Arthur Rylah Institute Technical Report Series

Arthur Rylah Institute for Environmental Research Technical Report No. 175

POTENTIAL BIOLOGICAL INDICATORS OF CLIMATE CHANGE: EVIDENCE FROM PHENOLOGY RECORDS OF PLANTS ALONG THE VICTORIAN COAST

Libby Rumpff1, Fiona Coates2,Andre Messina1 and John Morgan1

1Department of Botany, La Trobe University 2Arthur Rylah Institute for Environmental Research, Department of Sustainability and Environment

May 2008

Published by the Victorian Government Department of Sustainability and Environment Melbourne, August 2008 © The State of Victoria Department of Sustainability and Environment 2008 This publication is copyright. No part may be reproduced by any process except in accordance with the provisions of the Copyright Act 1968. Survey and monitoring recommendations contained in the report remain the intellectual property of the authors. Authorised by the Victorian Government, 8 Nicholson Street, East Melbourne. ISBN 978-1-74208-704-7 (print) ISBN 978-1-74208-705-4 (PDF) For more information contact the DSE Customer Service Centre 136 186

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CONTENTS

LIST OF TABLES ...... 2 LIST OF FIGURES...... 2 EXECUTIVE SUMMARY...... 1 INTRODUCTION...... 2 Phenology and the impacts of climate change...... 2 Phenological indicators of climate change ...... 3 Sources of phenological data to assess plant responses to climate change...... 3 Addressing the challenge in Australia ...... 7 Rationale for the present study...... 10 AIMS AND OBJECTIVES ...... 10 METHODS...... 11 Site selection and analysis of climate change ...... 11 The coastal species list...... 11 Sources of phenological data ...... 12 Determination of indicator species using herbarium records...... 14 Analysis...... 16 Collation of data ...... 16 RESULTS ...... 17 Climate data ...... 17 Potentially useful indicator species...... 19 Omitted species...... 25 DISCUSSION ...... 27 Functional groups...... 28 Suitability for monitoring...... 29 Availability and accuracy of data...... 29 Additional sources of biological data...... 31 CONCLUSION: Knowledge gaps, future research and community involvement...... 32 Acknowledgments ...... 33 REFERENCES...... 34 APPENDIX ONE ...... 37

LIST OF TABLES

Table 1 Examples of uses of herbarium/museum records in biological studies...... 4 Table 2 Potential sources of phenological data for native species in Australia...... 9 Table 3. Trends in mean summer and winter minimum and maximum temperatures (oC/year), and mean summer and winter precipitation levels (mm/year), 1910–2006...... 18 Table 4. Summary of the species identified as being potentially suitable as Indicator Species of climate change...... 20 Table 5. Results of the linear regression analysis: flowering dates (Julian dates) ~ time...... 20

LIST OF FIGURES

Figure 1. Plots of phenological observations over time for useful indicator species. Phenological key: black (flowering), dark pink (flowering and fruiting), light pink (flowering and budding), blue (fruiting), green (budding), red (fertile), and yellow (unknown status). Lines of best-fit are for flowering observations only...... 23 Figure 3. Observations of flowering in orchid species over time. Phenological key: black (flowering), blue (fruiting), and green (budding)...... 26

EXECUTIVE SUMMARY

There is a pressing need to collate data that might assist with understanding the ecological effects of climate change in south-eastern Australia. There is much evidence in the scientific literature that changes in the timing of events such as flowering is one likely consequence of climate change. This project investigated the potential for using herbarium records, combined with other data sources, to track changes in the time of flowering of Victorian coastal species in response to recent climate warming.

The main findings of the project were:

¾ There is great potential to utilize data sourced from herbaria, and elsewhere (e.g. naturalist diaries), to identify native plant species suitable as bioindicators of climate change, and to provide background historical data for comparison of future observations. ¾ Of the 105 candidate species investigated in this study, 12 species were identified as useful indicator species to track future changes due to climate warming. ¾ There is some evidence to suggest that species which flower in late-winter to early-spring may be more sensitive to changes in temperature than species with a wider flowering period. ¾ Issues with using herbaria records, in combination with other sources to select indicator species, lies in the accuracy and availability of data. It is proposed that this could be resolved by combining these data sets with detailed studies of phenological cycles in climatically different locations. ¾ Further attention needs to be directed toward collating and digitizing records held within the community, i.e. field naturalist notes. Additionally, it is proposed that future monitoring of indicator species might best be achieved by working with coastal community groups, and facilitated by setting up a phenological observation database.

1 INTRODUCTION

Phenology and the impacts of climate change

‘Phenology’ is the study of natural cyclic events and it typically refers to the observation of life cycle changes in plants and animals over time (Menzel 2002). It has long been recognised that phenological cycles are often strongly influenced by changes in climate, particularly temperature and rainfall (de Groot, Ketner et al. 1995; Hughes 2000; Menzel 2002; Chambers 2006; Penuelas and Filella 2007; Rosenzweig, Karoly et al. 2008) and hence, these changes may inform us about how plants are responding to a climate changed world. Although we have some information on how climate change may affect the phenology of plant species, there is still a dearth of knowledge in this area in Australia.

Numerous (mostly Northern Hemisphere) studies have collated information on global changes in phenological events in response to recent climate change (Hughes 2000; Walther, Post et al. 2002; Hughes 2003; Parmesan and Yohe 2003; Root, Price et al. 2003; Chambers 2006; Parmesan 2007; Miller-Rushing and Primack 2008; Rosenzweig, Karoly et al. 2008). A recent study of 28 880 records of (mostly phenological) changes in biological systems throughout the world in the past 30 years has shown that 90% of the changes are consistent with changes in temperature (Rosenzweig, Karoly et al. 2008). Climate change due to greenhouse gas emissions over the past 50 years is more likely to have caused these changes rather than natural climatic variability (Rosenzweig, Karoly et al. 2008).

The effect of climate change on plant phenological cycles can include changes in onset of new growth or flowering times, the production and viability of seed, and in the number of reproductive events per growing season (de Groot, Ketner et al. 1995; Hughes 2003; Inouye 2008). The potential feedback effects of these changes on ecological systems are enormous (Kagata and Yamamura 2006; Dahlgren, Zeipel et al. 2007; Penuelas and Filella 2007; Miller- Rushing and Primack 2008), as changes in plant and animal interactions can ultimately alter species composition, mutualisms, abundance and range (Inouye and McGuire 1991; Hughes 2000). It is crucial that we make a concerted effort to understand these effects as there are likely important implications for conservation and management of natural ecosystems. These implications range from how rare and endangered species, pests, or even entire habitats are managed, to identifying which species are likely to become extinct in the near future.

2 Phenological indicators of climate change

Attention has recently been directed toward assessing species that have exhibited phenological changes as a result of climatic change (Menzel, Estrella et al. 2001; Menzel 2002; Walther, Post et al. 2002; Dahlgren, Zeipel et al. 2007; Miller-Rushing and Primack 2008). One of the main challenges is to identify species that are useful indicators of climate change, i.e. those species that “respond predictably and sensitively, in ways that are easily observed and quantified” (Hughes 2003b: 1), and can act as surrogates for understanding other species responses to climate change in the same system. Ideally, species that respond primarily to temperature and are not influenced by biotic, edaphic and other climatic interactions (Menzel 2002) that display large inter-annual variation (e.g. rainfall), are likely to be the most likely candidates for following climate change. Indicator species selection can be a difficult task because variability in plant species responses with the environment is largely inevitable. Phenology may not only be cued by temperature, but also vary in relation to photoperiod, precipitation, soil nutrient content and the resource state of the plant (Dahlgren, Zeipel et al. 2007). In addition, if a species has a wide geographical distribution, phenological changes may vary with altitude, latitude (Hughes 2003), genetic differentiation, land-use changes or disturbance (Rosenzweig, Karoly et al. 2008). Consequently we may not necessarily see correlations between phenology and climatic factors such as temperature (Hughes 2000; Menzel 2002; Stenseth and Mysterud 2002; Dahlgren, Zeipel et al. 2007).

