Leveraging High Resolution Classifications and Random Forests for Hindcasting Decades of Mesic Ecosystem Dynamics in the Landsat Time Series

Mesic ecosystems are fundamental to conservation efforts in semi-arid systems, but are threatened by climate change and development. Newer earth observation datasets, including Sentinel-1 and −2, provide opportunities to monitor mesic ecosystems at meaningful spatial scales, but are insufficient for measuring decadal-scale changes. Conversely, the Landsat time series has decades of data, but images are spatially coarse relative to many of the mesic ecosystem areas that sustain dryland systems, resulting in classifications with mixed pixels inadequate for effective monitoring. We developed a workflow that uses 10-m classifications produced from fusion of the Sentinel-1 and −2 time series (2017–2020) to estimate sub-pixel proportions of Landsat time series observations (2004–2020). Using random forest regression models, we quantified water resource proportions (WRP) of surface water, mesic vegetation, and upland land covers within each 30-m Landsat pixel. We incorporated ancillary covariates to account for varying topographic conditions, land cover, and climate. Results indicate that our approach consistently estimates sub-pixel proportions of Landsat pixels more accurately compared to spectral mixture analysis (SMA). The WRP product for surface water had up to 8% less error than SMA as measured by Mean Absolute Error (MAE) and up to 17% less error as measured by Root Mean Squared Error (RMSE). For mesic vegetation, the WRP product outperformed SMA by up to 4% (MAE) and 7% (RMSE). Finally, we demonstrated the ability of our time series to characterize historical water resource availability at a case study site with a well documented restoration history by qualitatively examining the mesic vegetation dynamics time series to identify system responses to restoration efforts. Our approach allows us to hindcast observations of Sentinel products and measure water resource dynamics with greater precision over larger temporal scales. We envision these WRP data to be useful for measuring the impacts of conservation interventions, disturbance recovery, or land use changes that pre-date the Sentinel time series

Bark beetle population dynamics in the Anthropocene: Challenges and solutions

Tree-killing bark beetles are the most economically important insects in conifer forests worldwide. However, despite N200 years of research, the drivers of population eruptions and crashes are still not fully understood and the existing knowledge is thus insufficient to face the challenges posed by the Anthropocene. We critically analyze potential biotic and abiotic drivers of population dynamics of an exemplary species, the European spruce bark beetle (ESBB) (Ips typographus) and present a multivariate approach that integrates the many drivers governing this bark beetle system. We call for hypothesis-driven, large-scale collaborative research efforts to improve our understanding of the population dynamics of this and other bark beetle pests. Our approach can serve as a blueprint for tackling other eruptive forest insects

Exergy analysis:Tthe effect of relative humidity, air temperature and effective clothing insulation on thermal comfort

abstract onl

Auditory spatial representations of the world are compressed in blind humans

Compared to sighted listeners, blind listeners often display enhanced auditory spatial abilities such as localization in azimuth. However, less is known about whether blind humans can accurately judge distance in extrapersonal space using auditory cues alone. Using virtualization techniques, we show that auditory spatial representations of the world beyond the peripersonal space of blind listeners are compressed compared to those for normally sighted controls. Blind participants overestimated the distance to nearby sources, and underestimated the distance to remote sound sources, in both reverberant and anechoic environments, and for speech, music and noise signals. Functions relating judged and actual virtual distance were well fitted by compressive power functions, indicating that the absence of visual information regarding the distance of sound sources may prevent accurate calibration of the distance information provided by auditory signals

Sensory substitution information informs locomotor adjustments when walking through apertures

The study assessed the ability of the central nervous system (CNS) to use echoic information from sensory substitution devices (SSDs) to rotate the shoulders and safely pass through apertures of different width. Ten visually normal participants performed this task with full vision, or blindfolded using an SSD to obtain information regarding the width of an aperture created by two parallel panels. Two SSDs were tested. Participants passed through apertures of +0%, +18%, +35%, and +70% of measured body width. Kinematic indices recorded movement time, shoulder rotation, average walking velocity across the trial, peak walking velocities before crossing, after crossing and throughout a whole trial. Analyses showed participants used SSD information to regulate shoulder rotation, with greater rotation associated with narrower apertures. Rotations made using an SSD were greater compared to vision, movement times were longer, average walking velocity lower and peak velocities before crossing, after crossing and throughout the whole trial were smaller, suggesting greater caution. Collisions sometimes occurred using an SSD but not using vision, indicating that substituted information did not always result in accurate shoulder rotation judgements. No differences were found between the two SSDs. The data suggest that spatial information, provided by sensory substitution, allows the relative position of aperture panels to be internally represented, enabling the CNS to modify shoulder rotation according to aperture width. Increased buffer space indicated by greater rotations (up to approximately 35% for apertures of +18% of body width), suggests that spatial representations are not as accurate as offered by full vision

Socio-Ecological Interactions Promote Outbreaks of a Harmful Invasive Plant in an Urban Landscape

Urban landscapes often harbour organisms that harm people and threaten native biodiversity. These landscapes are characterized by differences in socioeconomic context, habitat suitability and patch connectedness. Identifying which spatial differences enable outbreaks of pests, pathogens and invasive species will improve targeted control efforts. We tested hypotheses to explain the distribution and demography of puncturevine Tribulus terrestris, a human-dispersed invasive plant in Boise, a city in the western United States. We hypothesized an increase in puncturevine infestations near low-valued properties with a high proportion of bare ground, the species\u27 preferred microhabitat, that are well connected on the urban road network. To test these hypotheses, we collected data on the abundance, emergence and persistence of reproductive plants in transects spanning \u3e100 km of our study city. We then used hierarchical Bayesian models to evaluate the impacts of spatial covariates on puncturevine distribution and demography. Bare ground cover consistently increased abundance, emergence and persistence of puncturevine, indicating the overarching importance of suitable establishment sites for this invasive species. Property value had the strongest impact on puncturevine abundance and was the most important main effect in the model for puncturevine emergence. In both models, lower-valued properties had a higher risk of puncturevine occurrence. The effects of road network connectivity depended on bare ground cover, with the highest predicted abundance and emergence of puncturevine in patches with low connectivity on the road network and high bare ground cover. Understanding these relationships will require data that can disentangle seed dispersal from establishment limitations