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opencc-zeroDec 2015View details →

Data from: Consistent scaling of population structure across landscapes despite intraspecific variation in movement and connectivity

Understanding the spatial scale of population structure is fundamental to long-standing tenets of population biology, landscape ecology and conservation. Nonetheless, identifying such scales has been challenging because a key factor that influences scaling – movement among patches or local populations – is a multicausal process with substantial phenotypic and temporal variation. We resolve this problem via a novel application of network modularity. When applied to movements, modularity provides a formal description of the functional aggregation of populations and identifies potentially critical scales for ecological and evolutionary dynamics. We first test for modularity using several different types of biologically relevant movements across the entire geographic range of an endangered bird, the snail kite (Rostrhamus sociabilis plumbeus). We then ask whether variation in movement based on (i) age, (ii) sex and (iii) time (annual, seasonal and within-season movements) influences spatial population structure (i.e. modularity) in snail kites. We identified significant modularity in annual dispersal of snail kites (all adults, males only, females only, and juveniles only) and in within-breeding season movements of adults, yet no evidence of modularity in seasonal (non-breeding) movements. For those movements with observed modular structure, we found striking similarities in the spatial configuration of population structure, even though movement properties varied considerably among these different types of movements. Our results suggest that the emergence of modularity in population networks can be robust despite movement heterogeneity and differences in patch-based measures of connectivity. Furthermore, our comparison of the population structure and connectivity across multiple movement phases helps to identify wetland patches most critical to population connectivity at multiple spatiotemporal scales. We argue that understanding modularity in populations may provide a robust complement to existing measures of population structure and connectivity and will help to clarify the limiting roles of movement for populations. Such information is increasingly needed for interpreting population persistence and guiding effective conservation strategies with ongoing environmental change.

Data from: From animal tracks to fine-scale movement modes: a straightforward approach for identifying multiple, spatial movement patterns

1. Thanks to developments in animal tracking technology, detailed data on the movement tracks of individual animals are now attainable for many species. However, straightforward methods to decompose individual tracks into high-resolution, spatial modes are lacking but are essential to understand what an animal is doing. 2. We developed an analytical approach that combines separately-validated methods into a straightforward tool for converting animal GPS tracks to short-range movement modes. Our three-step analytical process comprises: (1) decomposing data into separate movement segments using behavioural change point analysis; (2) defining candidate movement modes and translating them into non-linear or linear equations between net squared displacement (NSD) and time; and (3) fitting each candidate equation to NSD segments and determining the best-fitting modes using Concordance Criteria, Akaike's Information Criteria and other fine-scale segment characteristics. We illustrate our approach for three sub-adults, male wild boar Sus scrofa tracked at 15 min intervals over 4 months using GPS collars. We defined five candidate movement modes based on previously published studies of short-term movements: encamped, ranging, round trips (complete and partial), and wandering. 3. Our approach successfully classified over 80% of the tracks into these movement modes lasting between 5 and 54 hours and covering between 300 m to 20 km. Repeated analyses of GPS data resampled at different rates indicated that one positional fix every 3-4 h was sufficient for >70% classification success. Classified modes were consistent with published observations of wild boar movement, further validating our method. 4. The proposed approach advances the status quo by permitting classification into multiple movement modes (where these are adequately discernable from spatial fixes) facilitating analyses at high temporal and spatial resolutions, and is straightforward, largely objective, and without restrictive assumptions, necessary parameterizations or visual interpretation. Thus, it should capture the complexity and variability of tracked animal movement mode for a variety of taxa across a wide range of spatial and temporal scales.

opencc-zeroDec 2018View details →

Data from: How sexual and natural selection shape sexual size dimorphism: evidence from multiple evolutionary scales

