Fine-scale effects of habitat loss and fragmentation despite large-scale gene flow for some regionally declining woodland bird species

Habitat loss and associated fragmentation effects are well-recognised threats to biodiversity. Loss of functional connectivity (mobility, gene flow and demographic continuity) could result in population decline in altered habitat, because smaller, isolated populations are more vulnerable to extinction. We tested whether substantial habitat reduction plus fragmentation is associated with reduced gene flow in three 'decliner' woodland-dependent bird species (eastern yellow robin, weebill and spotted pardalote) identified in earlier work to have declined disproportionately in heavily fragmented landscapes in the Box-Ironbark forest region in north-central Victoria, Australia. For these three decliners, and one 'tolerant' species (striated pardalote), we compared patterns of genetic diversity, relatedness, effective population size, sex-ratios and genic (allele frequency) differentiation among landscapes of different total tree cover, identified population subdivision at the regional scale, and explored fine-scale genotypic (individual-based genetic signature) structure. Unexpectedly high genetic connectivity across the study region was detected for 'decliner' and 'tolerant' species. Power analysis simulations suggest that moderate reductions in gene flow should have been detectable. However, there was evidence of local negative effects of reduced habitat extent and structural connectivity: slightly lower effective population sizes, lower genetic diversity, higher within-site relatedness and altered sex-ratios (for weebill and eastern yellow robin) in 10 x 10 km 'landscapes' with low vegetation cover. We conclude that reduced structural connectivity in the Box-Ironbark ecosystem may still allow sufficient gene flow to avoid the harmful effects of inbreeding in our study species. Although there may still be negative consequences of fragmentation for demographic connectivity, the high genetic connectivity of mobile bird species in this system suggests that reconnecting isolated habitat patches may be less important than increasing habitat extent and/or quality if these need to be traded off.

Corner inlet and Nooramunga habitat mapping project

Deakin University and the University of Tasmania were commissioned by Parks Victoria (PV) to create two updated habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both ALOS (Advanced Land Observation Satellite) imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, returning overall accuracies >73 % and kappa values > 0.62 for both study localities. Habitats predicted with highest accuracies included Zosteraceae in Nooramunga (91 %), reef in Corner Inlet (80 %), and bare sediment (no-visible macrobiota/no-visible seagrass classes; both > 76 %). The majority of classification errors were due to the misclassification of areas of sparse seagrass as bare sediment. For the Corner Inlet study locality the no-visible macrobiota (10,698 ha), Posidonia (4,608 ha) and Zosteraceae (4,229 ha) habitat classes covered the most area. In Nooramunga no-visible seagrass (5,538 ha), Zosteraceae (4,060 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

In addition to the commissioned work preliminary change detection analyses were undertaken as part of this project. These analyses indicated shifts in habitat extents in both study localities since the late 1990s/2000. In particular, a post-classification analysis highlighted that there were considerable increases in seagrass habitat (primarily Zosteraceae) throughout the littoral zones and river/creek mouths of both study localities. Further, the numerous channel systems remained stable and were free of seagrass at both times. A substantial net loss of Posidonia in the Corner Inlet locality is likely but requires further investigation due to potential misclassifications between habitats in both the 1998 map (Roob et al. 1998) and the current mapping. While the unsupervised Independent Components Analysis (ICA) change detection technique indicated some changes in habitat extent and distribution, considerable areas of habitat change observed in the post-classification approach are questionable, and may reflect misclassifications rather than real change. A particular example of this is an apparent large decrease in Zosteraceae and increase in Posidonia being related to the classification of Posidonia beds as Zosteraceae in the 1998 mapping. Despite this, we believe that changes indicated by both the ICA and post-classification approaches have a high likelihood of being ‘actual’ change. A pattern of gains and losses of Zosteraceae in the region north of Stockyard channel is an example of this. Further analyses and refinements of approaches in change detection analyses such as would improve confidence in the location and extent of habitat changes over this time period.

This work has been successful in providing new baseline maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Population consequences of a predator-induced habitat shift by trout in whole-lake experiments

In a replicated whole-lake experiment, we (a) tested for the existence of a flexible habitat shift in response to predator presence in age-0 rainbow trout (Oncorhynchus mykiss) at risk of cannibalism and (b) evaluated the population-level consequences of habitat shifts in terms of growth and survival over their first growing season. Daphnid food and adult trout predators were substantially more abundant in pelagic than in littoral habitats. Age-0 trout used all habitats in populations without adult trout predators, whereas age-0 trout were observed only in the less profitable littoral habitat in populations with adult trout. Consequently, mean fall mass of age-0 trout in the presence of predators was almost half that observed in populations without adult trout. Despite the shift in habitat use, age-0 trout experienced 90% mortality when adult trout predators were present, in comparison to only 36% mortality when absent. We conclude that the commonly observed habitat shifts by fish at risk of predation, observed at smaller scales, do in fact occur at the whole-system scale over long time intervals. These results suggest that fish are able to perceive risk at large spatial scales and thus take advantage of profitable (but normally risky) habitats when predators are absent, or move to less profitable refuge habitats when predators are present.

