Aim Species range contractions are increasingly common globally. The niche reduction hypothesis posits that geographic range contractions are often patterned across space owing to heterogeneity in threat impacts and tolerance. We applied the niche reduction hypothesis to the decline of a threatened marsupial predator across northern Australia, the northern quoll (Dasyurus hallucatus). Location Northern Australia. Methods We assembled a database containing 3,178 historic and contemporary records for northern quolls across the extent of their distribution dating between 1778 and 2019. Based on these records, we estimated changes in the geographic range of the northern quoll using α‐hulls across four main populations. We then examined how range contractions related to factors likely to mediate the exposure, susceptibility, or tolerance of northern quolls to threats. Result The extent of range contractions showed an east–west gradient, most likely reflecting the timing of spread of introduced cane toads (Rhinella marina). There were clear changes in environmental characteristics within the contemporary compared to the historic geographic range, with the most substantial occurring in populations that have suffered the greatest range contractions. The contemporary range is comprised of higher quality habitats (measured using environmental niche models), characterized by higher topographical ruggedness and annual rainfall, and reduced distance to water, compared to the historic range. Main conclusions Changes to range and niche likely reflect the capacity of complex habitats to ameliorate threats (namely predation and altered fire regimes), and access to resources that increase threat tolerance. This study highlights the multivariate nature of ecological refuges and the importance of high‐quality habitats for the persistence of species exposed to multiple threats. Our methods provide a useful framework which can be applied across taxa in providing valuable insight to management.

Developing an organic luminescent solar concentrator (LSC), featuring ultralong lifetime and high transparency simultaneously, is crucial for building-integrated photovoltaic applications, such as solar energy harvesting clear windows. In this paper, a tandem organic LSC is encapsulated and connected with three optically transparent layers, namely an encapsulating epoxy layer and two insulating SiO2 layers that prevent dissolving the organic dyes into the epoxy layer. Experimental results demonstrate that the encapsulated organic LSC maintains the high average transmission of 60% in the visible range of 390-750 nm, and has an ultralong lifetime of ∼ 6.7 × 104 h under illuminated test in laboratory environment, which is around five times longer than that of the organic LSC without any encapsulation. In addition, experiments confirm that most of the photoluminescence radiation generated in the organic dyes is trapped in the high-index SiO2/epoxy/SiO2 structure, and guided between the glass substrate before emerging from the four edges of the organic LSC sample for conversion to electricity. A 30% increase in short-circuit current is attained, in comparison with a similar unencapsulated organic LSC structur

Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These data hold the promise to increase the relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled movement data have proved invaluable for understanding large scale processes (e.g., home range, habitat selection, etc.), but modern fine-scale data promise to unlock far more ecological information. While location error can often be ignored in coarsely sampled data, fine-scale data require much more care, and tools to do this have been lacking. Current approaches to dealing with location error largely fall into two categories—either discarding the least accurate location estimates prior to analysis or simultaneously fitting movement and error parameters in a hidden-state model. Unfortunately, both of these approaches have serious flaws. Here, we provide a general framework to account for location error in the analysis of animal tracking data, so that their potential can be unlocked. We apply our error-model-selection framework to 190 GPS, cellular, and acoustic devices representing 27 models from 14 manufacturers. Collectively, these devices are used to track a wide range of animal species comprising birds, fish, reptiles, and mammals of different sizes and with different behaviors, in urban, suburban, and wild settings. Then, using empirical data on tracked individuals from multiple species, we provide an overview of modern, error-informed movement analyses, including continuous-time path reconstruction, home-range distribution, home-range overlap, speed and distance estimation. Adding to these techniques, we introduce new error-informed estimators for outlier detection and autocorrelation visualization. We furthermore demonstrate how error-informed analyses on calibrated tracking data can be necessary to ensure that estimates are accurate and insensitive to location error, and allow researchers to use all of their data. Because error-induced biases depend on so many factors—sampling schedule, movement characteristics, tracking device, habitat, etc.—differential bias can easily confound biological inference and lead researchers to draw false conclusions.

Artificial refuges are human-made structures that aim to create safe places for animals to breed, hibernate, or take shelter in lieu of natural refuges. Artificial refuges are used across the globe to mitigate the impacts of a variety of threats on wildlife, such as habitat loss and degradation. However, there is little understanding of the science underpinning artificial refuges, and what comprises best practice for artificial refuge design and implementation for wildlife conservation. We address this gap by undertaking a systematic review of the current state of artificial refuge research for the conservation of wildlife. We identified 224 studies of artificial refuges being implemented in the field to conserve wildlife species. The current literature on artificial refuges is dominated by studies of arboreal species, primarily birds and bats. Threatening processes addressed by artificial refuges were biological resource use (26%), invasive or problematic species (20%), and agriculture (15%), yet few studies examined artificial refuges specifically for threatened (Vulnerable, Endangered, or Critically Endangered) species (7%). Studies often reported the characteristics of artificial refuges (i.e. refuge size, construction materials; 87%) and surrounding vegetation (35%), but fewer studies measured the thermal properties of artificial refuges (18%), predator activity (17%), or food availability (3%). Almost all studies measured occupancy of the artificial refuges by target species (98%), and over half measured breeding activity (54%), whereas fewer included more detailed measures of fitness, such as breeding productivity (34%) or animal body condition (4%). Evaluating the benefits and impacts of artificial refuges requires sound experimental design, but only 39% of studies compared artificial refuges to experimental controls, and only 10% of studies used a before-after-control-impact (BACI) design. As a consequence, few studies of artificial refuges can determine their overall effect on individuals or populations. We outline a series of key steps in the design, implementation, and monitoring of artificial refuges that are required to avoid perverse outcomes and maximise the chances of achieving conservation objectives. This review highlights a clear need for increased rigour in studies of artificial refuges if they are to play an important role in wildlife conservation.