Sources of phenological data to assess plant responses to climate change

Long-term monitoring of plant species in different habitats is invaluable for detecting trends in response to climate change, and identifying which species might be most affected by these changes. Unfortunately, continuous and systematically collected long-term phenological data sets for a variety of ecosystems are rare (Ledneva, Miller-Rushing et al. 2004), and the majority of studies have relied on short-term local data collections from scientific studies (Root, Price et al. 2003; Ledneva, Miller-Rushing et al. 2004). Irregularities in data collection can make it difficult to extrapolate a clear climate change signal, or to disentangle short-term and long-term environmental stochasticity and population processes (Walther, Post et al. 2002; Ledneva, Miller- Rushing et al. 2004).

3 Using herbarium specimens to track environmental change

A particularly useful way to investigate environmental change at multiple spatial and temporal scales is to examine scientific collections held in herbaria and museums (Anonymous 1998; Primack, Imbres et al. 2004; Bolmgren and Lonnberg 2005; Coleman and Brawley 2005). Many herbaria specimens, for example, date back decades and even centuries and these long- term records can provide valuable information on species relationships, distribution and ecology (Anonymous 1998).

This data source will generally be of good quality because collections are checked regularly for their scientific accuracy by specialists, (Ponder, Carter et al. 2001; Delisle, Lavoie et al. 2003). Depending on the quality and qauntity of the records, these data may be used as an alternative or supplement to scientific field studies (Vasseur, Guscott et al. 2001), and can provide insight into broad-scale long-term trends that would otherwise be unachievable due to time (and cost) constraints (Bolmgren and Lonnberg 2005).

Herbarium and museum records are commonly used in taxonomic, systematic and biogeographical studies as well as information on the distribution and habitat of organisms (Bolmgren and Lonnberg 2005)(Table 1). These collections contain (often detailed) information on collection date, location, habitat, life-form, abundance, co-occurring species and reproductive state. However, the relevance of such collections to wider ecological, conservation and other biological studies has been, until now, largely underappreciated in Australia.

Table 1 Examples of uses of herbarium/museum records in biological studies.

Type of study Information required Example Taxonomic/systematic Morphological measurements/ (Cayzer, Crisp et al. 1999) material for molecular analysis

Biodiversity assessment Number of species/endemics (Fagan and Kareiva 1997) occurring in an area over time. Comparing past and present number of species to find areas of conservation priority.

Species conservation Species distribution over time, (Burgman, Grimson et al. status and habitat requirements 1995)

Spread of invasive species Species distribution over time (Delisle, Lavoie et al. 2003)

Comparative phenology Timing of events (such as (Bolmgren and Lonnberg flowering) between species 2005) over time

Climate change — shifts in Flowering time of species over (Primack, Imbres et al. 2004)

4 flowering time time

Climate change — bird Laying time in birds over time (Both, Artemyev et al. 2004) breeding time

More recently, natural history records contained within herbarium specimens have been used to gain information on the phenology of organisms (Borchert 1996; Clark and Thompson 2004; Bolmgren and Lonnberg 2005). Information extracted from records (e.g. flowering dates, the appearance of animals) can enable us to track the phenology of organisms over time. This information can be combined with other data sources (such as temperature) to investigate how species respond to biotic and abiotic changes (Inouye and McGuire 1991; Vasseur, Guscott et al. 2001; Walther, Post et al. 2002). From this, we can extrapolate to determine the effect these changes may have on communities and ecosystems (Winder and Schindler 2004; Coleman and Brawley 2005; Kudo and Hirao 2006). Additionally, it allows us to identify useful biological indicators of climate change for future monitoring (Borchert 1996; Menzel 2002; Hughes 2003; Primack, Imbres et al. 2004).

Limitations

Caution is required when using herbarium and museum records to track biological changes, as these records are generally collected in an ad hoc manner, often without the strict sampling design associated with most scientific studies (Ponder, Carter et al. 2001). For instance, certain geographic areas may be sampled more intensively than others, with easily accessible areas (i.e. along or near tracks) representing a greater proportion of the data than more remote or difficult to access areas (Fagan and Kareiva 1997; Ponder, Carter et al. 2001). When the temporal span of records are considered, it is common to find gaps in the data due to variation in collection effort over time (MacDougall, Loo et al. 1998; Primack, Imbres et al. 2004; Bolmgren and Lonnberg 2005; Miller-Rushing and Primack 2008). For example, when a species undergoes a taxonomic review, a high proportion of records of that species may come from a relatively short period of field studies.

The time of collection can also be a source of error when trying to collate phenological information. Collections of species are often made during single trips, so the phenological stage of interest (i.e. first buds, first flowers) for every species will not be represented in the one collection (Bolmgren and Lonnberg 2005). Finally, consistency in data has been affected by a shift in the type of taxa collected for herbariums and museums. As confidence in taxonomic classification has improved, the collection of more common species has declined. The emphasis is now on collecting specific taxa, such as rare species (Burgman, Grimson et al. 1995).

5 However, over a longer time frame, common species are well represented in collections, while more inconspicuous, rare or weed species are not (Rich and Woodruff 1992; Delisle, Lavoie et al. 2003; Bolmgren and Lonnberg 2005).

Despite these problems, with careful screening of data, there is a great potential to further utilise these data sources to examine relationships between the phenology of plants and changing climates. Obviously, larger data sets have a greater chance of detecting biological changes in species. Alternatively, recent studies have focused on the analysis of phenological changes of multiple species and multiple locations (Menzel, Estrella et al. 2001; Gordo and Sanz 2005; Menzel, Sparks et al. 2006; Menzel, Sparks et al. 2006; Miller-Rushing, Primack et al. 2006; Miller-Rushing and Primack 2008) to increase the likelihood of detecting change in communities or ecosystems, and over greater spatial scales.

Looking beyond scientific collections

The availability of data to infer changes in species behaviour over time extends beyond the realm of scientific collections and publications. For centuries people have been collecting and recording information regarding the timing of life cycle changes in animals and plants. For instance, recording phenological observations is a very popular past-time for naturalists (Sparks and Carey 1995). Some of this data is available in herbaria, but there is potentially a much larger source of information held within the community by individuals or field naturalist organisations (Sparks and Carey 1995; Menzel, Estrella et al. 2001; Vasseur, Guscott et al. 2001; Whitfield 2001; Ledneva, Miller-Rushing et al. 2004; Miller-Rushing and Primack 2008). For example, field journals and drawings/photos by naturalists may provide similar information to that within herbarium records (Ledneva et al. 2004). This sort of information may also be found compiled into the newsletters of local field naturalist organisations. Local newspapers may also offer insight into biodiversity and distributions of species in areas where people have been interested in wildlife (Vuorisalo, Lahtinen et al. 2001).

It is only relatively recently that scientists have focused on utilising this data source (Sparks and Carey 1995; Whitfield 2001; Ledneva, Miller-Rushing et al. 2004). Careful screening of data is required because there can be problems with the reliability and accuracy of the data source (Whitfield 2001; Ledneva, Miller-Rushing et al. 2004). However, the utility of these data sources may be improved when combined with field data sets or scientific studies of species phenological cycles (Primack, Imbres et al. 2004; Miller-Rushing, Primack et al. 2006; Dahlgren, Zeipel et al. 2007). By collating all possible sources of data, we can improve consistency in long-term records

6 and increase the potential for detecting phenological changes (Kagata and Yamamura 2006; Miller-Rushing, Primack et al. 2006).

Future monitoring: phenological observation networks

An excellent way to systematically bring all of these data sources together and maintain a connection with the community is via well-publicised phenological observation networks. These networks focus on previously identified indicator species and address the need for the continued collection of data for future monitoring. This is particularly pertinent if further information is required to investigate interactions with environmental variables other than climate. The opportunity then arises to build or test detailed phenological models and more accurately predict future responses to climate change (Dahlgren, Zeipel et al. 2007).

