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1,721 results for “network data”
Data from: Landscape simplification shapes pathogen prevalence in plant-pollinator networks
Species interaction networks, which play an important role in determining pathogen transmission and spread in ecological communities, can shift in response to agricultural landscape simplification. However, we know surprisingly little about how landscape simplification-driven changes in network structure impact epidemiological patterns. Here, we combine mathematical modeling and data from eleven bipartite plant-pollinator networks observed along a landscape simplification gradient to elucidate how changes in network structure shape disease dynamics. Our empirical data show that landscape simplification reduces pathogen prevalence in bee communities via increased diet breadth of the dominant species. Furthermore, our empirical data and theoretical model indicate that increased connectance reduces the likelihood of a disease outbreak and decreases variance in prevalence among bee species in the community, resulting in a dilution effect. Because infectious diseases are implicated in pollinator declines worldwide, a better understanding of how land use change impacts species interactions is therefore critical for conserving pollinator health.
Data from: Plant life history stage and nurse age change the development of ecological networks in an arid ecosystem
Understanding how ecological networks are organised over the course of an organism's lifetime is crucial for predicting the dynamics of interacting populations and communities across temporal scales. However, most studies so far considered only one life history stage at a time, such as adult, when studying networks of interacting species. Therefore, knowledge about how multiple life history stages affect the development and stability of plant–plant association networks is lacking. We measured the understory adult plant community and the soil seed bank across a plant age gradient of the nurse shrub Retama sphaerocarpa in an arid ecosystem in Spain. Using a multilayer network approach, we built adult understory–nurse and seed bank–nurse networks and analysed how network nestedness, species' role, and species specificity varied between them and with nurse plant age. We found that seed bank and adult understory networks changed depending on nurse plant age in two different ways. With increasing nurse plant age, adult understory networks became significantly more nested than seed bank networks. The nested architecture of seed bank networks was therefore a poor predictor of adult understory network nestedness. The contribution and specificity of species to network nestedness increased with increasing nurse plant age more in the adult understory than in seed bank networks, despite high species turnover. Our data show that life history and ontogeny affect the development of plant–plant association networks. Niche construction and environmental filtering along nurse ontogeny seem pivotal mechanisms structuring adult understory networks while the assembly of seed bank networks seems rather stochastic. We highlight the importance of mature plant communities for maintaining rare species populations and supporting the stability of ecological communities through time.
Data from: High-resolution contact networks of free-ranging domestic dogs Canis familiaris and implications for transmission of infection
Contact patterns strongly influence the dynamics of disease transmission in both human and non-human animal populations. Domestic dogs Canis familiaris are a social species and are a reservoir for several zoonotic infections, yet few studies have empirically determined contact patterns within dog populations. Using high-resolution proximity logging technology, we characterised the contact networks of free-ranging domestic dogs from two settlements (n = 108 dogs, covering >80% of the population in each settlement) in rural Chad. We used these data to simulate the transmission of an infection comparable to rabies and investigated the effects of including observed contact heterogeneities on epidemic outcomes. We found that dog contact networks displayed considerable heterogeneity, particularly in the duration of contacts and that the network had communities that were highly correlated with household membership. Simulations using observed contact networks had smaller epidemic sizes than those that assumed random mixing, demonstrating the unsuitability of homogenous mixing models in predicting epidemic outcomes. When contact heterogeneities were included in simulations, the network position of the individual initially infected had an important effect on epidemic outcomes. The risk of an epidemic occurring was best predicted by the initially infected individual's ranked degree, while epidemic size was best predicted by the individual's ranked eigenvector centrality. For dogs in one settlement, we found that ranked eigenvector centrality was correlated with range size. Our results demonstrate that observed heterogeneities in contacts are important for the prediction of epidemiological outcomes in free-ranging domestic dogs. We show that individuals presenting a higher risk for disease transmission can be identified by their network position and provide evidence that observable traits hold potential for informing targeted disease management strategies.
