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The Komodo dragon ( Varanus komodoensis ) is an endangered, island-endemic species with a naturally restricted distribution. Despite this, no previous studies have attempted to predict the effects of climate change on this iconic species. We used extensive Komodo dragon monitoring data, climate, and sea-level change projections to build spatially explicit demographic models for the Komodo dragon. These models project the species' future range and abundance under multiple climate change scenarios. We ran over one million model simulations with varying model parameters, enabling us to incorporate uncertainty introduced from three main sources: (a) structure of global climate models, (b) choice of greenhouse gas emission trajectories, and (c) estimates of Komodo dragon demographic parameters. Our models predict a reduction in range-wide Komodo dragon habitat of 8%-87% by 2050, leading to a decrease in habitat patch occupancy of 25%-97% and declines of 27%-99% in abundance across the species' range. We show that the risk of extirpation on the two largest protected islands in Komodo National Park (Rinca and Komodo) was lower than other island populations, providing important safe havens for Komodo dragons under global warming. Given the severity and rate of the predicted changes to Komodo dragon habitat patch occupancy (a proxy for area of occupancy) and abundance, urgent conservation actions are required to avoid risk of extinction. These should, as a priority, be focused on managing habitat on the islands of Komodo and Rinca, reflecting these islands' status as important refuges for the species in a warming world. Variability in our model projections highlights the importance of accounting for uncertainties in demographic and environmental parameters, structural assumptions of global climate models, and greenhouse gas emission scenarios when simulating species metapopulation dynamics under climate change., Competing Interests: None declared., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

In its invasive range in Australia, the European rabbit threatens the persistence of native flora and fauna and damages agricultural production. Understanding its distribution and ecological niche is critical for developing management plans to reduce populations and avoid further biodiversity and economic losses.We developed an ensemble of species distribution models (SDMs) to determine the geographic range limits and habitat suitability of the rabbit in Australia. We examined the advantage of incorporating data collected by citizens (separately and jointly with expert data) and explored issues of spatial biases in occurrence data by implementing different approaches to generate pseudo-absences. We evaluated the skill of our model using three approaches: cross-validation, out-of-region validation, and evaluation of the covariate response curves according to expert knowledge of rabbit ecology.Combining citizen and expert occurrence data improved model skill based on cross-validation, spatially reproduced important aspects of rabbit ecology, and reduced the need to extrapolate results beyond the studied areas.Our ensemble model projects that rabbits are distributed across approximately two thirds of Australia. Annual maximum temperatures >25°C and annual minimum temperatures >10°C define, respectively, the southern and northern most range limits of its distribution. In the arid and central regions, close access to permanent water (≤~ 0.4 km) and reduced clay soil composition (~20%-50%) were the major factors influencing the probability of occurrence of rabbits. Synthesis and applications . Our results show that citizen science data can play an important role in managing invasive species by providing missing information on occurrences in regions not surveyed by experts because of logistics or financial constraints. The additional sampling effort provided by citizens can improve the capacity of SDMs to capture important elements of a species ecological niche, improving the capacity of statistical models to accurately predict the geographic range of invasive species., Competing Interests: None declared., (© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost-effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population- and community-level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate-induced changes, which will inform effective management actions for promoting biodiversity resilience.

The distribution of antilopine wallaroo, Macropus antilopinus , is marked by a break in the species' range between Queensland and the Northern Territory, coinciding with the Carpentarian barrier. Previous work on M. antilopinus revealed limited genetic differentiation between the Northern Territory and Queensland M. antilopinus populations across this barrier. The study also identified a number of divergent lineages in the Northern Territory, but was unable to elucidate any geographic structure. Here, we re-examine these results to (1) determine phylogeographic patterns across the range of M. antilopinus and (2) infer the biogeographic barriers associated with these patterns. The tropical savannahs of northern Australia: from the Cape York Peninsula in the east, to the Kimberley in the west. We examined phylogeographic patterns in M. antilopinus using a larger number of samples and three mtDNA genes: NADH dehydrogenase subunit 2, cytochrome b, and the control region. Two datasets were generated and analyzed: (1) a subset of samples with all three mtDNA regions concatenated together and (2) all samples for just control region sequences that included samples from the previous study. Analysis included generating phylogenetic trees based on Bayesian analysis and intraspecific median-joining networks. The contemporary spatial structure of M. antilopinus mtDNA lineages revealed five shallow clades and a sixth, divergent lineage. The genetic differences that we found between Queensland and Northern Territory M. antilopinus samples confirmed the split in the geographic distribution of the species. We also found weak genetic differentiation between Northern Territory samples and those from the Kimberley region of Western Australia, possibly due to the Kimberley Plateau-Arnhem Land barrier. Within the Northern Territory, two clades appear to be parapatric in the west, while another two clades are broadly sympatric across the Northern Territory. MtDNA diversity of M. antilopinus revealed an unexpectedly complex evolutionary history involving multiple sympatric and parapatric mtDNA clades across northern Australia. These phylogeographic patterns highlight the importance of investigating genetic variation across distributions of species and integrating this information into biodiversity conservation.

The Earth's climate is undergoing rapid warming, unprecedented in recent times, which is driving shifts in the distribution and phenology of many plants and animals. Quantifying changes in breeding phenology is important for understanding how populations respond to these changes. While data on shifts in phenology are common for Northern Hemisphere species (especially birds), there is a dearth of evidence from the Southern Hemisphere, and even fewer data available from the marine environment. Surface air temperatures at Macquarie Island have increased by 0.62°C during the 30-year study period (0.21°C decade(-1)) and royal penguins (Eudyptes schlegeli) commenced egg laying on average three days earlier in the 1990s than during the 1960s. This contrasts with other studies of Southern Ocean seabirds; five of nine species are now breeding on average 2.1 days later than during the 1950s. Despite the different direction of these trends, they can be explained by a single underlying mechanism: resource availability. There was a negative relationship between the Southern Annular Mode (SAM) and median laying date of royal penguins, such that low-productivity (low SAM) years delayed laying date. This accords with the observations of other seabird species from the Antarctic, where later laying dates were associated with lower sea ice and lower spring productivity. The unifying factor underpinning phenological trends in eastern Antarctica is therefore resource availability; as food becomes scarcer, birds breed later. These changes are not uniform across the region, however, with resource increases in the subantarctic and decreases in eastern Antarctica.