Spatial Replication Research Articles

New dimension in viral hepatitis research

Chronic hepatitis B is the leading cause of hepatocellular carcinoma and a significant global health issue, affecting over 296 million people worldwide, with 15 million people coinfected with hepatitis delta...

Vegetation canopy height shapes bats’ occupancy: a remote sensing approach

ABSTRACT Anthropogenic activities have significantly altered land cover on a global scale. These changes often have a negative effect on biodiversity limiting the distribution of species. The extent of the effect on species’ distribution depends on the landscape composition and configuration at a local and landscape level. To better understand this effect on a large scale, we evaluated how land cover and vegetation structure shape bat species’ occurrence while considering species’ imperfect detection. We hypothesize that intensification of anthropogenic activities in agriculture, for example, reduces heterogeneity of land cover and vegetation structure, and thereby, limits bat occurrence. To investigate this, we conducted acoustic bat sampling across 59 locations in southern Portugal, each with three spatial replicates. We derived fine-scale vegetation structural metrics by combining spaceborne LiDAR (GEDI) and synthetic aperture radar data (Sentinel-1 and ALOS/PALSAR-2). Additionally, we included land cover metrics and high-resolution climate data from CHELSA. Our findings revealed an important relationship between bat species’ occupancy and vegetation structure, particularly with vegetation canopy height. Moreover, forest and shrubland proportions were the main land cover types influencing bat species responses. All species’ best-ranking occupancy models included at least one climatic variable (temperature, humidity, or potential evapotranspiration), demonstrating the importance of climate when predicting bat distribution. Our acoustic surveys had a species’ detection probability varying from 0.19 to 0.86, and it was influenced by night conditions. These findings underscore the importance of modeling imperfect detection, especially for highly vagile and elusive organisms like bats. Our results demonstrate the effectiveness of using vegetation and landscape metrics derived from high-resolution remote sensing data to model species distribution in the context of biodiversity monitoring and conservation.

A Trial of a Virtual Fence to Mitigate Roadkill on an Unsealed Rural Road in Tasmania, Australia.

A commercial roadkill Virtual Fence (VF) mitigation device (iPTE Traffic Solutions) was used in a field trial to test its effectiveness, for which previously published results have been inconsistent, along a 4.9 km segment of road on Bruny Island, Tasmania. A total of 585 days of monitoring roadkill by species was conducted, with six sections that were alternatively switched on or off according to the Crossover and Multiple Before-After-Control-Impact (MBACI) experimental designs that divided monitoring into "off-on" then "on-off" periods. Aggregate counts, for each period by section combination, from daily counts of Tasmanian pademelons (Thylogale billardierii) were modelled, with a total count of 222. The statistical analysis used the MBACI design to estimate the VF effect using a log-odds ratio parameter (LORP) while accounting for local spatio-temporal effects. Both versions of the analysis, either averaged over the three spatial replicates (paired sections) or two temporal replicates (blocks), showed no statistically significant effect of the VF, judged as an LORP estimate not sufficiently below zero. Corresponding percentage reduction estimates of 9% and 16% were derived from the LORP. The corresponding statistical power required to detect a nominal significant reduction of 50% in rate was 0.5 and 0.6, respectively. This study confirms the results from a similar previous field trial in southern Tasmania that this VF is likely to lead to, if anything, only a minor reduction in roadkill.

VGWatch: A low-cost stand-alone monitor to measure the valve gape of bivalves in the field

Valve gape monitors are utilised to measure the extent of bivalve’s shell openings. This measurement is correlated with their filter-feeding activity, and valve closure can serve as an indicator of various environmental stressors, including poor water quality, the presence of predators, and human disturbance. We developed an inexpensive, stand-alone, and reusable valve gape monitor; enabling collection of sufficient and independent spatial replication in situ. The monitor is made using Arduino hardware and software, and we share the design and code. We tested it in the field with three mussels as a proof of concept. The mussels were likely actively feeding most of the time. Two of the mussels were in close vicinity and demonstrated similar valve gape patterns. The monitor enables to measure valve gape in high resolution, providing insights into bivalve biology, ecosystem functioning, and the effects of environmental conditions, including anthropogenic stressors.