Data from: Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants
Correlations among plant traits often reflect important trade‐offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to "spectra" or "leading dimensions," whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the "leaf economics spectrum," "biomass allocation dimension," "seed dimension," and carbon and nitrogen concentrations. This literature‐based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature‐based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below‐ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem‐specific length were "hub" traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature‐based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a "size" module, a "seed" module, two modules representing C and N concentrations in plant organs, and a "partitioning" module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole‐plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.
Data from: Interaction networks of macrofungi and mycophagous beetles reflect diurnal variation and the size and spatial arrangement of resources
Ecological networks are useful for characterizing interspecific associations and predicting the resilience of ecological communities. We evaluated how such networks vary with the size, spatial distribution, and timing of availability of resources, with a focus on beetle-macrofungal associations. We used 2 y of field experiments to construct ecological networks based on manipulated sporocarp baits (resources; Pleurotus ostreatus) and natural communities of beetles (consumers) in a temperate forest. Centrality and interaction strength increased with resource size, but were associated weakly with resource density and isolation, and not at all with position within patches. Whole-network connectance was greater in mornings (when beetle richness and abundance were high) than evenings. Interannual differences in networks were consistent with differences in beetle communities between years. The capacity of networks to vary temporally, spatially, and as a function of resource traits is examined in light of understanding beetle-macrofungal associations, which are important components of fungal ecology.
Data from: Invariant antagonistic network structure despite high spatial and temporal turnover of interactions
Recent work has suggested that emergent ecological network structure exhibits very little spatial or temporal variance despite changes in community composition. However, the changes in network interactions associated with turnover in community composition have seldom been assessed. Here we examine whether changes in ecological networks are best detected by standard emergent network metrics or by assessing internal network changes (i.e. interaction and composition turnover). To eliminate possible spatial or phylogenetic effects, that in large-scale studies may obscure mechanisms structuring networks and interactions, we sampled multiple antagonistic (plant-herbivore) networks for a single diverse plant family (the Restionaceae) in the hyperdiverse Cape Floristic Region. These are the first plant-herbivore networks constructed for this global biodiversity hotspot. We found invariant emergent network structure despite considerable changes in insect and plant composition across communities over time and space. In contrast, there was high interaction turnover between networks. Seasonally, this was driven by turnover in insect species and insect host switching. Spatially, this was driven by simultaneous turnover in plant and insect species, suggesting that many insects are host specific or that both groups exhibit parallel responses to environmental gradients. Spatial interaction turnover was also driven by turnover in plants, showing that many insects can utilise multiple (possibly closely related) hosts and this may create divergent selection gradients that promote insect speciation. Thus we show highly variable interaction fidelity, despite invariant emergent network structure. We suggest that evaluating internal network changes may be more effective at elucidating the processes structuring networks, and many fine-scale changes may be obscured when only calculating emergent network metrics.
Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize
Premature senescence in annual crops reduces yield while delayed senescence, termed stay-green, is known to impose both positive and negative impact on yield and nutrition quality. Despite the importance, scant information is available on the genetic architecture of senescence in maize (Zea mays L.) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and co-expression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by GWAS, and 14 of these are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a co-expression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding cysteine protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggest a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.
