A framework for modelling soil structure dynamics induced by biological activity

Soil degradation is a worsening global phenomenon driven by socio‐economic pressures, poor land management practices and climate change. A deterioration of soil structure at timescales ranging from seconds to centuries is implicated in most forms of soil degradation including the depletion of nutrients and organic matter, erosion and compaction. New soil–crop models that could account for soil structure dynamics at decadal to centennial timescales would provide insights into the relative importance of the various underlying physical (e.g. tillage, traffic compaction, swell/shrink and freeze/thaw) and biological (e.g. plant root growth, soil microbial and faunal activity) mechanisms, their impacts on soil hydrological processes and plant growth, as well as the relevant timescales of soil degradation and recovery. However, the development of such a model remains a challenge due to the enormous complexity of the interactions in the soil–plant system. In this paper, we focus on the impacts of biological processes on soil structure dynamics, especially the growth of plant roots and the activity of soil fauna and microorganisms. We first define what we mean by soil structure and then review current understanding of how these biological agents impact soil structure. We then develop a new framework for modelling soil structure dynamics, which is designed to be compatible with soil–crop models that operate at the soil profile scale and for long temporal scales (i.e. decades, centuries). We illustrate the modelling concept with a case study on the role of root growth and earthworm bioturbation in restoring the structure of a severely compacted soil.     

Synchronous biological feedbacks in parrotfishes associated with pantropical coral bleaching

Biological feedbacks generated through patterns of disturbance are vital for sustaining ecosystem states. Recent ocean warming and thermal anomalies have caused pantropical episodes of coral bleaching, which has led to widespread coral mortality and a range of subsequent effects on coral reef communities. Although the response of many reef‐associated fishes to major disturbance events on coral reefs is negative (e.g., reduced abundance and condition), parrotfishes show strong feedbacks after disturbance to living reef structure manifesting as increases in abundance. However, the mechanisms underlying this response are poorly understood. Using biochronological reconstructions of annual otolith (ear stone) growth from two ocean basins, we tested whether parrotfish growth was enhanced following bleaching‐related coral mortality, thus providing an organismal mechanism for demographic changes in populations. Both major feeding guilds of parrotfishes (scrapers and excavators) exhibited enhanced growth of individuals after bleaching that was decoupled from expected thermal performance, a pattern that was not evident in other reef fish taxa from the same environment. These results provide evidence for a more nuanced ecological feedback system—one where disturbance plays a key role in mediating parrotfish–benthos interactions. By influencing the biology of assemblages, disturbance can thereby stimulate change in parrotfish grazing intensity and ultimately reef geomorphology over time. This feedback cycle operated historically at within‐reef scales; however, our results demonstrate that the scale, magnitude, and severity of recent thermal events are entraining the biological responses of disparate communities to respond in synchrony. This may fundamentally alter feedbacks in the relationships between parrotfishes and reef systems.     

Functional analysis of RPS27 mutations and expression in melanoma

Next‐generation sequencing has enabled genetic and genomic characterization of melanoma to an unprecedent depth. However, the high mutational background plus the limited depth of coverage of whole‐genome sequencing performed on cutaneous melanoma samples make the identification of novel driver mutations difficult. We sought to explore the somatic mutation portfolio in exonic and gene regulatory regions in human melanoma samples, for which we performed targeted sequencing of tumors and matched germline DNA samples from 89 melanoma patients, identifying known and novel recurrent mutations. Two recurrent mutations found in the RPS27 promoter associated with decreased RPS27 mRNA levels in vitro. Data mining and IHC analyses revealed a bimodal pattern of RPS27 expression in melanoma, with RPS27‐low patients displaying worse prognosis. In vitro characterization of RPS27‐high and RPS27‐low melanoma cell lines, as well as loss‐of‐function experiments, demonstrated that high RPS27 status provides increased proliferative and invasive capacities, while low RPS27 confers survival advantage in low attachment and resistance to therapy. Additionally, we demonstrate that 10 other cancer types harbor bimodal RPS27 expression, and in those, similarly to melanoma, RPS27‐low expression associates with worse clinical outcomes. RPS27 promoter mutation could thus represent a mechanism of gene expression modulation in melanoma patients, which may have prognostic and predictive implications.     

Mapping sea level rise impacts to identify climate change adaptation opportunities in the Chesapeake and Delaware Bays,USA

Wetlands Ecology and Management - Salt marshes are at risk globally if they cannot keep pace with sea level rise. Along the United States Mid-Atlantic coast, high marsh has already declined, and is...     

New Caledonian crows plan for specific future tool use

The ability to plan for future events is one of the defining features of human intelligence. Whether non-human animals can plan for specific future situations remains contentious: despite a sustained research effort over the last two decades, there is still no consensus on this question. Here, we show that New Caledonian crows can use tools to plan for specific future events. Crows learned a temporal sequence where they were (a) shown a baited apparatus, (b) 5 min later given a choice of five objects and (c) 10 min later given access to the apparatus. At test, these crows were presented with one of two tool–apparatus combinations. For each combination, the crows chose the right tool for the right future task, while ignoring previously useful tools and a low-value food item. This study establishes that planning for specific future tool use can evolve via convergent evolution, given that corvids and humans shared a common ancestor over 300 million years ago, and offers a route to mapping the planning capacities of animals.     

Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin,USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream‐segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large‐river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC_C‐selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC_C‐selected models were more inclusive of westward‐situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.     

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.     

Effects of an anthropogenic diet on indicators of physiological challenge and immunity of white ibis nestlings raised in captivity

When wildlife forage and/or live in urban habitats, they often experience a shift in resource availability and dietary quality. Some species even use human handouts, such as bread, as well as human refuse, as a large part of their new diets; yet the influences of this nutritional shift on health and survival remain unclear. American white ibises are increasingly being seen in urban areas in Florida; they collect handouts, such as bread and other food items, from humans in parks, and are also found foraging on anthropogenic sources in trash heaps. We hypothesized that the consumption of these new anthropogenic food sources may trigger increases in indicators of physiological challenge and dampen immune responses. We tested this experimentally by raising 20 white ibis nestlings in captivity, and exposing 10 to a simulated anthropogenic diet (including the addition of white bread and a reduction in seafood content) while maintaining 10 on a diet similar to what ibises consume in more natural environments. We then tested two indicators of physiological challenge (corticosterone and heat shock protein 70), assessed innate immunity in these birds via bactericidal assays and an in vitro carbon clearance assay, and adaptive immunity using a phytohemagglutinin skin test. The anthropogenic diet depressed the development of the ability to kill Salmonella paratyphi in culture. Our results suggest that consuming an anthropogenic diet may be detrimental in terms of the ability to battle a pathogenic bacterial species, but there was little effect on indicators of physiological challenge and other immunological measures.