David H. Duncan

Towards Adaptive Management of Native Vegetation in Regional Landscapes

Landscape modellers are now capable of combining high resolution spatial data with process models to explore natural resource management scenarios at scales appropriate for decision making, but what of the process of decision making itself? In this chapter we review the applicability of the ‘adaptive management’ paradigm to natural resource management, using regional management of native vegetation by Catchment Management Authorities as an example. We find that progress has been made in the approach to defining management objectives and specifying assumptions behind vegetation change models; however, there remain significant challenges in instituting true management experiments and identifying performance indicators appropriate to support continuous learning. We argue that the ecological and institutional complexity of native vegetation management reinforces the importance of systematic decision protocols. Adaptive management is the most logical approach to decision making where there is uncertainty about the effectiveness of management options, and the opportunity exists to learn and update understanding. This iterative process offers continuous improvements to investment efficiency in native vegetation management.

High self-pollen transfer and low fruit set in buzz-pollinated Dianella revoluta (Phormiaceae)

We used pollinator observation, flower manipulation, controlled pollination and pollen-tube analysis to better understand the reproductive ecology of Dianella revoluta R.Br., a common species known to have depressed fruit set at fragmented sites. This buzz-pollinated species was found to receive large quantities of self-pollen even during a single pollinator visit, but is only partially self-compatible. This may be the first direct demonstration of pollinator-facilitated, autogamous self-pollen transfer accounting for a significant proportion of stigmatic pollen load. Frequent high self-pollen transfer may account for the observed low rate of fruit development in open-pollinated flowers. Self-pollen tubes reached the base of the style in comparable numbers and at the same rate as outcross pollen tubes, with no sign of pollen-tube competition favouring outcross pollen. Barriers to greater self-fertility occur late, probably through early abortion of selfed ovules. We also investigated what impact overlapping distribution with D. longifolia may have on D. revoluta pollination and reproduction. Although these species shared pollinators, they differed in terms of frequency of visits. There was also separation of floral phenology within the course of a day. BT03 Pollm mut D. H. Du

Biocrust morphogroups provide an effective and rapid assessment tool for drylands

Summary Biological soil crusts (biocrusts) occur across most of the worlds drylands and are sensitive indicators of dryland degradation. Accounting for shifts in biocrust composition is important for quantifying integrity of arid and semi‐arid ecosystems, but the best methods for assessing biocrusts are uncertain. We investigate the utility of surveying biocrust morphogroups, a reduced set of biotic classes, compared to species data, for detecting shifts in biocrust composition and making inference about dryland degradation. We used multivariate regression tree (MRT) analyses to model morphogroup abundance, species abundance and species occurrence data from two independent studies in semi‐arid open woodlands of south‐eastern Australia. We advanced the MRT method with a ‘best subsets’ model selection procedure, which improved model stability and prediction. Biocrust morphogroup composition responded strongly to surrogate variables of ecological degradation. Further, MRT models of morphogroup data had stronger explanatory power and predictive power than MRT models of species abundance or occurrence data. We also identified morphogroup indicators of degraded and less degraded sites in our study region. Synthesis and applications. Sustainable management of drylands requires methods to assess shifts in ecological integrity. We suggest that biocrust morphogroups are highly suitable for assessment of dryland integrity because they allow for non‐expert, rapid survey and are informative about ecological function. Furthermore, morphogroups were more robust than biocrust species data, showed a strong response to ecological degradation and were less influenced by environmental variation, and models of morphogroup abundance were more predictive.

Combining facilitated dialogue and spatial data analysis to compile landscape history

Successful reconstruction or restoration of formerly cleared landscapes depends on land use history and its legacies. Programmes developed without consideration of these legacies may fail to be effective and lack credibility. However, compiling landscape histories is not simple; our participatory workshops with long-term local residents combined spatial data on landscape change with facilitated conversations to compile a history of landscape change. Timing and extent of key environmental and socio-economic drivers of woody vegetation cover change since European settlement were established. Some drivers of clearing were relatively well-known, such as drought, or clearing for surface mining and pastoralism. However, others, including important interactions like prolonged drought intersecting with declining wool prices, were less known. These workshops verified provisional data, tested focus and methods, and identified critical time periods for further investigation. The workshops were a powerful transdisciplinary research tool that enhanced the understanding of researchers and participants beyond expectations. Other researchers should consider the general approach when assembling landscape history as a basis for documenting the degree and causes of change.