Data from: Inferring species networks from gene trees in high-polyploid North American and Hawaiian violets (Viola, Violaceae)
The phylogenies of allopolyploids take the shape of networks and cannot be adequately represented as bifurcating trees. Especially for high-polyploids (i.e., organisms with more than six sets of nuclear chromosomes), the signatures of gene homoeolog loss, deep coalescence and polyploidy may become confounded, with the result that gene trees may be congruent with more than one species network. Herein, we obtained the most parsimonious species network by objective comparison of competing scenarios involving polyploidization and homoeolog loss in a high-polyploid lineage of violets (Viola, Violaceae) mostly or entirely restricted to North America, Central America, or Hawaii. We amplified homoeologs of the low-copy nuclear gene GPI by single-molecule PCR and the chloroplast trnL-F region by conventional PCR for 51 species and subspecies. Topological incongruence among GPI homoeolog subclades, owing to deep coalescence and two instances of putative loss (or lack of detection) of homoeologs, were reconciled by applying the maximum tree topology for each subclade. The most parsimonious species network and the fossil-based calibration of the homoeolog tree favored monophyly of the high-polyploids, which has resulted from allodecaploidization 9–14 Ma ago, involving sympatric ancestors from the extant Viola sections Chamaemelanium (diploid), Plagiostigma (paleotetraploid), and Viola (paleotetraploid). While two of the high-polyploid lineages (Boreali-Americanae, Pedatae) remained decaploid, recurrent polyploidization with tetraploids of section Plagiostigma within the last 5 Ma has resulted in two 14-ploid lineages (Mexicanae, Nosphinium) and one 18-ploid lineage (Langsdorffianae). This implies a more complex phylogenetic and biogeographic origin of the Hawaiian violets (Nosphinium) than that previously inferred from rDNA data and illustrates the necessity of considering polyploidy in phylogenetic and biogeographic reconstruction.
Data from: Ecological divergence among colour morphs mediated by changes in spatial network structure associated with disturbance
1. Differences in individual behaviour affect social interactions and contribute to the spatial structuring of animal populations. However, disturbance should also affect spatial networks by altering habitat heterogeneity and resource availability. Variation in resource availability should perturb the frequency and nature of social and ecological interactions within a population by affecting the spatial distribution of individuals. 2. In disturbed habitats where resources are limiting, spatial relationships should reflect behavioural differences among individuals, with higher-quality resources controlled by dominant individuals. In contrast, all individuals may exploit preferred resources in resource-rich habitats. Environmental variation and population reorganisation may also result in variation in morphological, behavioural, and ecological traits, which ultimately affect fitness. 3. We addressed these considerations for male tree lizards (Urosaurus ornatus) at three sites that differ in levels of disturbance. The habitats at these localities differed in the availability of live trees, the preferred microhabitat of U. ornatus. In addition, male U. ornatus exhibit a polymorphism in dewlap colour linked with differences in aggression, which should influence their position in a network and access to resources. We applied a network framework to characterise the spatial organisation of male morphs at each site and quantified male aggressive behaviour in the laboratory. We also compared body size, body condition, number of bite marks, parasite load, and the microhabitat use and diet, of males among the sites. 4. We detected no significant differences in spatial network structure between unburned and infrequently burned sites. However, at a frequently-burned site, the network shifted towards geographically closer, heteromorphic male neighbour associations. Males at this site were also larger, more aggressive, and had more bite marks but fewer parasites than males at the other sites. Moreover, we detected divergence in microhabitat use and diet among the morphs at the frequently-burned site that reflected the shift in spatial network structure and differences in morph behaviour. That is, only more-aggressive morphs usurped trees and consumed prey from higher trophic levels. 5. We conclude that environmental variation may influence animal spatial network structure. Jointly, behavioural and environmental variation may promote despotic social dynamics and ecological divergence in resource-limited habitats.
Data from: Beta diversity and specialization in plant-pollinator networks along an elevational gradient
Aim: To assess whether the reduced nutritional resources available for pollinators due to plant community simplification along an elevational plant-diversity gradient changes pollinator niche breadth and richness. Additionally, we evaluated how body size and proboscis length of pollinators shifted along the gradient, and whether these changes were related to pollinator niche breadth. Location: An elevational gradient (2,350-3,520 m a.s.l.) on the oceanic high-mountain strato-volcano of El Teide (Tenerife, Canary Islands). Taxon: Flowering plant and pollinator species. Methods: We compared quantitative plant–pollinator networks along the plant-diversity gradient. We calculated a set of niche-based topological metrics that capture the degree of specialization, niche breadth and niche overlap. Furthermore, we obtained β-diversity measures and the proportion of replacement and richness components. Results: There was an overall decline in species richness of pollinators with increasing elevation. This decline was mainly driven by the loss of species along the elevational gradient, which conformed a nested subset pattern. The whole network showed less specialization, greater connectance and lower modularity towards the summit. At high elevations, pollinators were more generalized and less selective in their flower choice, showing a greater trophic niche breadth compared to pollinators at lower elevations. Mean body size of pollinators increased with elevation, and species body size and proboscis length were positively associated with the number of plant species visited. Main conclusions. Overall, results indicated that the elevational gradient filters pollinator species, probably according to their thermal tolerance and ability to exploit a wide range of trophic resources. The finding that pollinators become more generalized and opportunistic at higher elevations is a novel result, which may have implications for new research into how ecological networks vary over environmental gradients. From an applied perspective, our results highlight the importance of considering the spatial variation of species assemblages when aiming to construct functionally reliable interaction networks along environmental gradients.