Scientific contributions and lessons learned from 30 years of ecological monitoring of the Bylot Island tundra ecosystem

The Arctic tundra has a relatively low biodiversity but species living there have unique adaptations and are exposed to unprecedented rates of climate warming. Monitoring changes in Arctic biodiversity and identifying the driving forces is thus a pressing issue. Bylot Island in the Canadian Arctic has one of the longest and most comprehensive monitoring programs of the tundra food web, spanning four decades. We provide a historical overview of ecological studies on Bylot Island, summarize their key scientific contributions, show their impacts, and present the ingredients for the success of the program and the main challenges encountered. Some major contributions include demonstrating the key role of predation in structuring the tundra food web, the importance of exchanges between ecosystems for the persistence of top predators and their cascading effects on trophic interactions, the apparent resistance of the vertebrate biota to climate warming, the need to consider multiple hypotheses to explain northward range expansion of species and the benefits of integrating scientific data and local knowledge into ecological monitoring. The program has produced >250 journal articles and >80 graduate student theses, which generated >7,700 citations in the scientific literature. A high proportion (65%) of the articles had more citations than comparable publications in their field. The longevity and success of the program can be attributed to several factors, including a researcher-driven (i.e. bottom-up) approach to design the monitoring; long-term commitment of a small number of dedicated researchers and the strong participation of graduate students; the adoption of a food web rather than a single species perspective; extensive presence in the field; the combination of several methodological approaches; and the use of multiple spatial scales adapted to research questions of interest. Challenges encountered include funding issues, transfer of expertise over time, limited spatial replication, statistical design and maintaining partnerships. Robust monitoring is essential to provide sound baseline to detect future changes, and lessons learned from our program could improve future monitoring schemes in the Arctic. Paradoxically, we believe that ecological monitoring on Bylot Island has been successful in large part because it was not originally designed as a monitoring program per se.

Spatial variation of net methane uptake in Arctic and subarctic drylands of Canada and Greenland

The importance of uptake of atmospheric methane (CH4) in dry Arctic soils for the total Arctic CH4 budget is unresolved. This is partly due to lack of data on the spatial variability of net CH4 consumption and understanding of the main process drivers. We measured net CH4 consumption in Arctic and subarctic landscapes located in in Disko Bay Area and Kangerlussuaq in Western Greenland and in the St. Elias Range in the Yukon, Canada, respectively. Our aim was to characterize the in situ spatial variability of net CH4 uptake in hitherto unexplored Arctic dry upland soils to explore possible limits and environmental drivers across the Arctic geodiversity. Furthermore, we sampled soil for incubation experiments to investigate how net CH4 oxidation responded to changes in soil moisture in contrasting geomorphic settings and parent geological parent materials. We used a laser-based fast deployable chamber system for flux measurements. All studied sites were net sinks of atmospheric CH4 with an average flux −7.5 ± 5.6 μmol CH4 m-2h−1, that are in the upper range of reported net CH4 uptake fluxes in similar soils of the Arctic. The large observed spatial variability within all studied sites (coefficient of variation 50 – 120 %) highlights the need for careful research design allowing for many spatial replicates to achieve representative values. Sites with an active geomorphic environment (abrasion plateau, riverbeds, mountain tops) generally had lower than average net CH4 uptake. Our incubation studies revealed that subsurface CH4 oxidation is the main driver of net surface-atmosphere exchange and that net CH4 oxidation in these layers responded more to changes to soil moisture than in near surface layers. Our study shows surprisingly similar flux magnitudes of net CH4 uptake across widely different landscape forms and geologic parent material, but responding similarly to soil hydrology and geomorphic disturbance, indicating global controls on the net CH4 oxidation in these dry upland environments.

