochares tenuistriatus Insecta Coleoptera Hydrophilidae Paracymus Paracymus pygmaeus Insecta Coleoptera Scirtidae - Scirtidae Insecta Diptera Ceratopogonidae Bezzia Bezzia sp. Insecta Diptera Ceratopogonidae Clinohelea Clinohelea sp. Insecta Diptera Ceratopogonidae Culicoides Culicoides sp. Insecta Diptera Ceratopogonidae Nilobezzia Nilobezzia sp. Insecta Diptera Chironomidae - Pentaneurini genus C Insecta Diptera Chironomidae Alotanypus Alotanypus dalyupensis Insecta Diptera Chironomidae Chironomus Chironomus aff. alternans (V24) (CB) Insecta Diptera Chironomidae Chironomus Chironomus occidentalis Insecta Diptera Chironomidae Cladopelma Cladopelma curtivalva Insecta Diptera Chironomidae Corynoneura Corynoneura sp. Insecta Diptera Chironomidae Cryptochironomus Cryptochironomus aff griseidorsum Insecta Diptera Chironomidae Cryptochironomus Cryptochironomus griseidorsum Insecta Diptera Chironomidae Dicrotendipes Dicrotendipes conjunctus Insecta Diptera Chironomidae Parachironomus Parachironomus sp. 1 (VSCL35) (SAP) Insecta Diptera Chironomidae Paralimnophyes Paralimnophyes sp. Insecta Diptera Chironomidae Paramerina Paramerina levidensis Insecta Diptera Chironomidae Procladius Procladius paludicola Insecta Diptera Chironomidae Procladius Procladius sp. (normal claws)

Insecta Diptera Chironomidae Tanytarsus Tanytarsus barbitarsis Insecta Diptera Chironomidae Tanytarsus Tanytarsus bispinosus Insecta Diptera Chironomidae Tanytarsus Tanytarsus fuscithorax Insecta Diptera Chironomidae Tanytarsus Tanytarsus semibarbitarsus Insecta Diptera Culicidae Aedes Aedes camptorhynchus Insecta Diptera Culicidae Anopheles Anopheles atratipes Insecta Diptera Culicidae Coquillettidia Coquillettidia linealis Insecta Diptera Culicidae Culex Culex latus Insecta Diptera Dolichopodidae - Dolichopodidae Insecta Diptera Ephydridae - Ephydridae sp. 5 (SAP) Insecta Diptera Sciomyzidae - Sciomyzidae Insecta Diptera Stratiomyidae - Stratiomyidae Insecta Diptera Tipulidae - Tipulidae type A (SAP) Insecta Hemiptera Corixidae Micronecta Micronecta robusta Insecta Hemiptera Notonectidae Anisops Anisops thienemanni Insecta Hemiptera Notonectidae Notonecta Notonecta handlirschi Insecta Hemiptera Veliidae Microvelia Microvelia (Pacificovelia) oceanica Insecta Odonata Aeshnidae Adversaeshna Adversaeschna brevistyla Insecta Odonata Aeshnidae Hemianax Anax papuensis Insecta Odonata Coenagrionidae Xanthagrion Xanthagrion erythroneurum Insecta Odonata Lestidae Austrolestes Austrolestes analis Insecta Odonata Lestidae Austrolestes Austrolestes annulosus Insecta Odonata Lestidae Austrolestes Austrolestes io Insecta Odonata Libellulidae Austrothemis Austrothemis nigrescens Insecta Trichoptera Ecnomidae Ecnomina F group Ecnomina F group sp. AV16 (SAP) Insecta Trichoptera Ecnomidae Ecnomus Ecnomus pansus/turgidus Insecta Trichoptera Hydroptilidae Hellyethira Hellyethira litua Insecta Trichoptera Leptoceridae Notoperata Notoperata tenax Insecta Trichoptera Leptoceridae Oecetis Oecetis sp. Insecta Trichoptera Leptoceridae Symphitoneuria Symphitoneuria wheeleri Oligochaeta Enchytraeida Enchytraeidae - Enchytraeidae Oligochaeta Tubificida Naididae Antipodrilus Antipodrilus davidis

Oligochaeta Tubificida Naididae Paranais Paranais litoralis Oligochaeta Tubificida Pristinidae Pristina Pristina leidyi Oligochaeta Tubificida Pristinidae Pristina Pristina longiseta