Regionalization of landscape pattern indices using multivariate cluster analysis

This project was funded by the Government of Canada through the Mountain Pine Beetle Program, a six-year, $40 million program administered by Natural Resources Canada, Canadian Forest Service. Additional information on the Mountain Pine Beetle Program may be found at: http://mpb.cfs.nrcan.gc.ca.Regionalization, or the grouping of objects in space, is a useful tool for organizing, visualizing, and synthesizing the information contained in multivariate spatial data. Landscape pattern indices can be used to quantify the spatial pattern (composition and configuration) of land cover features. Observable patterns can be linked to underlying processes affecting the generation of landscape patterns (e.g., forest harvesting). The objective of this research is to develop an approach for investigating the spatial distribution of forest pattern across a study area where forest harvesting, other anthropogenic activities, and topography, are all influencing forest pattern. We generate spatial pattern regions (SPR) that describe forest pattern with a regionalization approach. Analysis is performed using a 2006 land cover dataset covering the Prince George and Quesnel Forest Districts, 5.5 million ha of primarily forested land base situated within the interior plateau of British Columbia, Canada. Multivariate cluster analysis (with the CLARA algorithm) is used to group landscape objects containing forest pattern information into SPR. Of the six generated SPR, the second cluster (SPR2) is the most prevalent covering 22% of the study area. On average, landscapes in SPR2 are comprised of 55.5% forest cover, and contain the highest number of patches, and forest/non-forest joins, indicating highly fragmented landscapes. Regionalization of landscape pattern metrics provides a useful approach for examining the spatial distribution of forest pattern. Where forest patterns are associated with positive or negative environmental conditions, SPR can be used to identify similar regions for conservation or management activities.PostprintPeer reviewe

Modeling movement probabilities within heterogeneous spatial fields

Recent efforts have focused on modeling the internal structure of space-time prisms to estimate the unequal movement opportunities within. This paper further develops this area of research by formulating a model for field-based time geography that can be used to probabilistically model movement opportunities conditioned on underlying heterogeneous spatial fields. The development of field-based time geography draws heavily on well-established methods for cost-distance analysis, common to most GIS software packages. The field-based time geographic model is compared with two alternative approaches that are commonly employed to estimate probabilistic space-time prisms - (truncated) Brownian bridges and time geographic kernel density estimation. Using simulated scenarios it is demonstrated that only field-based time geography captures underlying heterogeneity in output movement probabilities. Field-based time geography has significant potential in the field of wildlife tracking (an example is provided), where Brownian bridge models are preferred, but fail to adequately capture underlying barriers to movement.Publisher PDFPeer reviewe

Impacts of human hunting on spatial behavior of white-tailed deer (Odocoileus virginianus)

This study was funded by The Samuel Roberts Noble Foundation, Inc., and the Department of Wildlife, Fisheries and Aquaculture at Mississippi State University.Predators can influence populations through top-down effects, but most large predators have been extirpated from the white-tailed deer’s (Odocoileus virginianus) range. Hunters have filled this predatory role, but also can indirectly influence prey species. Indirect behavioral responses can include altered resource selection, space use, or movement patterns. Herein, we developed a controlled study that contained both temporal and spatial risk levels to assess how deer behavior changes in space relative to temporal periods of risk. Total distance travelled (m) and micro-range area (m²) were calculated over two-day periods to determine the general effects of hunting season on deer spatial behavior. Generally, distance travelled, micro-range area, and exploratory behavior decreased during the course of the study, with the greatest decrease occurring during the active 16-day hunting period. Despite potential risk and disturbance from hunters, deer maintained site fidelity to previously established ranges and did not expand micro-range areas. These data indicate that deer recognize threats from humans on the landscape and adapt behavioral strategies by minimizing movement and exhibiting high residency times in well-established ranges, factors known to influence harvest susceptibility. This information can be used to assess potential impacts from hunting for management purposes, but also to test the adaptive ability of animals to risk.Publisher PDFPeer reviewe

An ALS-associated variant of the autophagy receptor SQSTM1/p62 reprograms binding selectivity toward the autophagy-related hATG8 proteins

