Michael B. Ashcroft

Climate refugia: joint inference from fossil records, species distribution models and phylogeography

Climate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial-interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia - fossil records, species distribution models and phylogeographic surveys - in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas-fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine-scale processes and the particular geographic locations that buffer species against rapidly changing climate.

A climate of uncertainty: accounting for error in climate variables for species distribution models

Summary Spatial climate variables are routinely used in species distribution models (SDMs) without accounting for the fact that they have been predicted with uncertainty, which can lead to biased estimates, erroneous inference and poor performances when predicting to new settings – for example under climate change scenarios. We show how information on uncertainty associated with spatial climate variables can be obtained from climate data models. We then explain different types of uncertainty (i.e. classical and Berkson error) and use two statistical methods that incorporate uncertainty in climate variables into SDMs by means of (i) hierarchical modelling and (ii) simulation–extrapolation. We used simulation to study the consequences of failure to account for measurement error. When uncertainty in explanatory variables was not accounted for, we found that coefficient estimates were biased and the SDM had a loss of statistical power. Further, this bias led to biased predictions when projecting change in distribution under climate change scenarios. The proposed errors-in-variables methods were less sensitive to these issues. We also fit the proposed models to real data (presence/absence data on the Carolina wren, Thryothorus ludovicianus), as a function of temperature variables. The proposed framework allows for many possible extensions and improvements to SDMs. If information on the uncertainty of spatial climate variables is available to researchers, we recommend the following: (i) first identify the type of uncertainty; (ii) consider whether any spatial autocorrelation or independence assumptions are required; and (iii) attempt to incorporate the uncertainty into the SDM through established statistical methods and their extensions.

Sydney Harbour: its diverse biodiversity

All records of crustaceans, molluscs, polychaetes, echinoderms and fishes from Sydney Harbour were extracted from the Australian Museum database, and plotted onto a map of Sydney Harbour that was divided into four regions. Records were analysed according to the number of species, genera and families present and over 3000 species were recorded, approximately double to triple the number of species found in the neighbouring Hawkesbury River, Botany Bay and Port Hacking. We examined the rate of accumulation of records and species over time since the 1860s, which followed a stepwise pattern usually correlated with the research activity of specific curators at the Australian Museum. The high species richness of Sydney Harbour is probably the result of multiple factors including significant tidal flushing and the high diversity of habitats present. Not all parts of the harbour have been well sampled, however, and we highlight areas and habitats that should be prioritised for further biodiversity surveys. An Appe...

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.

Moving beyond presence and absence when examining changes in species distributions

Abstract Species distributions are often simplified to binary representations of the ranges where they are present and absent. It is then common to look for changes in these ranges as indicators of the effects of climate change, the expansion or control of invasive species or the impact of human land‐use changes. We argue that there are inherent problems with this approach, and more emphasis should be placed on species relative abundance rather than just presence. The sampling effort required to be confident of absence is often impractical to achieve, and estimates of species range changes based on survey data are therefore inherently sensitive to sampling intensity. Species niches estimated using presence‐absence or presence‐only models are broader than those for abundance and may exaggerate the viability of small marginal sink populations. We demonstrate that it is possible to transform models of predicted probability of presence to expected abundance if the sampling intensity is known. Using case studies of Antarctic mosses and temperate rain forest trees, we demonstrate additional insights into biotic change that can be gained using this method. While species becoming locally extinct or colonising new areas are extreme and obviously important impacts of global environmental change, changes in abundance could still signal important changes in biological systems and be an early warning indicator of larger future changes. &NA; Species distributions are often portrayed as binary representations of where they are present and absent. These are useful as rough guides but boundaries are virtually impossible to delineate accurately as the sampling effort to be certain of absence is prohibitive and populations near boundaries can be sparse and temporally variable. In this article, we highlight the advantages of focusing on relative abundance rather than presence‐absence and demonstrate methods that can be used to convert probabilities of presence to expected abundance. This has implications for climate change predictions and the management of invasive species and land‐use change. Figure. No caption available.

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.

Do daily and seasonal trends in leaf solar induced fluorescence reflect changes in photosynthesis, growth or light exposure?

Solar induced chlorophyll fluorescence (SIF) emissions of photosynthetically active plants retrieved from space-borne observations have been used to improve models of global primary productivity. However, the relationship between SIF and photosynthesis in diurnal and seasonal cycles is still not fully understood, especially at large spatial scales, where direct measurements of photosynthesis are unfeasible. Motivated by up-scaling potential, this study examined the diurnal and seasonal relationship between SIF and photosynthetic parameters measured at the level of individual leaves. We monitored SIF in two plant species, avocado (Persea Americana) and orange jasmine (Murraya paniculatta), throughout 18 diurnal cycles during the Southern Hemisphere spring, summer and autumn, and compared them with simultaneous measurements of photosynthetic yields, and leaf and global irradiances. Results showed that at seasonal time scales SIF is principally correlated with changes in leaf irradiance, electron transport rates (ETR) and constitutive heat dissipation (YNO; p < 0.001). Multiple regression models of correlations between photosynthetic parameters and SIF at diurnal time scales identified leaf irradiance as the principle predictor of SIF (p < 0.001). Previous studies have identified correlations between photosynthetic yields, ETR and SIF at larger spatial scales, where heterogeneous canopy architecture and landscape spatial patterns influence the spectral and photosynthetic measurements. Although this study found a significant correlation between leaf-measured YNO and SIF, future dedicated up-scaling experiments are required to elucidate if these observations are also found at larger spatial scales.

Nest caging as a conservation tool for threatened songbirds

Abstract Context. Enclosing nests in cages to exclude predators is a management tool frequently used to increase the reproductive success of threatened ground-nesting precocial birds. This technique has seldom been used with passerines, despite the predicted increased benefit for altricial species due to their longer period of nest dependency. Aims. The aims of this study were to determine (1) whether cages could be installed around the nests of a threatened, shrub-nesting passerine without causing parental desertion, and (2) whether caged nests could successfully exclude the dominant nest predators and increase nesting success. Methods. Cages with four different mesh sizes (1000 mm, 200 mm, 100 mm, 50 mm) were installed sequentially in trials at four nests in a secure population and three nests in an endangered population of white-fronted chats (Epthianura albifrons) to investigate susceptibility to desertion. Trials using 160 caged and uncaged artificial nests were used to determine the efficacy of 50-mm wire mesh in preventing access to eggs by potential nest predators. Key results. Parent birds accepted nest cages, which reduced predation rates on artificial nests from 96% to 14%. Infrared-triggered cameras revealed that corvids were responsible for 94% of predation episodes. Nest success of caged white-fronted chat nests was 85% (n = 7). Conclusions. Nest cages do not appear to have negative effects on nest success of white-fronted chats, and may considerably increase reproductive success. Implications. Nest cages may aid conservation of the endangered population of white-fronted chats and other endangered songbird species.

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.