Data from: Knockouts of high-ranking males have limited impact on baboon social networks
Social network structures can crucially impact complex social processes such as collective behaviour or the transmission of information and diseases. However, currently it is poorly understood how social networks change over time. Previous studies on primates suggest that 'knockouts' (due to death or dispersal) of high-ranking individuals might be important drivers for structural changes in animal social networks. Here we test this hypothesis using long-term data on a natural population of baboons, examining the effects of 29 natural knockouts of alpha or beta males on adult female social networks. We investigated whether and how knockouts affected (1) changes in grooming and association rates among adult females, and (2) changes in mean degree and global clustering coefficient in these networks. The only significant effect that we found was a decrease in mean degree in grooming networks in the first month after knockouts, but this decrease was rather small, and grooming networks rebounded to baseline levels by the second month after knockouts. Taken together our results indicate that the removal of high-ranking males has only limited or no lasting effects on social networks of adult female baboons. This finding calls into question the hypothesis that the removal of high-ranking individuals has a destabilizing effect on social network structures in social animals.
Data from: Genetics of gene expression responses to temperature stress in a sea urchin gene network
Stress responses play an important role in shaping species distributions and robustness to climate change. We investigated how stress responses alter the contribution of additive genetic variation to gene expression during development of the purple sea urchin, Strongylocentrotus purpuratus, under increased temperatures that model realistic climate change scenarios. We first measured gene expression responses in the embryos by RNA-seq to characterize molecular signatures of mild, chronic temperature stress. We found that an increase from 12 °C to 18 °C caused widespread alterations in gene expression including in genes involved in protein folding, RNA processing, and development. To understand the quantitative genetic architecture of this response, we then focused on a well-characterized gene network involved in endomesoderm and ectoderm specification. Using a breeding design with wild-caught individuals, we measured genetic and gene-environment interaction effects on 72 genes within this network. We found genetic or maternal effects in 33 of these genes, and that the genetic effects were correlated in the network. 14 network genes also responded to higher temperatures, but we found no significant genotype-environment interactions in any of the genes. This absence may be due to an effective buffering of the temperature perturbations within the network. In support of this hypothesis, perturbations to regulatory genes did not affect the expression of the genes that they regulate. Together, these results provide novel insights into the relationship between environmental change and developmental evolution and suggest that climate change may not expose large amounts of cryptic genetic variation to selection in this species.
Data from: Approaches to integrating genetic data into ecological networks
As molecular tools for assessing trophic interactions become common, research is increasingly focused on the construction of interaction networks. Here we demonstrate three key methods for incorporating DNA data into network ecology and discuss analytical considerations using a model consisting of plants, insects, bats and their parasites from the Costa Rican dry forest. The simplest method involves the use of Sanger sequencing to acquire long sequences to validate or refine field identifications, for example of bats and their parasites, where one specimen yields one sequence and one identification. This method can be fully quantified and resolved and these data resemble traditional ecological networks. For more complex taxonomic identifications, we target multiple DNA loci e.g. from a seed or fruit pulp sample in faeces. These networks are also well resolved but gene targets vary in resolution and quantification is difficult. Finally for mixed templates such as faecal contents of insectivorous bats we use DNA metabarcoding targeting two sequence lengths (157bp, 407bp) of one gene region and a MOTU, BLAST and BIN association approach to resolve nodes. This network type is complex to generate and analyse and we discuss the implications of this type of resolution on network analysis. Using these data we construct the first molecular-based network of networks containing 3304 interactions between 762 nodes of 8 trophic functions and involving parasitic, mutualistic, and predatory interactions. We provide a comparison of the relative strengths and weaknesses of these data types in network ecology.