1. Sexual size dimorphism (SSD) is pervasive across taxa and reflects differences in the effects of sexual and natural selection on body size between the sexes. However, disentangling the complex eco-evolutionary interactions between these two mechanisms remains a major challenge for biologists. 2. Here, we combine macro-evolutionary (between-species), local evolutionary (between-population) and fine-scale evolutionary (within-population) patterns of SSD to explore how sexual and natural selection interact and shape the evolution of SSD in Australian agamid lizards. Australian agamid lizards show substantial variation in SSD, ecological traits and species density making them an ideal study system to address this question. 3. At the between-species level, population density, ecological generalism and mean species size significantly predict SSD variation, however, only ecological generalism was found to significantly explain variation in larger than average male-biased SSD. At the population level, density positively correlated with SSD in native habitats, but not city park habitats. Last, agonistic behaviour acted as the primary driver of SSD at the within-population level. 4. Our results indicate how sexual and natural selection can interact at different evolutionary scales, and show the importance of considering both selective mechanisms when investigating patterns of SSD.

opencc-zeroDec 2015View details →

Data from: Fine scale genetic structure among greater sage-grouse leks in central Nevada

Background: Mating systems that reduce dispersal and lead to non-random mating might increase the potential for genetic structure to arise at fine geographic scales. Greater sage-grouse (Centrocercus urophasianus) have a lek-based mating system and exhibit high site fidelity and skewed mating ratios. We quantified population structure by analyzing variation at 27,866 single-nucleotide polymorphisms in 140 males from ten leks (within five lek complexes) occurring in a small geographic region in central Nevada. Results: Lek complexes, and to a lesser extent individual leks, formed statistically identifiable clusters in ordination analyses, providing evidence for fine-scale geographic genetic differentiation. Lek geography predicted genetic differentiation even at a small geographic scale, which could be sharpened by strong site fidelity. Relatedness was also higher among individuals within lek complexes (and leks), suggesting that reproductive skew, where few males participate in most of the successful matings, could also potentially contribute to genetic differentiation. Models incorporating a habitat resistance surface as a proxy for potentially reduced movement due to landscape features indicated that both geographic distance and habitat suitability (i.e. preferred habitat) predicted genetic structure, with no significant effect of man-made barriers to movement (i.e. power lines and roads). Finally, we illustrate how data sets containing fewer loci (<4000) had less statistical precision and failed to detect the full degree of genetic structure. Conclusion: Our results suggest that habitat features and lek site geography of sage-grouse shape fine scale genetic structure, and highlight how larger data sets can have increased precision and accuracy for quantifying ecologically relevant genetic structure over small geographic scales.

opencc-zeroFeb 2020View details →

The role of environmental vs. biotic filtering in the structure of European ant communities: a matter of trait type and spatial scale

<p>Functional trait-based approaches are increasingly used for studying the processes underlying community assembly. The relative influence of different assembly rules might depend on the spatial scale of analysis, the environmental context and the type of functional traits considered. By using a functional trait-based approach, we aim to disentangle the relative role of environmental filtering and interspecific competition on the structure of European ant communities according to the spatial scale and the type of trait considered. We used a large database on ant species composition that encompasses 361 ant communities distributed across the five biogeographic regions of Europe; these communities were composed of 155 ant species, which were characterized by 6 functional traits. We then analysed the relationship between functional divergence and co-occurrence between species pairs across different spatial scales (European, biogeographic region and local) and considering different types of traits (ecological tolerance and niche traits). Three different patterns emerged: negative, positive and non-significant regression coefficients suggest that environmental filtering, competition and neutrality are at work, respectively. We found that environmental filtering is important for structuring European ant communities at large spatial scales, particularly at the scale of Europe and most biogeographic regions. Competition could play a certain role at intermediate spatial scales where temperatures are more favourable for ant productivity (i.e. the Mediterranean region), while neutrality might be especially relevant in spatially discontinuous regions (i.e. the Alpine region). We found that no ecological mechanism (environmental filtering or competition) prevails at the local scale. The type of trait is especially important when looking for different assembly rules, and multi-trait grouping works well for traits associated with environmental responses (tolerance traits), but not for traits related to resource exploitation (niche traits). The spatial scale of analysis, the environmental context and the chosen traits merit special attention in trait-based analyses of community assembly mechanisms.</p>

opencc-zeroDec 2018View details →

Data from: Diversity dynamics of Phanerozoic terrestrial tetrapods at the local-community scale