Multi-scale habitat influences sprainting and group size of a freshwater-obligate smooth-coated otter (Lutrogale perspicillata) in Tungabhadra Otter Conservation Reserve, India

BackgroundThe impact of changing land-use patterns and associated anthropogenic threats on scale-dependent habitat use of semi-aquatic mustelids in scent-marking and social behaviour can provide important insights into the habitat ecology of smooth-coated otters (Lutrogale perspicillata).MethodsWe sampled 180 stream segments (100–400 m) as spatial replicates of 60 1-km2 sites to record indirect evidence (i.e. spraints and mass latrine sites) and group sizes of smooth-coated otters along the Tungabhadra Otter Conservation Reserve (TOCR) during the dry season. To quantify habitat, we recorded stream characteristics, riparian vegetation, and anthropogenic disturbances at the local scale, and hydro-environmental characteristics and land uses at the landscape scale. Using Markovian-chain detection and occupancy models, we assessed the multi-scale habitat use of otters in their selection of suitable areas for scent-marking based on repeated presence-absence data on spraint/latrine locations along the TOCR. We further used linear regression techniques to explore relationships between the number of individuals in smooth-coated otter group and hydro-environmental characteristics, spraint/latrine encounter rate, anthropogenic pressure, land cover, topography, and vegetation.ResultsAt the local scale, the probability of spraint deposition and group size decreased with anthropogenic disturbance while the probability of spraint detections decreased with grass cover. At the landscape scale, the probability of otter site use for spraint deposition and group sizes increased in southeast flowing streams. Spraint deposition increased with the proportion of sugarcane fields, whereas in contrast, group size decreased with proportion of sugarcane fields.ConclusionsOur findings highlight the first empirical evidence on multi-scale habitat use of a southern Indian population of smooth-coated otters in an inland freshwater ecosystem surrounded by the scrub jungle–agriculture matrix. We suggest that habitat models built from analytical approaches that account for correlated detections can avoid biased predictions when estimating occupancy and detection probability of semi-aquatic or riparian mammal communities with linear distributions. Our findings indicate that human activity can impose constraints on the choice of sites used for spraint deposition and preliminary patterns in otter groups. The study provides some crucial evidence on the need to maintain areas with minimal human interference for sustainability of freshwater reserves.

Evaluating trade-offs in spatial versus temporal replication when estimating avian community composition and predicting species distributions

Evaluating trade-offs in spatial versus temporal replication when estimating avian community composition and predicting species distributions

Low foraging rates drive large insectivorous bats away from urban areas

AbstractUrbanization has significant impacts on wildlife and ecosystems and acts as an environmental filter excluding certain species from local ecological communities. Specifically, it may be challenging for some animals to find enough food in urban environments to achieve a positive energy balance. Because urban environments favor small‐sized bats with low energy requirements, we hypothesized that common noctules (Nyctalus noctula) acquire food at a slower rate and rely less on conspecifics to find prey in urban than in rural environments due to a low food abundance and predictable distribution of insects in urban environments. To address this, we estimated prey sizes and measured prey capture rates, foraging efforts, and the presence of conspecifics during hunting of 22 common noctule bats equipped with sensor loggers in an urban and rural environment. Even though common noctule bats hunted similar‐sized prey in both environments, urban bats captured prey at a lower rate (mean: 2.4 vs. 6.3 prey attacks/min), and a lower total amount of prey (mean: 179 vs. 377 prey attacks/foraging bout) than conspecifics from rural environments. Consequently, the energy expended to capture prey was higher for common noctules in urban than in rural environments. In line with our prediction, urban bats relied less on group hunting, likely because group hunting was unnecessary in an environment where the spatial distribution of prey insects is predictable, for example, in parks or around floodlights. While acknowledging the limitations of a small sample size and low number of spatial replicates, our study suggests that scarce food resources may make urban habitats unfavorable for large bat species with higher energy requirements compared to smaller bat species. In conclusion, a lower food intake may displace larger species from urban areas making habitats with high insect biomass production key for protecting large bat species in urban environments.

