Border Ranges Biodiversity Management Plan: defining plant functional groups for use in resource-limited multi-species recovery implementation scenarios FLORA REPORT PREPARED FOR NSW DEC BY Robert Kooyman and Maurizio Rossetto National Herbarium of NSW, Botanic Gardens Trust, Mrs Macquaries Rd, Sydney NSW 2000, Australia. June 2007 Abstract This report provides an overview of the development of a bioregional approach to biodiversity assessment and management that uses trait-based plant functional groups as a basis for multi-species recovery planning. Multi-variate methods were used to extract and test emergent groups, and additional information fields related to species life history and distributional data were added to develop a biodiversity assessment matrix in spreadsheet format (Appendix 1). Tests of phylogenetic independence were undertaken and showed that phylogeny significantly affects the clustering of character states for nearly all the traits studied. Data rich samples were used to test the methods in one (rainforest) community type, and several species from one of our emergent groups were chosen from that sample to provide an example of the function of the biodiversity assessment tool. Relating emergent trait-based plant functional groups to habitat was found to be the most informative approach for the development of management recommendations and recovery planning related to landscape scale threat / risk categories. Appendix 2 provides a list of species representing the various groups that have been identified as the focus for additional research and information gathering. Appendix 3 provides species level information related to defining the realised niche (reflecting species distribution in relation to environmental variables) for twenty-nine species from the data rich sample that occur on the BRBMP list. 1 Table of Contents Project Brief........................................................................................................................ 3 Introduction......................................................................................................................... 4 Methods............................................................................................................................... 8 Study area and data compilation..................................................................................... 8 Trait Information............................................................................................................. 9 Habitat Types and Initial Threat Assessment ................................................................. 9 Data analysis methods for the target species ................................................................ 10 Results............................................................................................................................... 12 Identifying appropriate trait-based groups.................................................................... 12 BRBMP Project Listed Species .................................................................................... 13 Description of trait-based groups obtained from cluster analysis................................. 14 Discussion......................................................................................................................... 15 Multi-species planning based on trait-related groups: conceptual framework ............. 15 References......................................................................................................................... 21 Appendix 1 - Biodiversity Assessment Matrix.................................................................. 34 Appendix 2 – Group priorities for research..................................................................... 37 Appendix 3 – Data Rich Community Example (SNMVF) ................................................ 40 Introduction....................................................................................................................... 40 Methods............................................................................................................................. 40 Data analysis methods for the data rich community example ...................................... 40 Trait relationships for rare and threatened taxa in the SNVF sample........................... 41 Results............................................................................................................................... 42 Discussion......................................................................................................................... 43 2 Project Brief • Develop a transferable conceptual approach to guide rare and threatened plant biodiversity management planning for use at bio-regional scales. • Using the available and accessible data develop a (parsimonious) trait-based approach defining plant functional groups that reflect biological / ecological / evolutionary and habitat factors. • Provide a spreadsheet based biodiversity assessment matrix that, once relevant data has been added, can integrate group and species level landscape-scale threats to help define RISK-based assessment categories that inform management priorities and the strategic allocation of resources. • Provide a broad and fine-scale data rich (species richness / abundance / environmental variables) and threatened species rich ecosystem-based example to allow exploratory analyses and testing of methods. • Provide guidance for future implementation needs and develop preliminary examples using taxa for which data is available. 3 Introduction The study of the distribution of plants and their relative abundances in variable landscapes is central to the development of conservation planning. Determining how species make a living and how they interact with other species and environmental variables in their shared habitats is an important area of research linked to community ecology. Plant life history traits provide insights into both evolutionary and ecological processes and are regarded as a critically important area of research in plant science. From a conservation perspective, functional groups based on life-history characters have the potential to bring together taxa that are likely to respond to selective processes, environmental threats and potential management actions in similar ways. They also provide insights into the mechanisms behind species responses to land-use change (Verheyen et al., 2003; Kolb and Diekmann, 2005). The focus of recovery planning in response to Australian state and federal threatened species legislation has, until recently, predominantly been on the development of single- species recovery plans that developed strategies for threat abatement and population preservation. However, the allocated resources available for the development of such plans has often been insufficient and exhausted before many of the identified recovery actions could be implemented. In response to this, there is increasing interest in developing management and recovery planning efforts that are focused on securing multiple species outcomes at bioregional scales. The aim of such plans is to identify threatening processes, and coordinate and prioritise recovery efforts across landscape, community, site, and species levels while simultaneously responding to the requirement for cost-effectiveness. The need for effective approaches to guide the use of scarce resources for the conservation of rare and threatened species is well established and acknowledged as of broad interest to conservation scientists, managers and practitioners. Using plant functional traits to group species for research and management has attracted considerable research interest over many years (Cornelissen et al., 2003), and has resulted in a number 4 of plant strategy schemes being developed (eg., Grime 1977; Gitay and Noble 1997; Westoby 1998; Westoby et al., 2002). The idea that plant species with different qualitative and quantitative traits can be more successful in different parts of the landscape is certainly not new (for example Schimper, 1903). It is also well known that plant species functional traits vary both along environmental gradients and within communities of species under similar conditions. The shift in trait frequencies along gradients, the mix of traits at a site, and trait correlations, can all provide important insights into community and species level vegetation processes, and species present day ecological competence. In that context, the physical environment can then be considered as filtering the kinds of species that can succeed at a given site (by providing the framework within which species interact), but not as the final determinant of the range of trait values present at a site (Westoby and Wright 2006). Partial reviews of the history of development and efficacy of biodiversity recovery planning at various scales and in different contexts have been undertaken (for example, Harding et al., 2001; Hecht and Parkin, 2001; Abbitt and Scott, 2001; Clarke et al., 2002; Moore and Wooller, 2004; Roberge and Angelstam, 2004; Male and Bean, 2005). It is not our intention to compare or provide detailed descriptions of the various approaches to recovery planning, from the species to the systems level (refer to McNeely, 2006) however, the applicability of other recovery planning approaches to this case has been explored. It was concluded that: Reverting to a compilation of single species population viability analyses (PVA) for all taxa in the