The fossil record provides one of the strongest tests of the hypothesis that diversity within local communities is constrained over geological timescales. Constraints to diversity are particularly controversial in modern terrestrial ecosystems, yet long-term patterns are poorly understood. Here we document patterns of local richness in Phanerozoic terrestrial tetrapods using a global data set comprising 145,332 taxon occurrences from 27,531 collections. We show that the local richness of non-flying terrestrial tetrapods has risen asymptotically since their initial colonization of land, increasing at most threefold over the last 300 million years. Statistical comparisons support phase-shift models, with most increases in local richness occurring: (1) during the colonization of land by vertebrates, concluding by the late Carboniferous; and (2) across the Cretaceous/Paleogene boundary. Individual groups, such as mammals, lepidosaurs and dinosaurs also experienced early increases followed by periods of stasis often lasting tens of millions of years. Mammal local richness abruptly tripled across the Cretaceous/Paleogene boundary, but did not increase over the next 66 million years. These patterns are consistent with the hypothesis that diversity is constrained at the local-community scale.

Data from: Micro-scale environmental variation amplifies physiological variation among individual mussels

The contributions of temporal and spatial environmental variation to physiological variation remain poorly resolved. Rocky intertidal zone populations are subjected to thermal variation over the tidal cycle, superimposed with micro-scale variation in individuals' body temperatures. Using the sea mussel (<i>Mytilus californianus</i>), we assessed the consequences of this micro-scale environmental variation for physiological variation among individuals, first by examining the latter in field-acclimatized animals, second by abolishing micro-scale environmental variation via common garden acclimation, and third by restoring this variation using a reciprocal outplant approach. Common garden acclimation reduced the magnitude of variation in tissue-level antioxidant capacities by ~30% among mussels from a wave-protected (warm) site, but it had no effect on antioxidant variation among mussels from a wave-exposed (cool) site. The field-acclimatized level of antioxidant variation was restored only when protected-site mussels were outplanted to a high, thermally stressful site. Variation in organismal oxygen consumption rates reflected antioxidant patterns, decreasing dramatically among protected-site mussels after common gardening. These results suggest a highly plastic relationship between individuals' genotypes and their physiological phenotypes that depends on recent environmental experience. Corresponding context-dependent changes in the physiological mean-variance relationships within populations complicate prediction of responses to shifts in environmental variability that are anticipated with global change.

opencc-zeroNov 2019View details →

Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

<div class="page"> <div class="section"> <p>Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016-0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.</p> </div> </div>

opencc-zeroDec 2013View details →

Data from: Fire-regime complacency and sensitivity to centennial- through millennial-scale climate change in Rocky Mountain subalpine forests, Colorado, U.S.A.

1. Key uncertainties in anticipating future fire regimes are their sensitivity to climate change, and the degree to which climate will impact fire regimes directly, through increasing the probability of fire, versus indirectly, through changes in vegetation and landscape flammability. 2. We studied the sensitivity of subalpine forest fire regimes (i.e., fire frequency, fire severity) to previously documented climate variability over the past 6000 years, utilizing pollen and macroscopic charcoal from high-resolution lake-sediment records in Rocky Mountain National Park, Colorado. We combined data from the four lakes to provide composite records of vegetation and fire history within a 200 km2 study area. 3. Rates of forest burning were relatively complacent to millennial-scale summer cooling and decreased effective moisture. Mean return intervals between fire episodes, defined over 500-year periods, generally varied between 150-250 years, consistent with tree-ring-based estimates spanning recent centuries. Variability around these long-term means, however, was significantly correlated with variability in summer moisture (i.e., more burning with drier summers), inferred from existing lake-level and supporting paleoenvironmental records. 4. The most pronounced change in fire regimes was in response to decreased subalpine forest density ca. 2400 cal. year BP, itself a response to regional cooling. This indirect impact of climate was followed by a decrease in charcoal production per fire, a proxy for crown-fire severity, while the long-term rate of burning remained unchanged. Over the last 1500 years, increased summer evaporation and drought frequency were associated with increased fire severity, highlighting a direct link between fire and climate. 5. Synthesis: Subalpine forest fire history reveals complacency and sensitivity of fire regimes to changing vegetation and hydroclimate over the past 6000 years. Complacency is highlighted by non-varying fire frequency over millennia. Sensitivity is evident through changes in biomass burned per fire (and inferred fire severity), in response to climate-induced changes in forest density and, more recently, increased summer drought. Overall, the paleo record suggests that (i) fire severity may be more responsive to climate change than fire frequency in Rocky Mountain subalpine forests, and (ii) the indirect impacts of climate on vegetation and fuels are important mechanisms determining fire-regime response to climate change.

