Human land uses reduce climate connectivity across North America

Climate connectivity, the ability of a landscape to promote or hinder the movement of organisms in response to a changing climate, is contingent on multiple factors including the distance organisms need to move to track suitable climate over time (i.e. climate velocity) and the resistance they experience along such routes. An additional consideration which has received less attention is that human land uses increase resistance to movement or alter movement routes and thus influence climate connectivity. Here we evaluate the influence of human land uses on climate connectivity across North America by comparing two climate connectivity scenarios, one considering climate change in isolation and the other considering climate change and human land uses. In doing so, we introduce a novel metric of climate connectivity, ‘human exposure’, that quantifies the cumulative exposure to human activities that organisms may encounter as they shift their ranges in response to climate change. We also delineate potential movement routes and evaluate whether the protected area network supports movement corridors better than non‐protected lands. We found that when incorporating human land uses, climate connectivity decreased; climate velocity increased on average by 0.3 km/year and cumulative climatic resistance increased for ~83% of the continent. Moreover, ~96% of movement routes in North America must contend with human land uses to some degree. In the scenario that evaluated climate change in isolation, we found that protected areas do not support climate corridors at a higher rate than non‐protected lands across North America. However, variability is evident, as many ecoregions contain protected areas that exhibit both more and less representation of climate corridors compared to non‐protected lands. Overall, our study indicates that previous evaluations of climate connectivity underestimate climate change exposure because they do not account for human impacts.     

Spatial connectedness imposes local‐ and metapopulation‐level selection on life history through feedbacks on demography

Dispersal evolution impacts the fluxes of individuals and hence, connectivity in metapopulations. Connectivity is therefore decoupled from the structural connectedness of the patches within the spatial network. Because of demographic feedbacks, local selection also drives the evolution of other life history traits. We investigated how different levels of connectedness affect trait evolution in experimental metapopulations of the two‐spotted spider mite. We separated local‐ and metapopulation‐level selection and linked trait divergence to population dynamics. With lower connectedness, an increased starvation resistance and delayed dispersal evolved. Reproductive performance evolved locally by transgenerational plasticity or epigenetic processes. Costs of dispersal, but also changes in local densities and temporal fluctuations herein are found to be putative drivers. In addition to dispersal, demographic traits are able to evolve in response to metapopulation connectedness at both the local and metapopulation level by genetic and/or non‐genetic inheritance. These trait changes impact the persistence of spatially structured populations.     

Spatial graphs highlight how multi-generational dispersal shapes landscape genetic patterns

Current approaches that compare spatial genetic structure of a given species and the dispersal of its mobile phase can detect a mismatch between both patterns mainly due to processes acting at different temporal scales. Genetic structure result from gene flow and other evolutionary and demographic processes over many generations, while dispersal predicted from the mobile phase often represents solely one generation on a single time-step. In this study, we present a spatial graph approach to landscape genetics that extends connectivity networks with a stepping-stone model to represent dispersal between suitable habitat patches over multiple generations. We illustrate the approach with the case of the striped red mullet Mullus surmuletus in the Mediterranean Sea. The genetic connectivity of M. surmuletus was not correlate with the estimated dispersal probability over one generation, but with the stepping-stone estimate of larval dispersal, revealing the temporal scale of connectivity across the Mediterranean Sea. Our results highlight the importance of considering multiple generations and different time scales when relating demographic and genetic connectivity. The spatial graph of genetic distances further untangles intra-population genetic structure revealing the Siculo-Tunisian Strait as an important corridor rather than a barrier for gene flow between the Western- and Eastern Mediterranean basins, and identifying Mediterranean islands as important stepping-stones for gene flow between continental populations. Our approach can be easily extended to other systems and environments.     

Beyond the landscape: Resistance modelling infers physical and behavioural gene flow barriers to a mobile carnivore across a metropolitan area

Urbanization affects key aspects of wildlife ecology. Dispersal in urban wildlife species may be impacted by geographical barriers but also by a species’ inherent behavioural variability. There are no functional connectivity analyses using continuous individual‐based sampling across an urban‐rural continuum that would allow a thorough assessment of the relative importance of physical and behavioural dispersal barriers. We used 16 microsatellite loci to genotype 374 red foxes (Vulpes vulpes) from the city of Berlin and surrounding rural regions in Brandenburg in order to study genetic structure and dispersal behaviour of a mobile carnivore across the urban‐rural landscape. We assessed functional connectivity by applying an individual‐based landscape genetic optimization procedure. Three commonly used genetic distance measures yielded different model selection results, with only the results of an eigenvector‐based multivariate analysis reasonably explaining genetic differentiation patterns. Genetic clustering methods and landscape resistance modelling supported the presence of an urban population with reduced dispersal across the city border. Artificial structures (railways, motorways) served as main dispersal corridors within the cityscape, yet urban foxes avoided densely built‐up areas. We show that despite their ubiquitous presence in urban areas, their mobility and behavioural plasticity, foxes were affected in their dispersal by anthropogenic presence. Distinguishing between man‐made structures and sites of human activity, rather than between natural and artificial structures, is thus essential for better understanding urban fox dispersal. This differentiation may also help to understand dispersal of other urban wildlife and to predict how behaviour can shape population genetic structure beyond physical barriers.     