Quantifying ecosystem quality by modeling multi‐attribute expert opinion

The evaluation of ecosystem quality is inherently subjective, requiring decisions about which variables to notice or measure, and how these variables are integrated into a coherent evaluation. Despite the central role of human judgment, few evaluation methods address the subjectivity that is inherent in their design. There are, however, advantages to directly using opinion to create an expert system where the metric is constructed around opinion data. These advantages include stakeholder inclusion and the encouragement of a dialogue of data-driven criticism rather than subjective counter-opinion. We create an expert system to express the quality of a grassland ecosystem in Australia. We use an ensemble of bagged regression trees trained on calibrated expert preference data, to model the perceived quality of this grassland using a set of eight site variables as inputs. The model provides useful predictions of grassland quality, producing predictions similar to real expert evaluations of independent synthetic test sites not used to train the model. We apply the model to real grassland sites ranging from pristine to highly degraded, and confirm that our model orders the sites according to their degree of modification. We demonstrate that the use of too few experts produces relatively poor results, and show that for our problem the use of data from over twenty experts is appropriate. The scaling approach we used to calibrate between-expert data is shown to be an appropriate mechanism for aggregating the opinions of multiple experts. The resultant model will be useful in many contexts, and can be used by managers as a tool to evaluate real sites. It can also be integrated into ecological models of change as a means of evaluating predicted changes, for example, as a measure of utility when combined with cost estimates. The basic approach demonstrated here is applicable to any ecosystem, and we discuss the opportunities and limitations of its wider use.

Examining change over time in habitat attributes using Bayesian reinterpretation of categorical assessments.

Prospects for evaluating effects of vegetation restoration have long been limited by availability of appropriately sensitive baseline data. Data that are typically collected to justify investment in restoration are rarely suitable for estimating subsequent change over time, but given how commonly such data are collected, can they contribute something to learning about ecological change over time? We compared vegetation and habitat data from a quantitative reassessment of 25 habitat restoration sites seven years after they were initially assessed using a semiquantitative, categorical scoring system. Our aim was to estimate the change at sites between the first, semiquantitative survey and a second, quantitative survey. We treated the initial values as effectively unknown and used Bayesian models to infer plausible values using three different informative prior distributions, variously comprising the initial site assessments and modeled values from a statewide data set. We successfully constructed models of change over time between the two surveys, and regardless of which prior model was implemented, our data analysis suggested that cover of exotic species was reduced, but canopy cover, the cover of organic litter, and the length of fallen logs were all increased after the seven-year period. A small increase in the mean number of large-diameter trees was likely due to initial measurement error. Site fertility and canopy cover were important covariates in explaining the magnitude of change in total log length. Sites with higher canopy cover decreased more in weed cover and increased more in litter cover. Our approach could be used to retrospectively analyze any ordinal data set where there is a scoring logic that can be interpreted quantitatively. Data sets where treatment contrasts and untreated controls exist will be particularly valuable for testing the utility of our approach. While this novel approach should prove a useful analytical complement to genuine longitudinal monitoring and space-for-time surveys, it is no substitute for initiation of learning about management effectiveness using data from purposefully designed and measured surveys.

Evaluating the performance of a centralised government geodatabase in capturing publicly-funded natural resource management activities in Victoria, Australia

Over the past two decades the Australian government has invested billions of dollars into restoring and conserving Australias environment and natural resources. However, audits of major programs have, in many cases, found it hard to verify where money was spent, let alone estimate what ecological impact it achieved. In Victoria, the Catchment Activity Management System (CAMS) – a centralised geodatabase intended to capture information about on-ground natural resource management (NRM) works – was developed around 2000 to enable uniform reporting at regional and state levels. The advent of this system was lauded for its potential to streamline reporting, but also to facilitate monitoring of the effectiveness of those projects. We evaluated the representation of native vegetation protection, revegetation and remnant restoration activities in CAMS by comparing these data to equivalent, independently generated data from three catchment management regions. The CAMS database captured just over half of the relevant works directly co-funded by government as spatial records. Since these accounted for approximately two-thirds of the total area of publicly co-funded works for that period, it follows that smaller sites were more likely to have been omitted from CAMS. Although the entry of works into CAMS only became encouraged in 2001, each CMA had undertaken some back-filling of the database and those sites that were included in CAMS were typically accurately mapped and located. Although our aim was not to recommend what information might be collected in CAMS to improve the ecological reporting, we believe our review will help inform that purpose. Given that many basic fields within the database remain unpopulated, consideration should be given to how those who collect the data could be encouraged to undertake diligent collection of more complex information that might be required to inform ecological change analyses.