Data from: The relationship between dN/dS and scaled selection coefficients

Numerous computational methods exist to assess the mode and strength of natural selection in protein-coding sequences, yet how distinct methods relate to one another remains largely unknown. Here, we elucidate the relationship between two widely-used phylogenetic modeling frameworks: dN/dS models and mutation-selection (MutSel) models. We derive a mathematical relationship between dN/dS and scaled selection coefficients, the focal parameters of MutSel models, and use this relationship to gain deeper insight into the behaviors, limitations, and applicabilities of these two modeling frameworks. We prove that, if all synonymous changes are neutral, standard MutSel models correspond to dN/dS < 1. However, if synonymous codons differ in fitness, dN/dS can take on arbitrarily high values even if all selection is purifying. Thus, the MutSel modeling framework cannot necessarily accommodate positive, diversifying selection, while dN/dS cannot distinguish between purifying selection on synonymous codons and positive selection on amino acids. We further propose a new benchmarking strategy of dN/dS inferences against MutSel simulations and demonstrate that the widely-used Goldman-Yang-style dN/dS models yield substantially biased dN/dS estimates on realistic sequence data. By contrast, the less frequently used Muse-Gaut-style models display much less bias. Strikingly, the least-biased and most-precise dN/dS estimates are never found in the models with the best fit to the data, measured through both AIC and BIC scores. Thus, selecting models based on goodness-of-fit criteria can yield poor parameter estimates if the models considered do not precisely correspond to the underlying mechanism that generated the data. In conclusion, establishing mathematical links among modeling frameworks represents a novel, powerful strategy to pinpoint previously unrecognized model limitations and strengths.

opencc-zeroDec 2017View details →

Data from: Landscape history confounds the ability of the NDVI to detect fine-scale variation in grassland communities

1. The NDVI is a remotely-sensed vegetation index that is frequently used in ecological studies. There is, however, a lack of studies that evaluate the ability of the NDVI to detect fine-scale variation in grassland plant community composition and species richness. Ellenberg indicators characterize the environmental preferences of plant species – and community-mean Ellenberg values have been used to explore the environmental drivers of community assembly. 2. We used variation partitioning to test the ability of satellite-based NDVI to explain community-mean Ellenberg nutrient (mN) and moisture (mF) indices, and the richness of habitat-specialist species in dry grasslands of different ages. The grasslands represent a gradient of decreasing soil nutrient status. 3. If community composition is determined by the responses of individual species to the underlying environmental conditions and if, at the same time, community composition determines the optical characteristics of the vegetation canopy, then positive relationships between the NDVI and mN and mF are expected. Many grassland specialists are intolerant of nutrient-rich soils. If specialist richness is negatively related to soil-nutrient levels, then a negative association between the NDVI and specialist richness is expected. However, because grassland community composition is not only influenced by abiotic variables but also by other spatial and temporal drivers, we included spatial variables and grassland age in the statistical analyses. 4. The NDVI explained the majority of the variation in mF, and also contributed to a substantial proportion of the variation in mN. However, variation in specialist richness and the lowest values of mN were explained by grassland age and spatial variables – but were poorly explained by the NDVI. 5. Synthesis and applications. The NDVI showed a good ability to detect variation in plant community composition, and should provide a valuable tool for assessing fine-scale environmental variation in grasslands or for monitoring changes in grassland habitat properties. However, because the concentration of grassland specialists not only depends on environmental variables but also on the age and spatial context of the grasslands, the NDVI is unlikely to allow the identification of grasslands with high numbers of specialist species.