Data from: Network-scale effects of invasive species on spatially-structured amphibian populations
<p>Understanding the factors affecting the dynamics of spatially-structured populations (SSP) is a central topic of conservation and landscape ecology. Invasive alien species are increasingly important drivers of the dynamics of native species. However, the impacts of invasives are often assessed at the patch scale, while their effects on SSP dynamics are rarely considered. We used long-term abundance data to test whether the impact of invasive crayfish on subpopulations can also affect the whole SSP dynamics, through their influence on source populations. From 2010 to 2018, we surveyed a network of 58 ponds and recorded the abundance of Italian agile frog clutches, the occurrence of an invasive crayfish, and environmental features. Using Bayesian hierarchical models, we assessed relationships between frog abundance in ponds and a) environmental features; b) connectivity within the SSP; c) occurrence of invasive species at both the patch- and the SSP-levels. If spatial relationships between ponds were overlooked, we did not detect effects of crayfish presence on frog abundance or trends. When we jointly considered habitat, subpopulation, and SSP features, processes acting at all these levels affected frog abundance. At the subpopulation scale, frog abundance in a year was related to habitat features, but was unrelated to crayfish occurrence at that site during the previous year. However, when we considered the SSP level, we found a strong negative relationship between frog abundance in a given site and crayfish frequency in surrounding wetlands during the previous year. Hence, SSP-level analyses can identify effects that would remain unnoticed when focussing on single patches. Invasive species can affect population dynamics even in not invaded patches, through the degradation of subpopulation networks. Patch-scale assessments of the impact of invasive species can thus be insufficient: predicting the long-term interplay between invasive and native populations requires landscape-level approaches accounting for the complexity of spatial interactions.</p>
Data from: The robustness and restoration of a network of ecological networks
Understanding species' interactions and the robustness of interaction networks to species loss is essential to understand the effects of species' declines and extinctions. In most studies, different types of networks (such as food webs, parasitoid webs, seed dispersal networks, and pollination networks) have been studied separately. We sampled such multiple networks simultaneously in an agroecosystem. We show that the networks varied in their robustness; networks including pollinators appeared to be particularly fragile. We show that, overall, networks did not strongly covary in their robustness, which suggests that ecological restoration (for example, through agri-environment schemes) benefitting one functional group will not inevitably benefit others. Some individual plant species were disproportionately well linked to many other species. This type of information can be used in restoration management, because it identifies the plant taxa that can potentially lead to disproportionate gains in biodiversity.
Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks
The network architecture of streams and rivers constrains evolutionary, demographic, and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (1) examining hierarchical partitioning of genetic variation in stream networks and (2) testing for genetic isolation by distance along stream corridors versus overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. AMOVA identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in-stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.
Data from: Plant-mycorrhizal fungus co-occurrence network lacks substantial structure
The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co-occurrence network using novel methodology based on information theory and a unique set of spatially explicit species-level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non-spatial null models. However, for the null model considering spatial effects, there are few significant co-occurrences compared with the other two null models. Thus, plant–AMF spatial co-occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co-occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities.