Little evidence that condition, stress indicators, sex ratio, or homozygosity are related to landscape or habitat attributes in declining woodland birds

Habitat loss, fragmentation and degradation are drivers of major declines in biodiversity and species extinctions. The actual causes of species population declines following habitat change are more difficult to discern and there is typically high covariation among the measures used to infer the causes of decline. The causes of decline may act directly on individual fitness and survival, or through disruption of population processes. We examined the relationships among configuration, extent and status of native vegetation and three commonly used indicators of individual body condition and chronic stress (haemoglobin level, haematocrit, residual body mass condition index) in 13 species of woodland-dependent birds in south-eastern Australia. We also examined two measures of changes to population processes (sex ratio and individual homozygosity) in ten species and alleic richness in five species. We found little support for relationships between site or landscape characteristics and individual or population response variables, notwithstanding that our simulations showed we had sufficient power to detect relatively small effects. We discuss possible causes of the absence of detectable habitat effects in this system and the implications for the usefulness of individual body condition and easily measured haematological indices as indicators of the response of avian populations to habitat change. © 2012 The Authors.

Evaluation of four supervised learning methods for benthic habitat mapping using backscatter from multi-beam sonar

An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES) technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC), Quick, Unbiased, Efficient Statistical Tree (QUEST), Random Forest (RF) and Support Vector Machine (SVM) were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats. © 2012 by the authors.

Quantitative experimental comparison of single-beam, sidescan, and multibeam benthic habitat maps

Map comparison is a relatively uncommon practice in acoustic seabed classification to date, contrary to the field of land remote sensing, where it has been developed extensively over recent decades. The aim here is to illustrate the benefits of map comparison in the underwater realm with a case study of three maps independently describing the seabed habitats of the Te Matuku Marine Reserve (Hauraki Gulf, New Zealand). The maps are obtained from a QTC View classification of a single-beam echosounder (SBES) dataset, manual segmentation of a sidescan sonar (SSS) mosaic, and automatic classification of a backscatter dataset from a multibeam echosounder (MBES). The maps are compared using pixel-to-pixel similarity measures derived from the literature in land remote sensing. All measures agree in presenting the MBES and SSS maps as the most similar, and the SBES and SSS maps as the least similar. The results are discussed with reference to the potential of MBES backscatter as an alternative to SSS mosaic for imagery segmentation and to the potential of joint SBES–SSS survey for improved habitat mapping. Other applications of map-similarity measures in acoustic classification of the seabed are suggested.

Comparison of a self-processed EM3000 multibeam echosounder dataset with a QTC view habitat mapping and a sidescan sonar imagery, Tamaki Strait, New Zealand

A methodology for automatically processing the data files from an EM3000 multibeam echosounder (Kongsberg Maritime, 300 kHz) is presented. Written in MatLab, it includes data extraction, bathymetry processing, computation of seafloor local slope, and a simple correction of the backscatter along-track banding effect. The success of the latter is dependent on operational restrictions, which are also detailed. This processing is applied to a dataset acquired in 2007 in the Tamaki Strait, New Zealand. The resulting maps are compared with a habitat classification obtained with the acoustic ground-discrimination software QTC View linked to a 200-kHz single-beam echosounder and to the imagery from a 100-kHz sidescan sonar survey, both performed in 2002. The multibeam backscatter map was found to be very similar to the sidescan imagery, quite correlated to the QTC View map on one site but mainly uncorrelated on another site. Hypotheses to explain these results are formulated and discussed. The maps and the comparison to prior surveys are used to draw conclusions on the quality of the code for further research on multibeam benthic habitat mapping.

Corner Inlet and Nooramunga Habitat Mapping Project – Part 2 : High resolution mapping and change detection analysis using 2011 Rapid Eye Satellite Image compared to 2009 ALOS Satellite Image

Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Habitat utilization by juvenile hawksbill turtles (Eretmochelys imbricata, Linnaeus, 1766) around a shallow water coral reef

Contemporary studies of sea turtle diving behaviour are generally based upon sophisticated techniques such as the attachment of time depth recorders. However, if the risks of misinterpretation are to be minimized, it is essential that electronic data are analysed in the light of first-hand observations. To this aim, we set out to make observations of juvenile hawksbill turtles (Eretmochelys imbricata, Linnaeus, 1766) foraging and resting in a shallow water coral reef habitat around the granitic Seychelles (4°'S, 55°'E). Data were collected from six study sites characterized by a shallow reef plateau (<5 m) and a flat sandy area at the base of the reef face (<10 m). Observation data were categorized into the following behaviours: (1) stationary foraging; (2) active foraging; (3) resting; and (4) assisted resting. Central to this investigation was the development of a technique for accurately estimating the size of sea turtles in situ based upon previously tested techniques for reef fishes. This revealed that through calibration, the curved carapace length (CCL) of marine turtles can be consistently estimated to within 10 cm of their actual size. Although rudimentary, this has advantages for assessing the residency or absence of specific life history stages from particular environments. Indeed, our data supported previous claims that following the reproductive season, adult hawksbills in the region may move away from the nesting beaches to alternative foraging grounds whilst immature turtles (following the pelagic juvenile stage) may opt to reside in areas close to their natal beaches. With regards to habitat utilization, juvenile hawksbills displayed an alternating pattern of short, shallow foraging dives followed by deeper, longer resting dives. These findings are consistent with previous electronic studies of free-range diving in this species and suggest that the maximization of resting duration may be an important factor driving this behaviour.