These networks are a relatively recent worldwide phenomenon and rely on individuals or groups to register and submit phenological observations to a central database. They are a vital tool for maintaining a continuous data record into the future, and can provide important baseline phenological data with which past records can be compared (Chambers 2006; Miller-Rushing, Primack et al. 2006). In addition to being an inexpensive and easy form of data collection, the data have the added advantage of being easily communicated to and understood by the general public (Menzel 2002; Chambers 2006). It is a great opportunity to access, involve and publicise some of the knowledge held within the wider community.

Addressing the challenge in Australia

Climatic changes in line with those recorded globally have been documented in Australia (IPCC 2001), with an increase in average continental temperature by 0.8 °C since 1910, mostly since the 1950s (Hughes 2003). The ecological effects of recent warming have been noted in some ecosystems in Australia (Howden, Hughes et al. 2003; Hughes 2003), but there is still a great deal of work to be done in documenting these changes and identifying suitable biological indicators for future monitoring of climate change (Hughes 2003; Chambers 2006; Rosenzweig, Karoly et al. 2008). In 2003 the Australian Greenhouse Office noted that ‘work is still desirable on designing and implementing long-term monitoring programs that cover vulnerable animals, plants and ecosystems, and systematically examine them for the effects of climate changes’ (Pittock 2003: 185).

It is evident that most studies of phenology using long-term records are from the Northern Hemisphere, with very few from Australia (Keatley, Fletcher et al. 2002; Hughes 2003;

7 Environmental Systems Analysis Group 2004; Chambers 2006; Rosenzweig, Karoly et al. 2008). The lack of research can partly be blamed on a paucity of quality long-term data sets (Hughes 2003; Rosenzweig, Karoly et al. 2008). Hence, we are not in a position to yet quantify the rate and direction of response to climate change by Australian native plants.

The need to address this data shortage has not been ignored and there are a growing number of studies investigating the relationship between phenological events and climatic variability in Australia. For instance, a 10-year study by Law et al. (2000) investigated the relationship between climatic variability, disturbance and site characteristics on the phenological behaviour of 20 Eucalyptus species. Keatley et al. (2002) used forestry datasets over a 23-year period to demonstrate changes in the flowering of Eucalyptus species in response to variability in temperature and precipitation. In addition, a phenological observation network (Biowatch) has been established by Macquarie University in Sydney (Rice 2003) and another (TreeTime) is under construction at the Australian Research Centre for Urban Ecology at Melbourne University. The Biowatch database concentrates on a range of bird and plant species that are easily identifiable and are likely to be good biological indicators of climate change. There is great potential in Australia for an expansion of this concept (Chambers 2006; Rosenzweig, Karoly et al. 2008) to incorporate a broader range of species and ecosystems.

There are a number of potential sources of phenological information for native plants that can be harnessed in Australian studies (Table 2). Some of these have been partially explored, but concerted efforts could be made to initiate or further investigate these data sets. The scope for use of records held within herbaria, museums and by individuals and community groups has already been discussed. These long-term data sets may also be held within archives in botanic gardens (e.g. the Royal Society of Tasmania gardens in Hobart), and libraries (e.g. Jean Galbraith’s notes and diaries, State Library of Victoria). Information may also be collated from within scientific journals (i.e. Proceedings of the Royal Society of Victoria), newsletters from local naturalists groups, or from individuals within the community (Table 2).

The further potential for data exploration within the agriculture and forestry industries is acknowledged in the Australia literature (Keatley, Fletcher et al. 2002; Hughes 2003). It is possible that data collected over a great spatial and temporal scale is available with regard to monitoring phenological cycles in economically important native plants (i.e. from the apiary, forestry and possibly the native floriculture industry). Data may be sourced from government records and archives, but also from individuals such as beekeepers.

8 One major concern is that unless we collate the findings from the many disparate studies and sources of information that currently exist, we perpetuate the problem of not knowing what data sources exist in Australia, which in turn hinders efforts to detect and attribute changes in phenological events to climate change (Chambers 2006). As a result, a concerted effort is now being made to document and publicise this information through a National Ecological Meta Database (Bureau of Meteorology, Australian Greenhouse Office et al. 2008). This database is still in the early stages of collating available information, but there is an obvious need for further phenological studies to increase our understanding of the effects of climate change on a wider variety of ecosystems.

Table 2 Potential sources of phenological data for native species in Australia.

Source Australian Example Reference Herbariums/Museums Developing a database of (Messina and Morgan 2008 phenological records for alpine unpublished data) species Botanic gardens Phenological observations (Clark and Thompson 2004) (i.e. from 1858–1885, Royal Society of Tasmania Gardens, Hobart) Libraries Collections of naturalists State Library of Victoria, diaries, notes, illustrations Melbourne Scientific Journals Scientific studies of (Law, Mackowski et al. 2000) phenological variation in relation to climate Forestry Industry Records of flowering in (Keatley, Fletcher et al. 2002) Eucalyptus species Apiary Industry Observations of frequency, (Birtchnell and Gibson 2006) timing, duration and intensity of flowering in Eucalyptus species by commercial apiarists Horticulture/Floriculture N/A N/A Industry Community groups and Collating notes on Bairnsdale and district field naturalists observations from field naturalists excursions, noted in diaries, newsletters and journals (e.g. The Clematis) Indigenous knowledge Indigenous weather (BoM 2002) knowledge: tracking seasonal changes based on natural events (i.e. phenological cycles)

9 Rationale for the present study

There is evidence in the scientific literature and public domain of correlations between climate change, including global warming and El Niño events, and various biological indicators such as the timing of flowering. At present, there is a need to collate data that might assist with understanding the ecological effects of climate change in south-eastern Australia. This present study examines the potential of using phenological records held within herbaria and the wider community to detect evidence of recent climate change in plant functioning. This information will contribute to an understanding of global trends affecting the conservation of biodiversity, and will provide valuable information for future scientific and community efforts by establishing baseline data that can be extended into the future with on-going observation.

AIMS AND OBJECTIVES

This project investigates using biological indicators in the Victorian coastal environment that may provide correlative evidence for climate change by collating existing botanical information and data from a variety of sources including herbaria, Department of Sustainability and Environment databases, and knowledge held within the greater community. The main aims of the project were as follows:

- Collate the historical timing of phenological events in Victoria’s coastal flora (where sufficient data exist). - Assess which species or functional groups (i.e. shrubs, herbs, orchids) may be most sensitive to climate change. - Identify additional sources of biological data outside of herbaria that deserve further attention. - Identify strategic knowledge gaps and recommend areas of future research and community involvement.

10 METHODS

Site selection and analysis of climate change

We chose coastal vegetation communities for this project to illustrate the utility of using plant phenological records to track biological responses to climate change. We chose coastal areas reasons because they have a long history of occupation and hence, botanical data collection, there area number of active local field naturalist groups in coastal Victoria that represent an untapped resource of information, and there was a reduced chance of phenological variability in plant responses to climate change due to the edaphic similarity and low altitudinal differences common to most areas along the coast.

It was initially assumed that the general climate changes documented for Australia over the last few decades (Hughes 2003) are also evident in coastal areas. We analysed climate data to examine the strength and consistency of these trends using temperature and precipitation data from five Victorian coastal weather stations for which long-term records are available (Cape Nelson Lighthouse, Cape Otway Lighthouse, Melbourne Regional Office, Wilsons Promontory Lighthouse, and Gabo Island Lighthouse). Data were obtained from the Bureau of Meteorology (Bureau of Meteorology 2007). Linear regressions of mean monthly minimum and maximum temperature trends over time were calculated for summer (December–March) and winter (June– August) periods for each station. The same analysis was repeated for total monthly precipitation data. Regressions of climate data over time were analysed for the periods 1910–2006, 1950– 2006, and 1980–2006 to compare the slope of the regression line, and evidence of trends with time. Analysis was carried out using the statistical program R (R Development Core Team 2006).