Data from: On the relative importance of CSR ecological strategies and integrative traits to explain species dominance at local scales

PLEASE NOTE, PART OF THESE DATA ARE ALSO REFERRED TO ANOTHER ARTICLE. PLEASE SEE http://dx.doi.org/10.1111/j.1654-1103.2009.01119.x FOR MORE INFORMATION. 1. Identifying ecological strategies based on functional traits has been one of the main focuses of studies on plant community assembly. Recently, an important and timely tool, "StrateFy", has been proposed for detecting plant strategies across the globe according to the CSR scheme. The CSR scheme is undeniably efficient across scales, and distinct CSR strategies among species have been proposed to explain differing degrees of dominance among species. However, in a previous study we showed that dominance ranking of woody species in a resource-poor habitat (coastal sandy plain) was not explained by morphological traits commonly measured in functional approaches (such as those used to estimate CSR strategies), but by integrative traits (i.e. traits that are the result of different combinations of functional traits) more related to plant performance. 2. Here, we used CSR analysis and StrateFy on a dataset collected on a coastal sandy plain to test the hypothesis that the dominance ranking would be compatible with the CSR strategies; i.e., that dominant species would show a greater proportion of the stress-tolerance (S%) strategy than subordinate species. 3. Contrary to our hypothesis, all species exhibited an S/CS strategy, and the most-dominant species had neither similar values nor the highest S%. The inability of CSR analysis (as applied using StrateFy) to predict dominance ranking suggests that it can explain relative dominance when different strategies co-occur, but not in cases where dominant and subordinate plants share the same strategy. 4. We argue that the relative importance of CSR and integrative traits for describing dominance ranking may depend on how CSR strategies are filtered in each environment. In environments where only a narrow range of strategy classes are viable, integrative traits may be more important for explaining variation in degrees of dominance. Thus, the ability of a given species to achieve dominance may depend on integrative traits resulting from multiple trait arrays, not necessarily captured by the SLA, LDMC and LA measurements that are used to calculate the relative proportions of strategies in StrateFy.

Data from: Size structuring and allometric scaling relationships in coral reef fishes

Temperate marine fish communities are often size structured, with predators consuming increasingly larger prey and feeding at higher trophic levels as they grow. Gape limitation and ontogenetic diet shifts are key mechanisms by which size structuring arises in these communities. Little is known, however, about size structuring in coral reef fishes. Here, we aimed to advance understanding of size structuring in coral reef food webs by examining the evidence for these mechanisms in two groups of reef predators. Given the diversity of feeding modes amongst coral reef fishes, we also compared gape size—body size allometric relationships across functional groups to determine if they are reliable indicators of size structuring. We used gut content analysis and quantile regressions of predator size—prey size relationships to test for evidence of gape limitation and ontogenetic niche shifts in reef piscivores (n=13 species) and benthic invertivores (n=3 species). We then estimated gape size—body size allometric scaling coefficients for 21 different species from four functional groups, including herbivores/detritivores, which are not expected to be gape-limited. We found evidence of both mechanisms for size structuring in coral reef piscivores, with maximum prey size scaling positively with predator body size, and ontogenetic diet shifts including prey type and expansion of prey size. There was, however, little evidence of size structuring in benthic invertivores. Across species and functional groups, absolute and relative gape sizes were largest in piscivores as expected, but gape size—body size scaling relationships were not indicative of size structuring. Instead, relative gape sizes and mouth morphologies may be better indicators. Our results provide evidence that coral reef piscivores are size-structured, and that gape limitation and ontogenetic niche shifts are the mechanisms from which this structure arises. Although gape allometry was not indicative of size structuring, it may have implications for ecosystem function: positively allometric gape size—body size scaling relationships in herbivores/detritivores suggests that loss of large-bodied individuals of these species will have a disproportionately negative impact on reef grazing pressure.

