John R. Gollan

Can Volunteers Collect Data that are Comparable to Professional Scientists? A Study of Variables Used in Monitoring the Outcomes of Ecosystem Rehabilitation

Having volunteers collect data can be a cost-effective strategy to complement or replace those collected by scientists. The quality of these data is essential where field-collected data are used to monitor progress against predetermined standards because they provide decision makers with confidence that choices they make will not cause more harm than good. The integrity of volunteer-collected data is often doubted. In this study, we made estimates of seven vegetation attributes and a composite measure of six of those seven, to simulate benchmark values. These attributes are routinely recorded as part of rehabilitation projects in Australia and elsewhere in the world. The degree of agreement in data collected by volunteers was compared with those recorded by professional scientists. Combined results showed that scientists collected data that was in closer agreement with benchmarks than those of volunteers, but when data collected by individuals were analyzed, some volunteers collected data that were in similar or closer agreement, than scientists. Both groups’ estimates were in closer agreement for particular attributes than others, suggesting that some attributes are more difficult to estimate than others, or that some are more subjective than others. There are a number of ways in which higher degrees of agreement could be achieved and introducing these will no doubt result in better, more effective programs, to monitor rehabilitation activities. Alternatively, less subjective measures should be sought when developing monitoring protocols. Quality assurance should be part of developing monitoring methods and explicitly budgeted for in project planning to prevent misleading declarations of rehabilitation success.

Using spider web types as a substitute for assessing web-building spider biodiversity and the success of habitat restoration

Arthropods have been regarded as good indicators of habitat quality due to their sensitivity to changes in habitat state. However, there are many constraints to working with arthropods that make them inaccessible to land managers and most volunteer-driven initiatives. Our study examined a novel approach for detecting changes in web-building spider communities by focussing on the types of webs that spiders build rather than the spider itself. This method was cost-effective, easy-to-use, and importantly, we found a strong congruency between the diversity of web architecture and the diversity of web-building spider genera. The metrics derived from this method could distinguish differences in web-building communities among habitat types that represented a successional gradient, and thus we concluded that the method was useful for monitoring the progress of restoration. Many other applications for the method are possible such as environmental impact assessment and agricultural pest management, and we encourage development in these areas.

Testing common habitat-based surrogates of invertebrate diversity in a semi-arid rangeland

Habitat-based surrogates are a low cost alternative to intensive biodiversity surveys, though they have been poorly investigated in semi-arid ecosystem compared to others such as temperate woodlands. In this study we tested potential habitat-based surrogates of invertebrate richness in a semi-arid rangeland in northwest Australia. Potential surrogates were: distance from artificial watering-point; soil hardness; habitat complexity; and individual complexity components. Generalised additive models (GAMs) were used to relate abundance and richness of selected invertebrates with environmental factors and cluster analysis was used to examine similarity in species composition. The most frequently selected factor was soil hardness, but taxa varied as to whether biodiversity was higher in soft or hard soils. Where distance from watering-point was an important predictor, there were generally higher abundances and richness closer to watering-points than further away. Abundance and species richness could be partially explained using individual complexity components, but relationships were weak and there were no consistent trends among taxa. Therefore, although habitat complexity has been correlated with species richness under some circumstances, our results cast doubt on the generality of this relationship. There are also dangers in assuming that all taxa respond in a manner similar to indicator taxa, as we observed that different taxa had higher richness at opposite extremes of some environmental gradients. Grazing may have a negative impact on biodiversity in some environments, but in regions where water is limiting, the net effect may be positive due to the creation of waterholes.

Using Generalised Dissimilarity Models and many small samples to improve the efficiency of regional and landscape scale invertebrate sampling

Abstract It is rarely cost-effective to survey invertebrates for use in systematic conservation planning activities. The efficiency of sampling methods needs to be improved, and this is especially important at landscape and regional scales. We investigated two methods that could be used to improve regional scale sampling efficiency using a case study of ants, beetles, flies, bugs, spiders and wasps from the semi-arid Pilbara region of Western Australia. First, Generalised Dissimilarity Models (GDMs) were used to divide the region into landscapes with relatively homogeneous communities and environmental conditions. We found that some of these landscapes were large, and a low sampling density could be employed in these areas due to the low spatial turnover in species. Other landscapes were 1–2 orders of magnitude smaller, and a higher sampling density should be employed to capture the high species turnover and unique species in these areas. Variation of sampling density based on landscape dimensions could vastly improve survey efficiency. Second, we investigated whether one large sample or five small samples were a more efficient method to estimate the species composition of each landscape. We found that five small samples captured a higher proportion of landscape scale species richness for a fixed sampling effort, and was therefore a more efficient method to determine the species composition of the landscape. Combining five small samples also resulted in less sample variability than one large sample, which increases statistical power to detect changes. We concluded that GDM was an effective method to increase sampling efficiency, because it allowed sampling density to vary according to the spatial turnover in species. Using many small samples is a more efficient method to capture the species composition of landscapes than a single large sample with an equivalent sample size.