The coastal species list

The first step in identifying useful indicators of climate change was to obtain a manageable list of plant species that were restricted to coastal areas, as a basis for searches of herbarium and community group records. Species whose distributions extend beyond coastal areas have an increased likelihood of adaptation to a variety of environmental conditions and therefore, may vary greatly in phenological behaviour.

11 EVC benchmark species

The coastal area in Victoria was first identified according to nine bioregions: Bridgewater, Warnambool Plain, Otway Plains, Otway Ranges, Glenelg Plain, Victorian Volcanic Plain, Wilsons Promontory, Gippsland Plains and the East Gippsland Lowlands. A list of ecological vegetation classes (EVCs) for each bioregion was then obtained from the DSE website, along with the benchmark species for each bioregion (Department of Sustainability and Environment 2007). Twenty coastal EVCs were identified (Appendix 1), with a total of 297 benchmark species.

Database searches: FIS

The benchmark species were mapped on DSE’s Flora Information System (FIS) and analysed according to their distribution across the state. Species that were not predominantly restricted to the coast were rejected. The remaining species were then classified broadly according to their spatial distribution in Victoria as ‘widespread’, ‘intermediate’ or ‘local’. Species were additionally noted as ‘abundant’ or ‘restricted’ depending on the number of records on the FIS.

After this initial review the list of plant species was reduced to 30 key species (Appendix 1). It was anticipated that this list would represent a group of common coastally-restricted species but would largely overlook rare or locally restricted species. To obtain a more extensive list of species, these 30 species were re-plotted on the FIS, and all neighbouring species recorded in the FIS quadrats were noted. This gave a further 1153 species, which were sorted according to distribution, flowering times, number of records and conservation status. This resulted in the identification of a further 75 key coastal species, giving a total of 105 candidate species for initial herbarium searches (Appendix 1).

Sources of phenological data

Next, we identified sources of phenological data to be used in this study. This included herbarium records, Victorian Rare or Threatened Population (VROTpop) data, and individuals and organisations.

12 Herbarium data

Data were obtained initially from the Royal Botanic Gardens Melbourne’s MELISR database. Records that did not have at least month and year recorded at the time of collection were omitted, as were records that did not record a location more precise that the state of Victoria.

Records were then assessed according to phenological information. This information may be copied verbatim from the collector's notes, or it may have been added by the person identifying the specimen or entering it on the database (e.g. whether a specimen is in flower, bud, or fruit, or if it is fertile or sterile). This latter information may not always be accurate or detailed, and records are flagged only when the reproductive status of the plant is obvious. For example, reproductive structures on grasses are usually flagged only as 'fertile' in the database. In such an instance the record was retained only if the phenological status of the plant was certain.

Data was then added from the Melbourne University Herbarium collection, and the La Trobe University Herbarium collection following the same procedure. As an important note, some species had been renamed, or further classified into subspecies. With reference to the MELISR database, these species are checked (or ‘determined’) by a botanist, and noted in the record. This is often, but not always, the case at the University herbaria. As a result, species names were checked on the Australian Plant Name Index (Australian National Herbarium, Australian National Botanic Gardens et al. 2005) to obtain the history of classification. Searches were also completed using prior names. If a species had been determined by a botanist since the last date of classification, the record was retained. If the species was still recorded under the prior name and had not been determined since, care had to be taken to decide whether the record was of use. In particular, species that had been split into separate species, subspecies or varieties after the date of determination of a particular record were generally not considered reliable and were omitted.

VROTpop data

Searches of the VROTpop database were made to obtain additional records of species. Records were retained only if the species was stated to be flowering at time of survey.

Data from organisations or individuals

A list of coastal community groups was obtained from the Environment Victoria website (Environment Victoria 2003). These groups were contacted to investigate the possibility of

13 accessing information held within their community. Members of ANGAIR Incorporated (Anglesea field naturalist group), Traralgon Field Naturalists, Bairnsdale Field Naturalists and the South Gippsland Conservation Society were contacted regarding phenological information collected by individuals or groups within the organisations.

Additional long-term data records were located, and data was collected from records kept by Terri Allen (South Gippsland Conservation Society) and Bon Thompson (Traralgon Field Naturalists), and from Eulalie Hill (South Gippsland Conservation Society) who has records kept by Ellen Lyndon (now deceased). Some data was also collected from newsletters of ANGAIR Incorporated. The availability and accuracy of data sources are discussed later in this report.

Determination of indicator species using herbarium records

Initially, the suitability of indicator species was investigated using herbarium records. As an exception, long-term data sets (from Terri Allen and Bon Thompson) were available for orchid species that occur along the Victorian coast but were not detected in FIS searches (i.e. Caladenia aurantica, Caladenia latifolia, Corybas unguiliculatus, Corybas fimbriatus and Pterostylis pedoglossa). Special mention is made of orchid species here because they are potentially useful indicator species of phenological change because (a) orchid collection and observation is a very popular past-time, so it is likely that a large number of records exist, (b) flowering generally occurs over a short time, so it is easier to detect any changes in flowering times over time, and (c) the identification and observation of orchids largely relies on the flower, so even if detailed phenological notes are not kept by an observer it is highly likely that most records will be flowering records.

The data obtained were used to identify a list of indicator species to aid in further collection of data from other sources. This list was based on criteria developed for the selection of potential biological indicators of climate change (de Groot, Ketner et al. 1995), which we modified slightly to refer to phenological indicators only, as follows:

1. Climate sensitivity The species should be sensitive primarily to climate (i.e. temperature and rainfall), rather than other environmental factors such as edaphic conditions, disturbance or land-use changes.

14 2. Availability of data The capability of a species for future monitoring does not rely on the availability of data, but a demonstrably useful biological indicator with a large number and time span of quality prior records is ideal. 3. Functional position Where possible, species should be selected that are representative of a group of species (i.e. a functional group that represents differences in growth form or physiology) so we can generalise about change of groups of species over the largest spatial scale possible. 4. Suitability for monitoring Following the above, the species should be easy to observe, recognise and identify to enable cost effective and repeatable monitoring.

The first two criteria were used for the initial selection of indicator species from the herbarium records, and species were analysed according to the latter criteria after all the data had been collated.

Climatic sensitivity

To investigate the sensitivity of species flowering times in relation to climate change, records had to be sorted according to date. The dates of records were converted to Julian dates (i.e. the numeric day of the year, ranging from 1 to 365–366). Records that included only a month and year were automatically assigned the Julian date equal to the 15th day of the month, but this date was later adjusted for each species according to the estimated time of peak flowering (from the FIS data) so that the first Julian day for species that flowered in spring was calculated from the start of June or July. General trends in the data were assessed by plotting flowering (or fruiting or budding) dates through time.

Species were classified as either useful indicator species or potentially useful indicator species, or disregarded from further analysis. Useful or potentially useful species indicated a trend toward observed earlier flowering dates over time (which would be indicative of species responding to warmer temperatures earlier in the season, a key prediction under global warming scenarios), but their classification depended primarily on the availability of data. Data were then obtained from other sources (VROTpop and community data) and collated with the herbarium data for further analysis.

15 Analysis

Detection of flowering trends

General linear regression was used to evaluate the statistical strength and variability around any detected trend in the data, using the statistical program R (R Development Core Team 2006). Any statistical relationship with climate can be determined only if records of first flowering dates are available. The analysis of variability in relation to climatic data is thus generally restricted to general climatic patterns.

Ideally, climatic signals in the data would be robust enough to be detected regardless of location. However, variability in phenological records was expected because of the large area from which records were obtained, and because natural climatic gradients exist along the Victorian coastline. Where sufficient data were available, records were therefore grouped according to broad similarities in mean annual temperature or mean annual precipitation. To define these groups, data for the two bioclimatic variables were generated using the program BIOCLIM (Houlder, Hutchinson et al. 2000) for around 26 000 sites along the Victorian coastline.

Functional groups

Functional groups investigated included growth form and phenology (timing and duration of flowering). Numerous studies have already indicated that species which respond to environmental cues in spring rather than autumn or summer are more useful for tracking change (Hughes 2000; Menzel, Estrella et al. 2001), so species were grouped according to the season in which they began flowering (estimated from the FIS database).