A numerical model of the human cornea accounting for the fiber-distributed collagen microstructure

We present a fiber-distributed model of the reinforcing collagen of the human cornea. The model describes the basic connections between the components of the tissue by defining an elementary block (cell) and upscaling it to the physical size of the cornea. The cell is defined by two sets of collagen fibrils running in approximately orthogonal directions, characterized by a random distribution of the spatial orientation and connected by chemical bonds of two kinds. The bonds of the first kind describe the lamellar crosslinks, forming the ribbon-like lamellae; while the bonds of the second kind describe the stacking crosslinks, piling up the lamellae to form the structure of the stroma. The spatial replication of the cell produces a truss structure with a considerable number of degrees of freedom. The statistical characterization of the collagen fibrils leads to a mechanical model that reacts to the action of the deterministic intraocular pressure with a stochastic distribution of the displacements, here characterized by their mean value and variance. The strategy to address the solution of the heavy resulting numerical problem is to use the so-called stochastic finite element improved perturbation method combined with a fully explicit solver. The results demonstrate that the variability of the mechanical properties affects in a non-negligible manner the expected response of the structure to the physiological action.

Spatial replication can best advance our understanding of population responses to climate

Understanding the responses of plant populations dynamics to climatic variability is frustrated by the need for long‐term datasets. Here, we advocate for new studies that estimate the effects of climate by sampling replicate populations in locations with similar climate. We first use data analysis on spatial locations in the conterminous USA to assess how far apart spatial replicates should be from each other to minimize temporal correlations in climate. We find that on average spatial locations separated by 316 km (SD = 149 km) have moderate (0.5) correlations in annual precipitation. Second, we use simulations to demonstrate that spatial replication can lead to substantial gains in the range of climates sampled during a given set of years so long as the climate correlations between the populations are at low to moderate levels. Third, we use simulations to quantify how many spatial replicates would be necessary to achieve the same statistical power of a single‐population, long‐term data set under different strengths and directions of spatial correlations in climate between spatial replicates. Our results indicate that spatial replication is an untapped opportunity to study the effects of climate on demography and to rapidly fill important knowledge gaps in the field of population ecology.

Contrasting patterns of biodiversity across wetland habitats using single‐time‐point environmental DNA surveys

Abstract Wildlife surveys are central to the conservation and restoration management of wetland habitats; however, the often laborious and costly nature of traditional survey methods can constrain the spatial and temporal extent and replication of survey efforts. Environmental DNA (eDNA) technologies now provide the opportunity to reduce some of these limitations, but applications in temporary and permanent freshwater marshes and meadows (herein referred to as ‘wetland habitats’) remain limited. This study investigates the performance of single‐time‐point eDNA surveys for characterizing fish, amphibian and bird assemblages of wetland habitats in south‐eastern Australia. Comparisons were made between coastal and inland wetlands, between wetlands of varying condition and between eDNA and traditional surveys. Findings show that eDNA surveys can provide comprehensive descriptions of faunal assemblages associated with wetland habitats, with resolution similar to that provided by traditional survey approaches. Analyses also revealed significant differences in patterns of biodiversity between wetland types (coastal vs. inland) but not between wetland habitats varying in condition. Overall, this study confirms that eDNA surveys provide a reliable option for undertaking wetland biodiversity assessments aimed at improving biodiversity data coverage for otherwise data deficient wetlands.