Assessing the distribution and protection status of two types of cool environment to facilitate their conservation under climate change.

Strategies to mitigate climate change can protect different types of cool environments. Two are receiving much attention: protection of ephemeral refuges (i.e., places with low maximum temperatures) and of stable refugia (i.e., places that are cool, have a stable environment, and are isolated). Problematically, they are often treated as equivalents. Careful delineation of their qualities is needed to prevent misdirected conservation initiatives; yet, no one has determined whether protecting one protects the other. We mapped both types of cool environments across a large (∼3.4M ha) mixed-use landscape with a geographic information system and conducted a patch analysis to compare their spatial distributions; examine relations between land use and their size and shape; and assess their current protection status. With a modest, but arbitrary, threshold for demarcating both types of cool environments (i.e., values below the 0.025 quantile) there were 146,523 ha of ephemeral refuge (62,208 ha) and stable refugia (62,319 ha). Ephemeral refuges were generally aggregated at high elevation, and more refuge area occurred in protected areas (55,184 ha) than in unprotected areas (7,024 ha). In contrast, stable refugia were scattered across the landscape, and more stable-refugium area occurred on unprotected (40,135 ha) than on protected land (22,184 ha). Although sensitivity analysis showed that varying the thresholds that define cool environments affected outcomes, it also exposed the challenge of choosing a threshold for strategies to address climate change; there is no single value that is appropriate for all of biodiversity. The degree of overlap between ephemeral refuges and stable refugia revealed that targeting only the former for protection on currently unprotected land would capture ∼17% of stable refugia. Targeting only stable refugia would capture ∼54% of ephemeral refuges. Thus, targeting one type of cool environment did not fully protect the other.

The ratio of exotic-to-native dung beetles can indicate habitat quality in riparian restoration

1. Replanting natives on cleared riparian land is a common form of restoration. While most assessments of success are focussed on flora, the impact on fauna is often unknown.

Contrasting topoclimate, long-term macroclimatic averages, and habitat variables for modelling ant biodiversity at landscape scales

Spatial modelling is part of the solution for incorporating insects into conservation policy. Uptake, however, rests on identifying robust environmental predictors. Coarse‐grained climate models based on long‐term averages and similarly coarse environmental features may not be adequate, especially at regional scales where most planning is done. Here, we test whether topoclimatic variables, which are derived from local‐scale climate forcing factors, are more important for structuring ant assemblages. We quantified ant richness and species composition at 86 sites across a large (200 × 300 km) temperate region of southeast Australia, and tested the explanatory power of three groups of environmental variables: (i) topoclimatic variables, (ii) long‐term climatic averages modelled from global data, and (iii) habitat features, namely, habitat complexity, soil pH, and soil texture. Generalised Additive and Generalised Dissimilarity Models were used to test predictors. In univariate models, the topoclimatic estimator of maximum temperature (95maxT) explained the largest amount of variance in both richness and compositional turnover (20% and 24% of deviance respectively). The plot for richness indicated a positive but decelerating function of 95maxT. This was consistent for two of three habitat types. Habitat complexity was the most important predictor in cleared habitat (28%). While a topoclimatic variable was a strong predictor of ant biodiversity across the landscape, this was not a ‘magic bullet’. Other predictors such as complexity may be more applicable in certain habitat types. We concluded that tailored predictors are needed for landscapes with a mosaic of different land use.

Fine-grained climate data alters the interpretation of a trait-based cline

Investigating responses to climate often rely on macroclimatic models. This is problematic because of the potential to miss or wrongly attribute relationships. Here we compare the explanatory power of macroclimatic models and near-surface topoclimatic models. Body-size measurements of the ant species, Iridomyrmex purpureus, were collected from separate colonies spanning a range of climatic conditions in a large region (∼75,000 km2) of Australia. Regional regression was used to derive two topoclimatic variables, while ANUCLIM was used to derive macroclimatic variables. Relationships were tested using linear mixed-effect models with Akaike information criterion used as an indication of the relative goodness of fit for each model. Significant trends for both topoclimatic variables with body size were detected but only one of the three macroclimatic variables showed a significant trend. Although the significant macroclimatic variable was correlated with one of the topoclimatic variables, the topoclimatic variable had greater explanatory power. Few studies have considered climatic data accuracy or the effects of inaccurately quantified climatic data on ecological theory. This cannot continue to be ignored. As we show in this study, there is potential for important trends to go undetected and interpretation of results to be completely different.