Characterizing change points and continuous transitions in movement behaviours using wavelet decomposition

Multi-mode movement decisions across widely ranging behavioral processes

Movement of organisms plays a fundamental role in the evolution and diversity of life. Animals typically move at an irregular pace over time and space, alternating among movement states. Understanding movement decisions and developing mechanistic models of animal distribution dynamics can thus be contingent to adequate discrimination of behavioral phases. Existing methods to disentangle movement states typically require a follow-up analysis to identify state-dependent drivers of animal movement, which overlooks statistical uncertainty that comes with the state delineation process. Here, we developed population-level, multi-state step selection functions (HMM-SSF) that can identify simultaneously the different behavioral bouts and the specific underlying behavior-habitat relationship. Using simulated data and relocation data from mule deer (Odocoileus hemionus), plains bison (Bison bison bison) and plains zebra (Equus quagga), we illustrated the HMM-SSF robustness, versatility, and predictive ability for animals involved in distinct behavioral processes: foraging, migrating and avoiding a nearby predator. Individuals displayed different habitat selection pattern during the encamped and the travelling phase. Some landscape attributes switched from being selected to avoided, depending on the movement phase. We further showed that HMM-SSF can detect multi-modes of movement triggered by predators, with prey switching to the travelling phase when predators are in close vicinity. HMM-SSFs thus can be used to gain a mechanistic understanding of how animals use their environment in relation to the complex interplay between their needs to move, their knowledge of the environment and navigation capacity, their motion capacity and the external factors related to landscape heterogeneity.

New insights into external layers of cyanobacteria and microalgae based on multiscale analysis of AFM force-distance curves

External layers, the outermost structures around cells, perform essential eco-physiological functions to support cyanobacteria and microalgae in aquatic environments. These layers have been recognized as adaptations to turbulence, a ubiquitous and inherent physical process occurring in the environments of most cyanobacteria and microalgae. However, the underlying biophysical mechanism of these layers is still poorly understood. Force measurements were performed directly on the external layers of eight living cyanobacterial and green algal strains in situ using atomic force microscopy (AFM). We developed a wavelet analysis method based on a multiscale decomposition of derivative force-distance curves to quantify the elastic responses of various external layers upon mechanical deformation. Such analysis has the advantages of detecting singularities and distinguishing the biomechanical contributions of each external layer. The elastic modulus of the same type of external layer follows the same statistical distribution. However, the elastic response among different types of external layers is challenged by our method, indicating the heterogeneity of the mechanical properties of inner and outer layers in multilayer strains. This discrepancy was due to the thickness and texture of each external layer, especially the chemical presence of ribose, hydroxyproline and glutamic acid. This study highlights a new way to elucidate more precise information about external layers and provides a biophysical mechanistic explanation for the functioning of the various external layers to protect cyanobacterial and microalgal cells in a turbulent environment.

Complex life histories discovered in a critically endangered fish

Effective conservation of endangered species requires knowledge of the full range of life-history strategies used to maximize population resilience within a stochastic and ever-changing environment. California’s endemic Delta Smelt (Hypomesus transpacificus) is rapidly approaching extinction in the San Francisco Estuary, placing it in the crossfire between human and environmental uses of limited freshwater resources. Though managed as a semi-anadromous species, recent studies have challenged this lifecycle model for Delta Smelt, suggesting the species is an estuarine resident with several localized “hot-spots” of abundance. Using laser-ablation otolith strontium isotope microchemistry, we discovered three distinct life-history phenotypes including freshwater resident (FWR), brackish-water resident (BWR), and semi-anadromous (SA) fish. We further refined life-history phenotypes using an unsupervised algorithm and hierarchical clustering and found that in the last resilient year-class, the FWR (12%) and BWR (7%) comprised a small portion of the population, while the majority of fish were SA (81%). Furthermore, the semi-anadromous fish could be clustered into at least four additional life-history phenotypes that varied by natal origin, dispersal age and adult salinity history. These diverse life-history strategies should be incorporated into future conservation and management efforts aimed at preventing the extinction of Delta Smelt in the wild.