Understanding Landscapes through Knowledge Management Frameworks, Spatial Models, Decision Support Tools and Visualisation

Understanding Landscapes through Knowledge Management Frameworks, Spatial Models, Decision Support Tools and Visualisation.- Natural Resource Knowledge Management Frameworks and Tools.- Reading between the Lines: Knowledge for Natural Resource Management.- Improving the Use of Science in Evidencebased Policy: Some Victorian Experiences in Natural Resource Management.- The Catchment Analysis Tool: Demonstrating the Benefits of Interconnected Biophysical Models.- The Application of a Simple Spatial Multi-Criteria Analysis Shell to Natural Resource Management Decision Making.- Platform for Environmental Modelling Support: a Grid Cell Data Infrastructure for Modellers.- Integrating the Ecology of Landscapes into Landscape Analysis and Visualisation.- Looking at Landscapes for Biodiversity: Whose View Will Do?.- Native Vegetation Condition: Site to Regional Assessments.- Towards Adaptive Management of Native Vegetation in Regional Landscapes.- Revegetation and the Significance of Timelags in Provision of Habitat Resources for Birds.- The Application of Genetic Markers to Landscape Management.- Scenario Analysis with Performance Indicators: a Case Study for Forest Linkage Restoration.- Socioeconomic Dimensions to Landscapes.- Strategic Spatial Governance: Deriving Social-Ecological Frameworks for Managing Landscapes and Regions.- Placing People at the Centre of Landscape Assessment.- The Social Landscapes of Rural Victoria.- A Decision Aiding System for Predicting Peoples Scenario Preferences.- Land Use Change and Scenario Modelling.- Mapping and Modelling Land Use Change: an Application of the SLEUTH Model.- Uncertainty in Landscape Models: Sources, Impacts and Decision Making.- Assessing Water Quality Impacts of Community Defined Land Use Change Scenarios for the Douglas Shire, Far North Queensland.- Analysing Landscape Futures for Dryland Agricultural Areas: a Case Study in the Lower Murray Region of Southern Australia.- Applying the What If? Planning Support System for Better Understanding Urban Fringe Growth.- Landscape Visualisation.- Understanding Place and Agreeing Purpose: the Role of Virtual Worlds.- Geographic Landscape Visualisation in Planning Adaptation to Climate Change in Victoria, Australia.- Visualising Alternative Futures.- Virtual Globes: the Next GIS?.- A Virtual Knowledge World for Natural Resource Management.- Computer Games for Interacting with a Rural Landscape.- Automated Generation of Enhanced Virtual Environments for Collaborative Decision Making Via a Live Link to GIS.- Land Use Decision Making in a Virtual Environment.

Useful surrogates of soil texture for plant ecologists from airborne gamma-ray detection

Abstract Plant ecologists require spatial information on functional soil properties but are often faced with soil classifications that are not directly interpretable or useful for statistical models. Sand and clay content are important soil properties because they indicate soil water‐holding capacity and nutrient content, yet these data are not available for much of the landscape. Remotely sensed soil radiometric data offer promise for developing statistical models of functional soil properties applicable over large areas. Here, we build models linking radiometric data for an area of 40,000 km2 with soil physicochemical data collected over a period of 30 years and demonstrate a strong relationship between gamma radiometric potassium (40K), thorium (²³²Th), and soil sand and clay content. Our models showed predictive performance of 43% with internal cross‐validation (to held‐out data) and ~30% for external validation to an independent test dataset. This work contributes to broader availability and uptake of remote sensing products for explaining patterns in plant distribution and performance across landscapes.