How much is enough? Examining the sampling effort necessary to estimate mean eDNA concentrations in lentic systems

AbstractThe concentration of eDNA in an environment can provide important ecological information of relevance for management and conservation, but little research has explored optimizing sampling strategies to estimate mean eDNA concentrations in natural environments. Inter‐replicate eDNA concentrations often exhibit right‐skewed “clustered” or “clumped” distributions, likely due to the stochastic capture of large “aggregate” particles with high eDNA copy numbers. This has important potential implications for modeling the resulting sampling effort necessary to accurately quantify eDNA concentrations. In a previous study, 17–20 Brook Charr eDNA samples were collected from 28 lakes in Québec, Canada. We explored how variation in eDNA concentrations within a lake was affected by several habitat characteristics. We then conducted a power analysis to determine the sampling effort (“minimum n”) necessary to accurately quantify mean lake eDNA concentrations and, using simulations, explored how a bimodal distribution of eDNA particle copy count could affect inter‐replicate variability. The median sample size such that 90% of sample mean estimates were within 20% of the “true” mean was 12.5; a sample size of 20 was sufficient to quantify mean concentrations in 21/28 lakes. We found no evidence that temperature or lake size impacted sample variability. We also found that variance among replicates was non‐linearly related to mean lake eDNA concentration across years: variability was lowest at low and high concentrations and highest at intermediate concentrations. We hypothesize that this resulted from the stochastic capture of large “aggregate” particles at intermediate concentrations; at low concentrations, aggregates were likely rarely captured and at high concentrations may represent a consistent component of total eDNA. Simulations demonstrated that these patterns can emerge from some bimodal eDNA particle “size” distributions. Overall, we conclude that sampling efforts in many previous studies (notably including the authors' own) were potentially low, emphasizing the need to increase spatial replication in lentic surveys.

Optimized array nanostructure for plasmonically induced motion force generation.

The growing demand to manipulate objects with long-range techniques has increasingly called for the development of techniques capable of intensifying and spatially concentrating electromagnetic fields with the aim of improving the electromagnetic forces acting on objects. In this context, one of the most interesting techniques is based on the use of plasmonic phenomena that have the ability to amplify and structure the electric field in very small areas. In this paper, we report the simulation analysis of a plasmonic nanostructure useful for optimizing the profile of the induced plasmonic field distribution and thus the motion dynamics of a nanoparticle, overcoming some limitations observed in the literature for similar structures. The elementary cell of the proposed nanostructure consists of two gold scalene trapezoids forming a planar V-groove. The spatial replication of this elementary cell to form linear or circular array sequences is used to improve the final nanoparticle velocity. The effect of the geometry variation on the plasmonic behaviour and consequently on the force generated, was analyzed in detail. The results suggest that this optimized plasmonic structure has the potential to efficiently propel macroscopic objects, with implications for various fields such as aerospace and biomedical research.

Strategic monitoring to minimize misclassification errors from conservation status assessments

Classifying species into risk categories is a ubiquitous process in conservation decision-making affecting regulatory procedures, conservation actions, and guiding resource allocation at global, national, and regional scales. However, monitoring programs often do not provide data required for accurate species classification decisions. Misclassification can lead to otherwise preventable species extinctions, undue regulatory burden, poor allocation of limited conservation resources, and can undermine species conservation legislation. We developed a framework that evaluates monitoring designs based on the ability to correctly inform a species classification decision, where minimizing the risk of misclassification is the central objective. We further evaluated monitoring designs by calculating the expected value of information and explored the relationship between statistical power to detect trends and misclassification. Our measure of misclassification risk, which can be tailored to the decision context, clarified the costs of over- and under-protection. High power to detect trends often corresponded to accurate species classification decisions. However, in several scenarios power to detect trends was low but the ability to correctly inform the classification decision was high. The value of information generally increased with monitoring intensity and quantified the tradeoffs between spatial and temporal replication. Our framework allows managers to assess monitoring program performance with direct implications for conservation decision-making. Our framework affords practitioners an opportunity to evaluate the effectiveness of monitoring programs a priori focusing on improving conservation decisions. We demonstrate that prioritizing monitoring to minimize misclassification errors can improve monitoring efficiency and conservation decision-making with considerable practical applications and benefits for species conservation.