Data from: Rate of inter-sex interactions affects injury likelihood in Tasmanian devil contact networks
Identifying the types of contacts that result in disease transmission is important for accurately modelling and predicting transmission dynamics and disease spread in wild populations. We investigated contacts within a population of adult Tasmanian devils (Sarcophilus harrisii) over a six-month period and tested whether individual-level contact patterns were correlated with accumulation of bite wounds. Bite wounds are important in the spread of devil facial tumour disease (DFTD), a clonal cancer cell line transmitted through direct inoculation of tumour cells when susceptible and infected individuals bite each other. We used multi-model inference and network autocorrelation models to investigate the effects of individual-level contact patterns, identities of interacting partners, and position within the social network on the propensity to be involved in bite-inducing contacts. We found that males were more likely to receive potentially disease-transmitting bite wounds than females, particularly during the mating season when males spend extended periods mate-guarding females. The number of bite wounds individuals received during the mating season was unrelated to any of the network metrics examined. Our approach illustrates the necessity for understanding which contact types spread disease in different systems to assist the management of this and other infectious wildlife diseases.
Data from: The contribution of land tenure diversity to the spatial resilience of protected area networks
1. The relationship between diversity and resilience is relatively well-established for ecological systems, but remains much less explored for socioeconomic systems. Institutional diversity may have particular relevance for protected areas, whose managerial responses to environmental change depend on their legal basis, ability to make and enforce rules, and socio-political acceptance and endorsement. 2. Protected area expansion strategies are increasingly turning to private land conservation to increase the configuration and connectivity of national protected area networks. Yet we know little about the relative role of privately-owned protected areas in protecting threatened and poorly protected (under-represented) habitats, and in the overall connectivity of the national protected area network. 3. We present an empirical assessment of protected area tenure diversity across South Africa. 4. Privately-owned protected areas comprise 25.58% (2878422.26 ha) of the area of the total protected area estate. 5. Private nature reserves emerged as the dominant protected area type in under-represented and threatened habitats, protecting, on average, 32%, 38%, and 41%, respectively, of poorly protected, threatened and endangered vegetation classes. 6. Private nature reserves had the largest overall effect, compared to other protected area types, on connectivity within the national network. A spatially randomised comparison showed that privately-owned protected areas are over-dispersed and more strategically positioned to connect other types of protected areas than would be expected by chance from their extent and abundance. 7. Our results suggest that privately-owned protected areas enhance the resilience of the national protected area network, making it more extensive and better-connected, with greater levels of habitat redundancy. More generally, our analysis highlights the potentially valuable role of institutional diversity in building resilient habitat networks for biodiversity conservation.
Data from: Dynamic species co-occurrence networks require dynamic biodiversity surrogates
In conservation it is inevitable that surrogates be selected to represent the occurrence of hard–to–find species and find priority locations for management. However, species co–occurrence can vary over time. Here we demonstrate how temporal dynamics in species co–occurrence influence the ability of managers to choose the best surrogate species. We develop an efficient optimisation formulation that selects the optimal set of complementary surrogate species from any co–occurrence network. We apply it to two Australian datasets on successional bird responses to disturbances of revegetation and fire. We discover that a surprisingly small number of species are required to represent the majority of species co–occurrences at any one time. Because co–occurrence patterns are temporally dynamic, the optimal set of surrogates, and the number of surrogates required to achieve a desired surrogacy power, depend on sampling effort and the successional state of a system. Overlap in optimal sets of surrogates for representing 70% of co–occurring species ranges from zero to 57% depending on when the surrogacy decision is made. Surrogate sets representing early successional communities over–estimate the power of surrogacy decisions at later times. Our results show that in dynamic systems, optimal surrogates might be selected in different ways: (1) use short–term monitoring to choose a larger number of static less–informative surrogates; (2) use long–term monitoring to choose a smaller number of static high–power surrogates that may poorly represent early successional co–occurrence; (3) develop adaptive surrogate selection frameworks with high short–term and long–term surrogacy power that update surrogate sets and capture temporal dynamics in species co–occurrence. Our results suggest vigilance is needed when selecting surrogates for other co–occurring species in dynamic landscapes, as selected surrogates from one time may have reduced effectiveness at a different time. Ultimately, decisions that fail to acknowledge dynamic species co–occurrence will lead to uninformative or redundant surrogates.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.