Recognition of human autophagy-related 8 (hATG8) proteins by autophagy receptors represents a critical step within this cellular quality control system. Autophagy impairment is known to be a pathogenic mechanism in the motor neuron disorder amyotrophic lateral sclerosis (ALS). Overlapping but specific roles of hATG8 proteins belonging to the LC3 and GABARAP subfamilies are incompletely understood, and binding selectivity is typically overlooked. We previously showed that an ALS-associated variant of the SQSTM1/p62 (p62) autophagy receptor bearing an L341V mutation within its ATG8-interacting motif (AIM) impairs recognition of LC3B in vitro, yielding an autophagy-deficient phenotype. Improvements in understanding of hATG8 recognition by AIMs now distinguish LC3-interaction and GABARAP-interaction motifs and predict the effects of L341V substitution may extend beyond loss of function to biasing AIM binding preference. Through biophysical analyses, we confirm impaired binding of the L341V-AIM mutant to LC3A, LC3B, GABARAP, and GABARAPL1. In contrast, p62 AIM interactions with LC3C and GABARAPL2 are unaffected by this mutation. Isothermal titration calorimetry and NMR investigations provided insights into the entropy-driven GABARAPL2/p62 interaction and how the L341V mutation may be tolerated. Competition binding demonstrated reduced association of the L341V-AIM with one hATG8 manifests as a relative increase in association with alternate hATG8s, indicating effective reprogramming of hATG8 selectivity. These data highlight how a single AIM peptide might compete for binding with different hATG8s and suggest that the L341V-AIM mutation may be neomorphic, representative of a disease mechanism that likely extends into other human disorders

Uncovering a Massive z~7.65 Galaxy Hosting a Heavily Obscured Radio-Loud QSO Candidate in COSMOS-Web

In this letter, we report the discovery of the highest redshift, heavily obscured, radio-loud QSO candidate selected using JWST NIRCam/MIRI, mid-IR, sub-mm, and radio imaging in the COSMOS-Web field. Using multi-frequency radio observations and mid-IR photometry, we identify a powerful, radio-loud (RL), growing supermassive black hole (SMBH) with significant spectral steepening of the radio SED ($f_{1.32 \mathrm{GHz}} \sim 2$ mJy, $q_{24\mu m} = -1.1$, $\alpha_{1.32-3\mathrm{GHz}}=-1.2$, $\Delta \alpha = -0.4$). In conjunction with ALMA, deep ground-based observations, ancillary space-based data, and the unprecedented resolution and sensitivity of JWST, we find no evidence of QSO contribution to the UV/optical/NIR data and thus infer heavy amounts of obscuration (N$_{\mathrm{H}} > 10^{23}$ cm$^{-2}$). Using the wealth of deep UV to sub-mm photometric data, we report a singular solution photo-z of $z_\mathrm{phot}$ = 7.65$^{+0.4}_{-0.3}$ and estimate an extremely massive host-galaxy ($\log M_{\star} = 11.92 \pm 0.06\,\mathrm{M}_{\odot}$). This source represents the furthest known obscured RL QSO candidate, and its level of obscuration aligns with the most representative but observationally scarce population of QSOs at these epochs.Comment: Submitted to ApJL, Comments welcom

Measuring Dynamic Interaction in Movement Data

The emergence of technologies capable of storing detailed records of object locations has presented scientists and researchers with a wealth of data on object movement. Yet analytical methods for investigating more advanced research questions from such detailed movement datasets remain limited in scope and sophistication. Recent advances in the study of movement data has focused on characterizing types of dynamic interactions, such as single-file motion, while little progress has been made on quantifying the degree of such interactions. In this article, we introduce a new method for measuring dynamic interactions (termed DI) between pairs of moving objects. Simulated movement datasets are used to compare DI with an existing correlation statistic. Two applied examples, team sports and wildlife, are used to further demonstrate the value of the DI approach. The DI method is advantageous in that it measures interaction in both movement direction (termed azimuth) and displacement. Also, the DI approach can be applied at local, interval, episodal, and global levels of analysis. However the DI method is limited to situations where movements of two objects are recorded at simultaneous points in time. In conclusion, DI quantifies the level of dynamic interaction between two moving objects, allowing for more thorough investigation of processes affecting interactive moving objects.PostprintPeer reviewe

Toward a kinetic-based probabilistic time geography

Time geography represents a powerful framework for the quantitative analysis of individual movement. Time geography effectively delineates the space–time boundaries of possible individual movement by characterizing movement constraints. The goal of this paper is to synchronize two new ideas, probabilistic time geography and kinetic-based time geography, to develop a more realistic set of movement constraints that consider movement probabilities related to object kinetics. Using random-walk theory, the existing probabilistic time geography model characterizes movement probabilities for the space–time cone using a normal distribution. The normal distribution has a symmetric probability density function and is an appropriate model in the absence of skewness – which we relate to an object’s initial velocity. Moving away from a symmetric distribution for movement probabilities, we propose the use of the skew-normal distribution to model kinetic-based movement probabilities, where the degree and direction of skewness is related to movement direction and speed. Following a description of our model, we use a set of case-studies to demonstrate the skew-normal model: a random walk, a correlated random walk, wildlife data, cyclist data, and athlete movement data. Our results show that for objects characterized by random movement behavior, the existing model performs well, but for object movement with kinetic properties (e.g., athletes), the proposed model provides a substantial improvement. Future work will look to extend the proposed probabilistic framework to the space–time prism.PostprintPeer reviewe