Collation of data

Data were collated in Microsoft Access and submitted with this report to the Ecological Meta Database run by the Bureau of Meteorology (Bureau of Meteorology, Australian Greenhouse Office et al. 2008).

16 RESULTS

Climate data

Results from the analysis of long-term climate data from five Victorian meteorological stations along the Victorian coast indicate a general warming trend with time (Table 3). The magnitude of the trend differs between locations, but it is evident that trends are generally stronger in the period after 1950. The magnitude of this trend is even greater during the period from 1980–2006. Since 1980, the strongest trends have occurred at the Melbourne station, and the weakest trends have been at Cape Otway (maximum temperatures only) and Cape Nelson.

There are no consistent trends in the magnitude of change in minimum compared to maximum temperatures, or summer compared to winter temperatures. These changes vary over time and in accordance with location. For instance, the greatest changes at the Cape Otway station have been in summer and winter minimum temperatures, while the greatest changes at Gabo Island and Wilsons Promontory have been in summer and winter maximum changes. At the Melbourne station, the greatest changes have been in summer minimum and summer maximum temperatures.

Changes in precipitation are similarly inconsistent. There has been a general decrease in precipitation levels at Gabo Island and Melbourne, with the greatest change seen after 1950. The exception is an increasing trend in post 1980 precipitation at the Melbourne station, but this is due to periods of higher rainfall during the 1990s. Cape Otway and Wilsons Promontory, in general, show a trend toward increasing precipitation over time. At Cape Nelson there was an overall decrease in precipitation up to 1980, after which time levels increase. This highlights the variable nature of the precipitation data.

17 Table 3. Trends in mean summer and winter minimum and maximum temperatures (oC/year), and mean summer and winter precipitation levels (mm/year), 1910–2006. Data are slopes of linear regression models. NA: Insufficient data. * Data available until 1998. ** Data available from 1957 to 1997.

Site Climate variable 1910– 1950– 1980– (Station number) 2006 2006 2006 Cape Otway Summer max. temperature 0.009 0.005 0.003 Lighthouse Summer min. temperature 0.005 0.018 0.028 (090015) Winter max. temperature 0.004 0.009 0.001 Winter min. temperature 0.003 0.018 0.026 Summer precipitation 0.077 0.113 0.259 Winter precipitation 0.245 0.002 0.400 Gabo Island Summer max. temperature 0.014 0.030 0.034 Lighthouse Summer min. temperature 0.002 0.002 0.018 (084016) Winter max. temperature 0.008 0.029 0.043 Winter min. temperature 0.001 –0.003 0.016 Summer precipitation 0.003 –0.094 –0.458 Winter precipitation –0.136 –0.736 –0.701 Melbourne Summer max. temperature 0.008 0.010 0.063 Regional Office Summer min. temperature 0.021 0.032 0.051 (086071) Winter max. temperature 0.012 0.022 0.048 Winter min. temperature 0.018 0.030 0.031 Summer precipitation –0.012 –0.055 0.310 Winter precipitation –0.038 –0.188 –0.047 Wilsons Summer max. temperature 0.009 0.009 0.029 Promontory Summer min. temperature 0.008 0.024 0.028 Lighthouse Winter max. temperature 0.003 0.019 0.037 (085096) Winter min. temperature 0.004 0.030 0.024 Summer precipitation 0.016 0.082 –0.091 Winter precipitation 0.286 0.247 0.337 Cape Nelson Summer max. temperature NA 0.001** –0.028* (090014) Summer min. temperature NA 0.020** 0.024* Winter max. temperature NA 0.009** 5.931 x 10–5* Winter min. temperature NA 0.010** –0.012* Summer precipitation –0.043* –0.033* 0.550* Winter precipitation 0.150* -0.053* 0.549*

18 Potentially useful indicator species

Of the 79 species investigated, only 12 indicator species were found to be useful in the sense that they seem to track climate changes through time (Table 4). These showed a general trend toward earlier flowering dates with time, which would initially suggest that phenological changes in these species may be linked predominantly to temperature. Though there is a sufficient quantity of data to illustrate a trend, more data are required to statistically test the relationship for the majority of species (Table 5). Nevertheless, adequate records existed for these species to provide a some indiactive baseline data for future monitoring.

The strongest linear relationship between flowering dates over time is recorded for Lepidium foliosum (Figure 1, Table 5), but because there are only 13 records the variability explained by this model is likely to be inflated (R2 = 0.72). By comparison, Senecio pinnatifolius var. lanceolatus, which also has a significant linear trend, had a greater number of records (204) and a corresponding low R2 value (0.08). Other species which show stronger trends over time include Atriplex paludosa, Calorophus elongatus and the rare parasitic shrub Dendropthoe vitellina, all of which have fewer than 20 records.

Functional groups

Of the 12 useful indicator species, there is no apparent grouping according to life form or genus. However, there is an indication that the timing of flowering events may be important, as stronger trends were noted for species that flowered predominantly in spring and summer (Table 4)

19 Table 4. Summary of the species identified as being potentially suitable as Indicator Species of climate change. Data includes distribution (W= Widespread , I = Intermediate, L = Local), peak flowering time, number of phenological records (FL = flowering, B = budding, FR = fruiting, FL = flowering and budding or fruiting, and FE = fertile). The Range indicates the years over which data spans.

FL/ Species Distribution Flowers FL B FR FE Total Range FR/B

Alyxia buxifolia W Oct–Feb 19 18 12 49 1852–2004 Atriplex cinerea W Sept–Dec 48 4 52 1852–2006 Atriplex paludosa I Dec–Feb 13 3 2 1 19 1854–1997 Calorophus elongatus I Feb–Jul 9 12 1983–1993 Dendrophthoe vitellina L Sept–Feb 14 1 1 16 1912–1999 Lepidium foliosum W Dec–Feb 11 2 13 1864–1978 Leptospermum laevigatum W Aug–Nov 41 2 29 31 103 1852–2007 Limonium australe I Jan–Apr 31 31 1854–1997 Logania ovata I Sept–? 29 29 1858–1994 Pultenaea prolifera I Sept–Oct 38 1 1 40 1875–1992 Senecio pinnatifolius W Aug–Nov 204 204 1854–2005 var. lanceolatus Spinifex sericeus W Sept–Feb 25 22 47 1886–2000

Table 5. Results of the linear regression analysis: flowering dates (Julian dates) ~ time. Values highlighted in bold include significant linear trends (p < 0.10), and/or trends with higher levels of variation explained by the regression model (R2 values > 0.2).

Species Indicator Slope t p R2 Alyxia buxifolia FL –0.161 –0.865 0.399 0.042 Atriplex cinerea FL –0.028 –0.300 0.765 0.002 Atriplex paludosa FL –0.334 –1.905 0.079 0.218 Calorophus elongatus FL –11.589 –2.076 0.065 0.301 Dendrophthoe vittelina FL –0.798 –1.836 0.091 0.219 Lepidium foliosum FL –0.900 –5.288 2.57 x 10–4 0.718 Leptospermum laevigatum FL(FR/BD) –0.121 –1.627 0.108 0.036 Limonium australe FL –0.346 –1.075 0.291 0.036 Logania ovata FL –0.796 –3.332 0.003 0.291 Pultenaea prolifera FL –0.639 –1.635 0.110 0.066 Senecio pinnatifolius var. lanceolatus FL –0.688 –4.076 6.59 x 10–5 0.076 Spinifex sericeus FL –0.260 –1.400 0.174 0.076

20 21

Julian date 300 e) Dendropththoe vitellina 250

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300 f) Lepidium foliosum 250

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Julian day 360 g) Leptospermum laevigatum 320 280 240 200 160 120 80 40 0 1845 1865 1885 1905 1925 1945 1965 1985 2005

350 h) Limonium australe 300

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Figure 1. Plots of phenological observations over time for useful indicator species. Phenological key: black (flowering), dark pink (flowering and fruiting), light pink (flowering and budding), blue (fruiting), green (budding), red (fertile), and yellow (unknown status). Lines of best-fit are for flowering observations only.