Australian brown seaweeds as a source of essential dietary minerals

Seaweeds are rich in essential dietary minerals, often lacking in terrestrial plant foods, with interest in Australian seaweeds rapidly increasing. We screened six Australian brown seaweeds with commercial potential for dietary mineral composition: Cystophora torulosa, Caulocystis uvifera, Durvillaea potatorum, Ecklonia radiata, Hormosira banksii and Phyllospora comosa. Spatial replicates of each species were collected from three non-urbanised sites remote from pollution sources and processed for human consumption. Dried samples were analysed by inductively coupled plasma mass spectrometry (ICP-MS) for 12 essential dietary minerals. Overall dietary mineral composition differed significantly amongst all species, except between sargassaceous species C. torulosa and C. uvifera; but concentrations of individual elements varied in complex ways. All species investigated had high concentrations of dietary minerals essential for optimal human health if consumed in realistic quantities (e.g. 10 g day−1 DW) as part of balanced diets, including the most common dietary minerals deficient in humans (iodine, iron, zinc, magnesium, calcium and selenium): iodine (888 ± 100 mg kg−1 DW) and zinc were highest in P. comosa; iron and calcium were highest in C. torulosa, but calcium was also high in E. radiata, H. banksii and D. potatorum; magnesium was highest in H. banksii, D. potatorum and P. comosa; selenium concentrations exceeded those previously reported for seaweeds for all species, except D. potatorum. The best nutritional outcomes may be achieved by regularly consumption of a diversity of seaweed species. However, further investigation into ways to reduce iodine content in some species may be required to maximise health benefits from regular consumption of these Australian seaweeds.

Reanalysis ignores pertinent data, includes inappropriate observations, and disregards realities of applied ecology: Response to Huso and Dalthorp (2023)

Abstract We recently demonstrated efficacy of automated curtailment of wind turbines in reducing fatalities of eagles at a study site in Wyoming, USA. Huso and Dalthorp criticize our work, asserting that there are several ‘major errors’ that render our previous work as providing ‘no meaningful support’ for automated curtailment. As we show here, our data do indeed provide support for the efficacy of automated curtailment. The purported major errors they identify include: having only 1 year of post‐treatment data, having only one control and one treatment site, using the control site for inference, choosing an arbitrary demarcation date between the ‘before’ and ‘after’ periods, analysing the number, rather than the rate, of fatalities, and not including data they consider pertinent. These claims are unsupported because all result from misreading our study, ignoring realities of causal inference in field ecology, or are matters of preference. Most importantly, we did not fail to include pertinent data and we provided sufficient criteria in the manuscript to explain inclusion of carcasses in our study. As stated in our previous study, the eagle carcasses we did not include were found either outside of search areas or incidentally, and thus did not meet criteria for inclusion. Further, Huso and Dalthorp present a standard for spatial and temporal replication that is inconsistent with their own recent work and many other studies in this field. Finally, their reanalysis of our data ignores the control site while including inappropriate data and thus is not suitable for inference. We appreciate the unusually thorough critique of our work provided by Huso and Dalthorp. Despite the major errors in their argument, this discussion provides a platform for further evaluation of our original work. Synthesis and applications. We show that incorporating control site data and using our a priori demarcation of before and after periods into Huso and Dalthorp's reanalysis returns meaningful support for automated curtailment. We also direct the reader to an updated analysis that uses components of the approach Huso and Dalthorp suggest, along with additional data and a number of other analytical improvements, to validate and strengthen our original conclusions.

Testing concordance and conflict in spatial replication of landscape genetics inferences.