Data from: Fine-scale movement responses of free-ranging harbour porpoises to capture, tagging, and short-term noise pulses from a single airgun

Knowledge about the impact of anthropogenic disturbances on the behavioural responses of cetaceans is constrained by lack of data on fine-scale movements of individuals. We equipped five free-ranging harbour porpoises (Phocoena phocoena) with high-resolution location and dive loggers and exposed them to a single 10 in3 underwater airgun producing high-intensity noise pulses (2−3 second intervals) for one minute. All five porpoises responded to capture and tagging with longer, faster and more directed movements as well as with shorter, shallower, less wiggly dives immediately after release, with natural behaviour resumed in ≤24 hours. When we exposed porpoises to airgun pulses at ranges of 420−690 m with noise level estimates of 135−147 dB re 1µPa2s (SEL), one individual displayed rapid and directed movements away from the exposure site and two individuals used shorter and shallower dives compared to natural behaviour immediately after exposure. Noise-induced movement typically lasted for ≤8 hours with an additional 24-hour recovery period until natural behaviour was resumed. The remaining individuals did not show any quantifiable responses to the noise exposure. Changes in natural behaviour following anthropogenic disturbances may reduce feeding opportunities and evaluating potential population-level consequences should be a priority research area.

opencc-zeroDec 2013View details →

Data from: Intraspecific scaling of the resting and maximum metabolic rates of the crucian carp (Carassius auratus)

The question of how the scaling of metabolic rate with body mass (M) is achieved in animals is unresolved. Here, we tested the cell metabolism hypothesis and the organ size hypothesis by assessing the mass scaling of the resting metabolic rate (RMR), maximum metabolic rate (MMR), erythrocyte size, and the masses of metabolically active organs in the crucian carp (Carassius auratus). The M of the crucian carp ranged from 4.5 to 323.9 g, representing an approximately 72-fold difference. The RMR and MMR increased with M according to the allometric equations RMR = 0.212M0.776 and MMR = 0.753M0.785. The scaling exponents for RMR (br) and MMR (bm) obtained in crucian carp were close to each other. Thus, the factorial aerobic scope remained almost constant with increasing M. Although erythrocyte size was negatively correlated with both mass-specific RMR and absolute RMR adjusted to M, it and all other hematological parameters showed no significant relationship with M. These data demonstrate that the cell metabolism hypothesis does not describe metabolic scaling in the crucian carp, suggesting that erythrocyte size may not represent the general size of other cell types in this fish and the metabolic activity of cells may decrease as fish grows. The mass scaling exponents of active organs was lower than 1 while that of inactive organs was greater than 1, which suggests that the mass scaling of the RMR can be partly due to variance in the proportion of active/inactive organs in crucian carp. Furthermore, our results provide additional evidence supporting the correlation between locomotor capacity and metabolic scaling.

Data from: Template for using biological trait groupings when exploring large-scale variation in seafloor multifunctionality

Understanding large-scale spatial variation in ecosystem properties and associated functionality is key for successful conservation of ecosystems. This study provides a template for how to estimate differences in ecosystem functionality over large spatial scales by using groupings of biological traits. We focus on trait groupings that describe three important benthic ecosystem properties, namely bioturbation, community stability and juvenile dispersal. Recognizing that groups of traits interact and are constrained within an organism, we statistically define important functional trait subgroups that describe each ecosystem property. The sub-groups are scored according to their weighted ecological impact to gain an overall estimation of the cumulative expression of each ecosystem property at individual sites. Furthermore, by assigning each property a value relative to its observed maximum, and by summing up the individual property values, we offer an estimate of benthic ecosystem multifunctionality. Based on a spatially extensive benthic data set, we were able to identify coastal areas with high and low potential for the considered benthic ecosystem properties and the measure of ecosystem multifunctionality. Importantly, we show that a large part of the spatial variation in functional trait sub-groups and in benthic ecosystem multifunctionality was explained by environmental change. Our results indicate that through this simplification it is possible to estimate the functionality of the seafloor. Such information is vital in marine spatial planning efforts striving to balance the utilization with the preservation of natural resources.