23 Location

The variability in the relationship s between flowering time and year can be attributed partly to the area over which species are distributed along the Victorian coast. For instance, Atriplex paludosa, Calorphus elongatus and Dendropthoe vitellina have a much more restricted distribution than species such as Leptospermum laevigatum or Senecio pinnatifolius var. lanceolatus. It is likely that the variability encountered in these latter species is partly driven by gradients in temperature and rainfall along the coast, but this is very difficult to analyse given the nature of the data. For example, records for Senecio were extracted for three areas; Wilsons Promontory, Otway Ranges area, and East Gippsland east of Marlo. The groups represent a temperature gradient, with warmer mean annual temperatures in the east (~13.9–14.5 °C) compared to the west (~12.7–13.2 °C). East Gippsland records are distributed earliest in the season, which may reflect warmer average temperatures (Figure 2). In contrast, the Otway and Wilsons Promontory records indicate flowering over a similarly widespread period, though the Otway area records earlier minimum flowering dates. This variation may also be a function of precipitation, as the Otway area has a higher mean annual precipitation (1011–1263 mm/year) compared to Wilsons Promontory (936–1117 mm/year) or East Gippsland (870–1011 mm/year). It is likely that an interaction between temperature and precipitation gradients across the coast affects flowering times, but there are insufficient data to complete the sort of detailed modelling required.

Julian day

Figure 2. Flowering records for Senecio pinnatifolius var. lanceolatus from Wilsons Promontory ( ), Otways ( ) and East Gippsland ( ).

24

Omitted species

The majority of species examined in this study were not considered as useful indicators because they (a) showed no general pattern over time, (b) flowered over an extended period, or (c) had very few records from which to detect trends. Some species showed a trend for earlier flowering times over the study but a larger quantity of data (over a longer time frame) are required to determine whether these flowering times are cued predominantly by temperature. These species were omitted as potential indicator species because insufficient historical records were available for comparison of future observations. For example, it was proposed that orchid species may be useful indicator species. However, this is generally not the case. As above, there is a large degree of variability in flowering time, and no clear trend over time (Figure 3). In some cases this may simply be attributed to a lack of data (e.g. Caladenia valida, Corybas despectans), but it is likely that flowering in the majority of species is not cued by temperature or precipitation, but rather other environmental variables, such as fire (Coates et al. 2006; Coates and Duncan 2007).

25 a) Caladenia aurantica b) Caladenia calcicola c) Caladenia latifolia 180 160 140 160 140 120 140 120 120 100 100 100 80 80 80 60 60 60 40 40 40 20 20 20 0 0 0 1965 1970 1975 1980 1985 1990 1995 2000 2005 1930 1940 1950 1960 1970 1980 1990 2000 1965 1970 1975 1980 1985 1990 1995 2000 2005

d) Caladenia valida e) Corybas despectans f) Corybas fimbriatus 120 180 360 160 320 100 140 280 80 120 240 100 200 60 80 160 40 60 120 40 80 20 20 40 0 0 0 1930 1940 1950 1960 1970 1980 1990 2000 1965 1970 1975 1980 1985 1990 1995 2000 1960 1965 1970 1975 1980 1985 1990 1995

g) Corybas unguiculatus h) Pterostylis pedoglossa i) Pterostylis tenuissima 360 360 300 320 320 250 280 280 240 240 200 200 200 150 160 160 120 120 100 80 80 50 40 40 0 0 0 1960 1965 1970 1975 1980 1985 1990 1995 2000 1968 1970 1972 1974 1976 1978 1980 1982 1984 1940 1950 1960 1970 1980 1990 2000

Year

Figure 3. Observations of flowering in orchid species over time. Phenological key: black (flowering), blue (fruiting), and green (budding).

26 DISCUSSION

Based on climate data obtained from five Victorian coastal weather stations with long-term records, there is a trend toward increasing temperatures with time. The magnitude of the positive trend differs according to location, but in general the trend strengthened after 1950, and was greatest after 1980. Using data sourced from herbaria and the general community, it was demonstrated that the historical timing of flowering in some coastal species is correlated with this increase in average temperatures, with the majority of earliest flowering times recorded after 1950. Monitoring flowering times in these species may therefore be a useful indicator of future climatic variability.

Although a trend was evident, there was generally a large degree of variation in flowering period over time in many species. This was expected, as the variation encountered in observations of flowering in herbaria records is presumably in proportion to the length of the flowering period, which may also be affected by temperature. For instance, plants may flower earlier, but the flowering period might also be of longer duration in warmer years (Menzel, Estrella et al. 2001; Menzel, Sparks et al. 2006). Species which have a shorter flowering period (i.e. Pultenaea prolifera, orchid species) are more useful in minimising this problem, but it was still difficult to detect the scale at which variability in temperature is important given the irregular nature of data collection.

Variability in flowering response was expected because of the large spatial scale of the study. For example, variability in flowering time was greatest in species with a widespread range (i.e. Senecio pinnatifolius var. lanceolatus and Leptospermum laevigatum). If flowering in these species is cued by temperature, then flowering will also vary in relation to a geographical temperature gradient. Unfortunately, it was not possible to quantify (or confirm) this relationship because information regarding first flowering dates was not available. Even basic grouping of records in relation to location did not clarify the results, but again, this was largely limited by a lack of data and irregularities in data collection.

A further complication is that flowering in these species might be driven by environmental factors other than temperature (Dahlgren, Zeipel et al. 2007). In relation to the Senecio records (Figure 2), the absence of a clear trend in flowering times may be the result of an interaction with other environmental variables. Variation in precipitation is a likely candidate, as moisture is also an important determinant of phenological events in many plant species (de Groot, Ketner et al. 1995; Hughes 2000; Menzel 2002; Chambers 2006; Penuelas and Filella 2007). The

27 temperature gradient along the coast was not directly correlated with variability in rainfall which may have complicated the relationship. Similarly, variability was expected because the trend in rainfall over time did not always match the overall trend toward warmer temperatures for the Victorian coastline.

For these reasons, species with a large degree of variation in flowering records could have been omitted as indicators, but this is not warranted until further study is undertaken. These species could be very useful indicators of climate change because they are common and widespread across the Victorian coastal environment. Species with a restricted distribution may be better for detecting trends using herbarium records, but are not necessarily good indicators of the effect of climate change along the whole coastal system.

Functional groups

In addition to climatic sensitivity, other factors contribute to the utility of species as useful indicators of climate change (de Groot, Ketner et al. 1995; Hughes 2003). Indicator species should ideally be representative of a group of species so that generalisations can be made with respect to change over a larger spatial scale. DeGroot et al. (1995) referred to the identification of keystone species as indicator species, but the aim of grouping species is to simplify patterns and enhance our understanding of complex ecosystems (McIntyre, Diaz et al. 1999). Thus, functional grouping can also refer to life-form, size, or onset of flowering (Weiher, van der Werf et al. 1999).

The ability to detect functional group responses is largely limited by the availability of data. There is no indication at this stage that species can be grouped according to life-form or genus (perhaps with the exception of Atriplex) to make generalisations about biotic responses to climate change in coastal areas of Victoria. However, it was evident that plants that begin flowering in late winter to mid spring might be more useful than plants that flower at the start of winter. This is an interesting finding because there were no consistent trends in the magnitude of change in summer compared to winter temperatures and this suggests that flowering in winter may be responsive to other environmental cues, such as day-length or precipitation. This is consistent with findings in mid- to high-latitude areas, where the response in spring and summer phenological events is greater than that shown in autumn (Menzel, Estrella et al. 2001; Walther, Post et al. 2002; Menzel, Sparks et al. 2006).