Migration sources and pathways of the pest species Sogatella furcifera in Yunnan,China, and across the border inferred from DNA and wind analyses

The migration sources and pathways of Sogatella furcifera (Horváth) in topologically complex regions like Yunnan, China, and adjacent montane areas have long been a challenging task and a bottleneck in effective pest forecast and control. The present research reinvestigated this issue using a combination of mtDNA and long‐term historical wind field data in an attempt to provide new insights. Genetic analyses showed that the 60 populations of S. furcufera collected across Myanmar, Thailand, Laos, Vietnam, Yunnan, Guizhou, and Sichuan lack genetic structure and geographic isolation, while spatial analysis of haplotype and diversity indices discovered geographic relevance between populations. Migration rate analysis combined with high‐resolution 10‐year wind field analysis detected the following migration sources, pathways, and impacted areas which could explain the outbreak pattern in Yunnan. (a) Dominating stepwise northward migrations originated from northern Indochina, southern Yunnan, and central‐eastern Yunnan, impacting their northern areas. (b) Concurring summer–autumn southward (return) migration originated from nearly all latitude belts of Sichuan and Yunnan mainly impacting central and southern Yunnan. (c) Regular eastward and summer–autumn westward migrations across Yunnan. The northward migration reflects the temporal rhythm of gradual outbreaks from the south to the north in a year, while the return migration may explain the repeated or very severe outbreaks in the impacted areas. To form a better pest forecast and control network, attention must also be paid to the northern part of Yunnan to suppress the impact of return migration in summers and autumns.     

Geoclimatic factors influence the population genetic connectivity of Incarvillea arguta (Bignoniaceae) in the Himalaya–Hengduan Mountains biodiversity hotspot

Geoclimatic factors related to the uplift of the Himalaya and the Quaternary climatic oscillations influence the population genetic connectivity in the Himalaya–Hengduan Mountains (HHM) biodiversity hotspot. Therefore, to explore the relative roles played by these two factors, we examined the population dynamics and dispersal corridors of Incarvillea arguta (Royle) Royle incorporating ensemble species distribution modelling (SDM). Thirty‐seven populations were genotyped using plastid chloroplast DNA and low copy nuclear gene (ncpGS) sequences. Phylogeographic analysis was carried out to reveal the genetic structure and lineage differentiation. Ensemble SDMs were carried out for distributional change in the last glacial maximum, present, and future. Finally, the least cost path method was used to trace out possible dispersal corridors. The haplotypes were divided into four clades with strong geographical structure. The late Miocene origin of I. arguta in the western Himalaya ca. 7.92 Ma indicates lineage diversification related to the uplift of the HHM. The variability in habitat connectivity revealed by SDM is due to change in suitability since the Pleistocene. A putative dispersal corridor was detected along the drainage systems and river valleys, with strong support in the eastern Hengduan Mountains group. Our results support the signature of geoclimatic influence on population genetic connectivity of I. arguta in the HHM. We proposed that the major drainage systems might have assisted the rapid dispersal of isolated riverine plant species I. arguta in the HHM. The population genetic connectivity, using the fine‐tuned ensemble SDMs, enables scientists and policymakers to develop conservation strategies for the species gene pool in the HHM biodiversity hotspots.     

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.     

An assessment of the seascape genetic structure and hydrodynamic connectivity for subtropical seagrass restoration

Seagrass ecosystems have suffered significant declines globally and focus is shifting to restoration efforts. A key component to successful restoration is an understanding of the genetic factors potentially influencing restoration success. This includes understanding levels of connectivity between restoration locations and neighboring seagrass populations that promote natural recovery (source and sink populations), the identification of potential donor populations, and assessment of genetic diversity of restored meadows and material used for restoration. In this study, we carry out genetic surveys of 352 individuals from 13 populations using 11 polymorphic microsatellite loci to inform seagrass restoration activities by: (1) understanding levels of genetic and genotypic diversity within meadows; and (2) understanding genetic structure and patterns of connectivity among these meadows to determine which source sites may be most appropriate to assist recovery of three restoration sites. The study identified high genotypic diversity within the locations analyzed from the Port of Gladstone and Rodd's Bay region, indicating sexual reproduction is important in maintaining populations. Overall, we detected significant genetic structuring among sites with the Bayesian structure analysis identifying genetic clusters that largely conformed to a northern, central, and southern region. This suggests limited gene flow between regions, although there does appear to be some connectivity within regions. The hydrodynamic models showed that seeds were largely locally retained, while fragments were more widely dispersed. Limited gene flow between regions suggests donor material for restoration should be sourced locally where possible.     

Establishing Restoration Strategy of Eastern Oyster via a Coupled Biophysical Transport Model

For marine fish and invertebrates, larval dispersal plays a critical role in determining connections among source and sink habitats, and the lack of a predictive understanding of larval dispersal is a fundamental obstacle to the development of spatially explicit restoration plans for marine populations. We investigated larval dispersal patterns of eastern oyster in an estuary along the Northern Gulf of Mexico under different simulation scenarios of tidal amplitude and phase, river discharge, wind direction, and larval vertical migration, using a coupled biophysical transport model. We focused on the dispersal of larvae released from the commercially exploited (Cedar Point, CP) and non‐exploited (Bon Secour Bay, BSB) oyster populations. We found that high flushing rates through the dominant inlet prevented larval exchange between the commercially exploited and non‐exploited populations, resulting in negligible connectivity between them. Variations in tidal amplitude, river discharge and wind direction played a more important role in the amount of larvae retained in Mobile Bay when they are released from CP than from BSB. Under most of the scenarios, larvae from BSB were retained around the spawning area, while larvae from CP showed a predominant westward flow. Net sinking behavior of late‐stage larvae increased larval retention in the bay, but physical transport showed a higher impact in the amount of larvae retained. These findings have enhanced our understanding of larval dispersal of eastern oyster in a wide, shallow estuarine system, and been used to establish spatially explicit strategies for oyster restoration in the Mobile Bay system, Alabama.