Data from: Benefits and challenges of scaling up expansion of marine protected area networks in the Verde Island Passage, Central Philippines

Locally-established marine protected areas (MPAs) have been proven to achieve local-scale fisheries and conservation objectives. However, since many of these MPAs were not designed to form ecologically-connected networks, their contributions to broader-scale goals such as complementarity and connectivity can be limited. In contrast, integrated networks of MPAs designed with systematic conservation planning are assumed to be more effective—ecologically, socially, and economically—than collections of locally-established MPAs. There is, however, little empirical evidence that clearly demonstrates the supposed advantages of systematic MPA networks. A key reason is the poor record of implementation of systematic plans attributable to lack of local buy-in. An intermediate scenario for the expansion of MPAs is scaling up of local decisions, whereby locally-driven MPA initiatives are coordinated through collaborative partnerships among local governments and their communities. Coordination has the potential to extend the benefits of individual MPAs and perhaps to approach the potential benefits offered by systematic MPA networks. We evaluated the benefits of scaling up local MPAs to form networks by simulating seven expansion scenarios for MPAs in the Verde Island Passage, central Philippines. The scenarios were: uncoordinated community-based establishment of MPAs; two scenarios reflecting different levels of coordinated MPA expansion through collaborative partnerships; and four scenarios guided by systematic conservation planning with different contexts for governance. For each scenario, we measured benefits through time in terms of achievement of objectives for representation of marine habitats. We found that: in any governance context, systematic networks were more efficient than non-systematic ones; systematic networks were more efficient in broader governance contexts; and, contrary to expectations but with caveats, the uncoordinated scenario was slightly more efficient than the coordinated scenarios. Overall, however, coordinated MPA networks have the potential to be more efficient than the uncoordinated ones, especially when coordinated planning uses systematic methods.

Data from: Spatial scaling of environmental variables improves species-habitat models of fishes in a small, sand-bed lowland river

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species' presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale.

opencc-zeroJun 2019View details →

Data from: Phenotype-environment mismatch in metapopulations - implications for the maintenance of maladaptation at the regional scale

Maladaptation is widespread in natural populations. However, maladaptation has most often been associated with absolute population decline in local habitats rather than on a spectrum of relative fitness variation that can assist natural populations in their persistence at larger regional scales. We report results from a field experiment that tested for relative maladaptation between pond habitats with spatial heterogeneity and (a)symmetric selection in pH. In the experiment, we quantified relative maladaptation in a copepod metapopulation as a mismatch between the mean population phenotype and the optimal trait value that would maximize mean population fitness under either stable or fluctuating pH environmental conditions. To complement the field experiment, we constructed a metapopulation model that addressed both relative (distance from the optimum) and absolute (negative population growth) maladaptation, with the aim of forecasting maladaptation to pH at the regional scale in relation to spatial structure (environmental heterogeneity and connectivity) and temporal environmental fluctuations. The results from our experiment indicated that maladaptation to pH at the regional scale depended on the asymmetry of the fitness surface at the local level. The results from our metapopulation model revealed how dispersal and (a)symmetric selection can operate on the fitness surface to maintain maladaptive phenotype-environment mismatch at local and regional scales in a metapopulation. Environmental stochasticity resulted in the maintenance of maladaptation that was robust to dispersal, but also revealed an interaction between the asymmetry in selection and environmental correlation. Our findings emphasize the importance of maladaptation for planning conservation strategies that can support adaptive potential in fragmented and changing landscapes.