The degree to which landscape genetics findings can be extrapolated to different areas of a species range is poorly understood. Here, we used a broadly distributed ectothermic lizard (Sceloporus occidentalis, Western Fence lizard) as a model species to evaluate the full role of topography, climate, vegetation, and roads on dispersal and genetic differentiation. We conducted landscape genetics analyses with a total of 119 individuals in five areas within the Sierra Nevada mountain range. Genetic distances calculated from thousands of ddRAD markers were used to optimize landscape resistance surfaces and infer the effects of landscape and topographic features on genetic connectivity. Across study areas, we found a great deal of consistency in the primary environmental gradients impacting genetic connectivity, along with some site-specific differences, and a range in the proportion of genetic variance explained by environmental factors across study sites. High-elevation colder areas were consistently found to be barriers to gene flow, as were areas of high ruggedness and slope. High temperature seasonality and high precipitation during the winter wet season also presented a substantial barrier to gene flow in a majority of study areas. The effect of other landscape variables on genetic differentiation was more idiosyncratic and depended on specific attributes at each site. Across study areas, canyon valleys were always implicated as facilitators to dispersal and key features linking populations and maintaining genetic connectivity, though the relative importance varied in different areas. We emphasize that spatial data layers are complex and multidimensional, and careful consideration of spatial data correlation structure and robust analytic frameworks will be critical to our continued understanding of spatial genetics processes.

How has bird biodiversity changed over time? A review across spatio-temporal scales

Empirical quantification of biodiversity changes remains a challenge even in well surveyed groups such as birds. This may be because the change depends on spatio-temporal scales, specifically on spatial grain (i.e. average unit of area of the sampling or the analysis), geographic extent (i.e. size of the area of interest), temporal grain (i.e. average unit of duration of the sampling or the analysis), and temporal extent (i.e. length of the time series). Further, different metrics of biodiversity may exhibit different trends. Here we review the literature assessing the temporal trends of avian biodiversity from ca. 1900 AD to present, focusing on studies summarising trends across many locations within a larger region (i.e. spatially replicated). From each study we extracted direction of average trend (increase, decrease, stable), spatial and temporal grains and extents at which the trends have been assessed, metrics of biodiversity, and location. We then discuss the trends as a function of the spatio-temporal grains and extents they are defined at. We found 59 trends of 12 metrics, where each trend is an average of trends from multiple sites (spatial replicates). There was a tendency of biodiversity metrics to increase at local and regional spatial scales, and to decrease globally. We thus confirmed that biodiversity dynamics can have opposite trends at different spatial scales. Concerning temporal grain, it was poorly documented across the studies, with inconsistent and/or confusing definitions. We suggest a common framework to better understand the link between temporal scales and biodiversity dynamics. We have also identified underrepresented regions (those outside North America and Europe), periods (those before the 70′s), and biodiversity metrics that need further attention. We highlight the importance of considering both spatial and temporal scaling jointly in any assessment of biodiversity change, and provide guidelines for specifying spatio-temporal features (i.e. grain, lag and extent) effectively both in birds, and in other taxa.

Toward a statistical validation of brain signatures as robust measures of behavioral substrates.

The "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of behavioral outcomes. Previously we presented a method for computing signatures of episodic memory. However, to be a robust brain measure, the signature approach requires a rigorous validation of model performance across a variety of cohorts. Here we report validation results and provide an example of extending it to a second behavioral domain. In each of two discovery data cohorts, we derived regional brain gray matter thickness associations for two domains: neuropsychological and everyday cognition memory. We computed regional association to outcome in 40 randomly selected discovery subsets of size 400 in each cohort. We generated spatial overlap frequency maps and defined high-frequency regions as "consensus" signature masks. Using separate validation datasets, we evaluated replicability of cohort-based consensus model fits and explanatory power by comparing signature model fits with each other and with competing theory-based models. Spatial replications produced convergent consensus signature regions. Consensus signature model fits were highly correlated in 50 random subsets of each validation cohort, indicating high replicability. In comparisons over each full cohort, signature models outperformed other models. In this validation study, we produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Signatures in two memory domains suggested strongly shared brain substrates. Robust brain signatures may therefore be achievable, yielding reliable and useful measures for modeling substrates of behavioral domains.