Remote examination of the seasonal succession of phytoplankton assemblages from time-varying trends

The seasonal succession of phytoplankton assemblages is important to ascertain the dynamics of an aquatic ecosystem structure, whereas its occurrence in response to hydrodynamic alterations is not clearly understood. In view of the characteristics of annual water level variation formed by the Three Gorges Dam Project (TGDP), our understanding about how these changes affect phytoplankton structure and dynamics is still very limited due to the shortage of long-term observation data. In this study, we used Huan Jing 1 charge-coupled device images over the past decade to examine the phytoplankton succession dates between cyanobacterial and green algal blooms in the backwater area of the Three Gorges Reservoir (TGR). The results indicated continuous wavelet transform-based peak analysis is an efficiency tool that can illustrate the temporal pattern of phytoplankton succession using satellite-derived chlorophyll ɑ and Cyano-Chlorophyta index thresholds. Water level, air temperature, pH and total nitrogen/total phosphorus ratio were four important factors affecting the decline and rise phase of cyanobacterial blooms in the TGR from 2008 to 2018. Given that the upstream dam operation is likely to alter ecological and environmental conditions in the backwater area, this mechanism, so-called "water-level linkage", could alleviate the persistent period of cyanobacterial and green algal blooms. Remote sensing together with time series analysis provided a useful method to examine the seasonal succession of phytoplankton assemblages in the TGR, and these findings provided strategic insight for the water-quality management in the post-TGDP period.

A Review of GPS Trajectories Classification Based on Transportation Mode

GPS trajectories generated by moving objects provide researchers with an excellent resource for revealing patterns of human activities. Relevant research based on GPS trajectories includes the fields of location-based services, transportation science, and urban studies among others. Research relating to how to obtain GPS data (e.g., GPS data acquisition, GPS data processing) is receiving significant attention because of the availability of GPS data collecting platforms. One such problem is the GPS data classification based on transportation mode. The challenge of classifying trajectories by transportation mode has approached detecting different modes of movement through the application of several strategies. From a GPS data acquisition point of view, this paper macroscopically classifies the transportation mode of GPS data into single-mode and mixed-mode. That means GPS trajectories collected based on one type of transportation mode are regarded as single-mode data; otherwise it is considered as mixed-mode data. The one big difference of classification strategy between single-mode and mixed-mode GPS data is whether we need to recognize the transition points or activity episodes first. Based on this, we systematically review existing classification methods for single-mode and mixed-mode GPS data and introduce the contributions of these methods as well as discuss their unresolved issues to provide directions for future studies in this field. Based on this review and the transportation application at hand, researchers can select the most appropriate method and endeavor to improve them.

A three-decade review of telemetry studies on vultures and condors

Telemetry-based movement research has become central for learning about the behavior, ecology and conservation of wide-ranging species. Particularly, early telemetry studies were conducted on vultures and condors due to three main reasons: i) these birds capture the curiosity of humans, ii) their large body size allows researchers to deploy large telemetry units, and iii) they are of high conservation concern. This has resulted in a great number of scientific articles that remain scattered throughout the literature. To achieve a more cohesive view of vultures and condors movement behavior, we review all telemetry studies published up to 2017. We first present a descriptive summary of the technical and design characteristics of these studies (e.g. target species, tagging location, number of individuals tagged) and go on to discuss them under a common conceptual framework; the Movement Ecology Paradigm. The articles found (N = 97) were mainly published in the last decade and based on the tagging of individuals from 14 species (61% of the extant species) and 24 countries. Foraging was the most in-depth investigated movement phase (25 studies), with studies covering several species, using both phenomenological and mechanistic approaches and tackling the role of different drivers of movement. In contrast, commuting and natal dispersal phases were only superficially investigated (3 and 8 studies, respectively). Finally, studies dealing with the conservation and management also comprised a large portion of the reviewed articles (24 studies). Telemetry studies have revealed relevant details of vultures and condors movements, with highly accurate measurements of flight energetics and a better understanding of the morphological, physiological and context-dependent drivers that underlie the movement decisions of these birds. However, we also detected several information gaps. We expect this review helps researchers to focus their efforts and funds where more information is needed.