28 Suitability for monitoring

Indicator taxa should be easy to observe, recognise and identify to enable cost-effective and repeatable monitoring (de Groot, Ketner et al. 1995; Hughes 2003). Some level of botanical training is required to fulfil these criteria, but common taxa with a widespread distribution (i.e. Leptospermum laevigatum, Spinifex sericeus) are particularly beneficial because they can be readily identified by non-specialists and hence, there is potential for involving the broader community in an observation network of phenological change

Availability and accuracy of data

The primary issue in using these data sources to detect indicator species lies in the accuracy and availability of data. While the utility of a species for future monitoring does not rely on the availability of data, a sufficient quantity of accurate data is necessary to demonstrate that a species can be used as an indicator species. In this study, a large number of species were designated ‘potential’ indicator species because some evidence of a trend toward earlier flowering over time was evident. However, there was a lack of data to corroborate a trend and to provide enough baseline data for future monitoring. Ideally, a useful indicator species will have a large number of quality prior records collected over a long period (de Groot, Ketner et al. 1995; Hughes 2003).

Herbarium data

The majority of data collected was sourced from the National Herbarium of Victoria at the Royal Botanic Gardens, Melbourne (RBG), which is considered a reliable data source because specimens are determined by botanists. In general, the record of flowering is also accurate, because if a note on the phenological state of the plant was not made by the collector it was noted by herbarium staff. A large number of records were omitted because the date of collection was not accurately recorded by the collector. Records were retained if the month and year were specified and the assigned Julian date was the 15th of that month, but this causes problems with accuracy, particularly if a species flowers only for a short period. A smaller number of records were omitted because the recorded location was too broad (e.g. ‘Victoria Felix’).

The greatest issue with these data sources is the declining number of recent records held in herbaria. A reduction in the type and number of records being submitted by the general public to the RBG has occurred because of a relatively recent requirement for a permit to collect native flora from public land by the Department of Sustainability and Environment and because charges

29 are applied for the identification of specimens by the RBG (RBG Melbourne 2008). Understandably, a herbarium is limited by time and space, so continual collection of commonly collected species is perhaps not a priority, but this does severely limit the potential for future studies on the ecological effects of climate change using herbaria records as the primary source of information.

VROTpop data

A small amount of data was obtained from the VROTpop database. Although the database contained numerous records, most had to be discarded because the phenological status of plants was not recorded, apparently because recorders did not fill in the forms completely. This is an issue which needs to be resolved, as VROTpop forms are potentially a scientifically sound substitute for herbarium records. This shortfall in data collection could be easily addressed by including a check-box on the form that indicates whether plants are flowering.

Community group data

Some data were sourced from individuals, but the potential for utilising data held by field naturalist groups greatly extends beyond what was collected in this study. Some of the issues with the indicator species might be clarified with the addition of such data.

A good source of regular catalogued information is often available in the form of newsletters compiled by community groups. For instance, a monthly column on flowering plants extended for a period of over 30 years was listed in the ANGAIR newsletters. The accuracy of the data is limited in that details of dates are not available, as the column is only a summary of plants flowering that month. Nevertheless, it would be valuable to digitise these records for future analysis. Similar accounts of flowering species observed on field trips are given in The Clematis, published by the Bairnsdale and District Field Naturalists. In this instance the dates of the field trips are known, and a database is currently being constructed to digitise these records.

In addition, some members of these groups keep their own records. For example, the naturalist notes of Terri Allen (South Gippsland Conservation Society), Bon Thompson (Traralgon Field Naturalists), Mary White (ANGAIR), and Ellen Lyndon were seen for this study. A large number of records were obtained from Bon Thompson, who has kept excellent records since the 1960s of a great number of species, including the date, location and phenological status. These were not regular records, but are an excellent additional source of data. A number of records were also obtained from Terri Allen, who has kept yearly diaries of both plant and bird

30 observations in the Wonthaggi Heathlands (‘The Pines’) since 1979. These records are an extremely valuable source of information. However, there were a few issues with the accuracy of these and some other community data. First, phenological notes were sometimes, but not always recorded, so it was not always possible to determine whether a species was in flower. This prompted our investigation into the potential of orchid species as indicators because most orchids must be flowering to be seen and identified. Secondly, the precise date was not always recorded, though this was generally not the case in Terri Allen’s diaries.

Additional sources of biological data

In addition to naturalist groups and individuals within the community, records from the apiary industry could be investigated as an additional source of phenological data. Phenological records are important in the industry because an understanding of the reproductive cycle is required (Keatley, Fletcher et al. 2002; Hughes 2003). While the majority of indicator species in this report may be irrelevant in this regard, there is potential for further collection of Leptospermum records.

31 CONCLUSION: Knowledge gaps, future research and community involvement

At present, there is a need to collate data that might assist with understanding the ecological effects of climate change in south-eastern Australia (Howden, Hughes et al. 2003; Hughes 2003; Pittock 2003; Chambers 2006; Rosenzweig, Karoly et al. 2008). This study has demonstrated that there is great potential to utilise data sourced from herbaria and within the community to identify biological indicators of climate change, and to provide background historical data for comparison of future observations.

Because of the irregular nature of data collection it is difficult to detect clear trends in phenological observations over time. It is proposed that this could be resolved by combining these data sets with detailed studies of phenological cycles in climatically different locations. The easiest method of obtaining this information is to work with coastal community groups. These groups have regular field trips throughout the year, and an arrangement could be made to record phenological observations of these species. A database could be set up along the lines of that used for the BioWatch phenological observation network (Rice 2003), enabling individuals or groups to submit observations directly. This would be an excellent way to publicise community involvement and knowledge, and would provide valuable information for future scientific and community efforts.

During this study we noted that recent herbarium specimens are few or lacking or fewer than in previous years. Given the utility of this data source, this is an issue that needs to be addressed. A good scientifically collected substitute for information on species distribution and occurrence is available in the form of FIS and VROTpop records. At present, the capacity of these databases does not extend to phenological information, but this could be considered as part of the review of these systems currently being conducted by DSE.

Lastly, there is far greater potential to utilise the information held within the community. One way in which species may respond to climate change is through a change in distribution and abundance (Hughes 2003). The records kept by individuals and by field naturalist groups constitute very accurate species lists for specific areas along the Victorian coast. It is suggested that there might be greater potential to use these data sources (combined with herbarium records) in the analysis of species distributions over time, rather than as accurate sources of phenological information (MacDougall, Loo et al. 1998; Ponder, Carter et al. 2001). It is crucial that future work is directed toward digitising these valuable information sources so that the data are not lost (Keatley, Fletcher et al. 2002).

32 Acknowledgments

We would like to thank Alison Vaughan (RBG Melbourne), Nicole Middleton (Melbourne University) and Heidi Zimmer (ARI) for assistance with herbarium searches; Terri Allen (South Gippsland Conservation Society) and Bon Thompson (Traralgon Field Naturalists) for providing phenological records and general suggestions regarding this research; Eulalie Hill and other members of South Gippsland Conservation Society, members of ANGAIR, Sera Cutler (La Trobe University), and to members of the Bairnsdale and District Field Naturalists Club for general discussion and access to information; to Timothy Forster (Bureau of Meteorology) for providing climate records; and to Yung En Chee for assistance with ANUCLIM. Ian Mansergh initiated the project, which was funded by the Greenhouse Policy Unit, DSE.

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36 APPENDIX ONE

Ecological Vegetation Class Groups

Number EVC Group 1 Coastal Dune Scrub Mosaic 2 Coast Banksia Woodland 3 Damp Sands Herb-Rich Woodland 5 Coastal Sand Heathland 6 Sand Heathand 154 Bird Colony Shrubland 155 Bird Colony Succulent Herbland 160 Coastal Dune Scrub 161 Coastal Headland Scrub 163 Coastal Tussock Grassland 181 Coast Gully Thicket 233 Wet Sands Thicket 309 Calcareous Swale Grassland 311 Berm Grassy Shrubland 652 Lunette Woodland 665 Coast Mallee Scrub 858 Coastal Alkaline Scrub 876 Spray-zone Coastal Shrubland 879 Coastal Dune Grassland 898 Cane Grass – Lignum Halophytic Herbland

37 Presence (*) of nominated EVC groups in each bioregion

EVC 3 652 5 6 311 154 155 309 898 2 181 858 879 160 1 161 665 163 876 233 Gippsland Plain * * * * * * * * * * * * * East Gippsland Lowlands * * * * Wilsons Promontory * * * * * * * * * * Victorian Volcanic Plains * * * * * * * * Otway Ranges * * * * Otway Plains * * * * * * * * * * Bridgewater * * * * * Warnambool Plain * * * * * * * Glenelg Plain * * * * * * * * *

38 Key EVC species (‘coastal’)

Species Common Name Distribution (FIS) No. FIS Records Flowers Status Acacia retinodes var. uncifolia Coast Wirilda L A Oct-Nov r Actites megalocarpa Dune Thistle W R Sept-Jun Alyxia buxifolia Sea Box W R Oct-Feb Atriplex cinerea Coast Saltbush W R Sept-Dec Austrofestuca littoralis Coast Fescue W R Sept-Oct Austrostipa stipoides Prickly Spear-grass M A Oct-Mar Banksia integrifolia ssp. integrifolia Coast Banksia M A Jan-Jun Carex pumila Strand Sedge W R Sept-Nov Exocarpos syrticola Coast Ballart M R Sept-Nov r Ixodia achillaeoides ssp. arenicola Ixodia L R ? Lasiopetalum schulzenii Drooping Velvet-bush L R Sept-Dec r Lepidosperma gladiatum Coast Sword-sedge W A Sept-Feb Leucophyta brownii Cushion Bush W A Sept-Feb Leucopogon parviflorus Coast Beard-heath W A Sept-Nov Malva sp. aff. australiana Coast Hollyhock L R ? Monotoca elliptica s.s. Monotoca elliptica M R Jun-Sept Muehlenbeckia adpressa Climbing Lignum W A Sept-Jan Olearia axillaris Coast Daisy-Bush W A Feb-Apr Ozothamnus turbinatus Coast Everlasting W A Dec-May Poa poiformis Coast Tussock-grass W A Sept-Jan Poa poiformis var. poiformis Coast Tussock-grass W A Sept-Jan Pomaderris oraria ssp. oraria Bassian Pomaderris L R Sept-Nov Pultenaea canaliculata Coast Bush-pea M R Sept-Nov Senecio spathulatus s.l. Dune Groundsel W A ? Spinifex sericeus Hairy Spinifex W A Sept-Feb Spyridium vexilliferum Winged Spyridium L R ? var. vexilliferum Stackhousia spathulata Coast Stackhousia W R Jul-Jan Swainsona lessertiifolia Coast Swainson-pea W A Aug-Jan Tetragonia implexicoma Bower Spinach W A Aug-Nov

39 Key FIS species (‘coastal’)

Species Common Name Distribution No. FIS Flowers Status (FIS) records Acrotriche cordata Coast Ground-berry L R Jul-Oct R Allocasuarina media Prom Sheoak L R Mar, Dec k Amphibolis antarctica Sea Nymph ? k Apium insulare Island Celery L R Oct-Feb v Atriplex paludosa subsp. paludosa Marsh Saltbush L A Dec-Feb r Australina pusilla subsp. pusilla Small Shade-nettle L R Oct-Jan r Avicennia marina subsp. australasica Grey Mangrove M A Mar-Aug r Banksia aff. paludosa (Mallacoota) Swamp Banksia L R Mar-Aug v Baumea laxa Lax Twig-sedge M A/R Sept-Nov r Bossiaea ensata Sword Bossiaea A Sept-Oct r Caladenia calcicola Limestone Spider-orchid L R Oct f, V, e Caladenia valida Robust Spider-orchid M A Sept-Oct f, e Calorophus elongatus Long Rope-rush L Feb-Jul v Colobanthus apetalus Coast Colobanth W Nov-Feb Correa alba var. pannosa Velvet White Correa L ? r Correa backhouseana var. backhouseana Coast Correa L ? v Corybas despectans Coast Helmet-orchid W A Jul-Aug v Darwinia camptostylis Clustered Darwinia L Aug-Nov r Dendrophthoe vitellina Long-flower Mistletoe L Sept-Feb r Galium compactum Compact Bedstraw L R Sept-Dec r Grevillea infecunda Anglesea Grevillea Oct-Dec V, v, endemic Hakea decurrens subsp. platytaenia Coast Needlewood L May-Sept r Hakea petiolaris Sea-urchin Hakea L R ? # Halophila australis Oval Sea-wrack L ? k Hemichroa pentandra Trailing Hemichroa M Nov-Feb Hibbertia hirticalyx Bass Guinea-flower L A Aug-Jan r Hibbertia pallidiflora Pale Guinea-flower L A Aug-Jan r Hibbertia truncata Port Campbell Guinea-flower A Aug-Jan r, endemic Hybanthus vernonii subsp. vernonii Erect Violet M Jun-Oct r

40 Species Common Name Distribution No. FIS Flowers Status (FIS) records Ixodia achillaeoides subsp. arenicola Ixodia L ? V, v Lepidium desvauxii Bushy Peppercress L Sept-May r Lepidium foliosum Leafy Peppercress L R Dec-Feb v Lepidosperma elatius var. ensiforme Tall Sword-sedge ? Lepilaena marina Sea Water-mat L Jul-Dec v Leptecophylla juniperina subsp. oxycedrus Crimson Berry L Aug-Nov v Leptospermum laevigatum Coast Tea-tree W A Aug-Nov Leucopogon esquamatus Swamp Beard-heath L Aug-Sept r Limonium australe Yellow Sea-lavender M Jan-Apr r Logania ovata Oval-leaf Logania M ? r Logania pusilla Tiny Logania M Sept-Nov r Microlepidium pilosulum Hairy Shepherd's Purse M Sept-Nov e Mitrasacme polymorpha Varied Mitrewort M Sept-Feb r Monotoca elliptica s.s. Tree Broom-heath M Jun-Sept Olearia axillaris Coast Daisy-bush W A Feb-April Olearia glutinosa Sticky Daisy-bush W A Dec-Feb Olearia ramulosa var. ramulosa Twiggy Daisy-bush W A Sept-May Olearia sp. 2 Peninsula Daisy-bush M Jan-Mar r Olearia viscosa Viscid Daisy-bush M ? v Oxalis rubens Dune Wood-sorrel M Nov-Feb r Poa poiformis var. ramifer Dune Poa W A Sept-Jan R Pomaderris oraria subsp. oraria Bassian Pomaderris L Sept-Nov r Pomaderris paniculosa subsp. paralia Coast Pomaderris M Sept-Oct Potamogeton sulcatus Furrowed Pondweed L Sept-Apr Prostanthera hirtula var. hirtula Hairy Mint-bush L ? Pseudoraphis paradoxa Slender Mud-grass L Feb-Apr f, e Pterostylis tenuissima Swamp Greenhood M Oct-Mar V, v Pultenaea canaliculata Coast Bush-pea M A Sept-Nov r Pultenaea prolifera Otway Bush-pea M A Sept-Oct r Ruppia tuberosa Tuberous Tassel L Sept-Nov k Salsola tragus subsp. pontica Coast Saltwort M May-Oct r

41 Species Common Name Distribution No. FIS Flowers Status (FIS) records Sclerostegia arbuscula Shrubby Glasswort M July-Sept Senecio pinnatifolius var. 2 Dune Groundsel M R Aug-Nov Taraxacum cygnorum Coast Dandelion L ? f, V, e Thelychiton speciosus Rock Orchid L AR Sept-Nov f, e Veronica hillebrandii Coast Speedwell L Dec-Feb v Xanthosia huegelii Heath Xanthosia M AR Oct-Mar Xerochrysum papillosum Island Everlasting L Nov-Feb r Zostera capricorni Dwarf Grass-wrack W A Oct-Mar Zostera tasmanica Tasman Grass-wrack M Sept-Feb r

42