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in category ecology
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1,959 downloads ecology
The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package ( `rmangal`) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.
1,954 downloads ecology
DNA sampled from the environment (eDNA) is becoming a game changer for uncovering biodiversity patterns. By combining a conceptual model and empirical data, we test whether eDNA transported in river networks can be used as an integrative way to assess eukaryotic biodiversity for broad spatial scales and across the land-water interface. Using an eDNA metabarcode approach we detected 296 families of eukaryotes, spanning 19 phyla across the catchment of a river. We show for a subset of these families that eDNA samples overcome spatial autocorrelation biases associated with classical community assessments by integrating biodiversity information over space. Additionally, we demonstrate that many terrestrial species can be detected; thus revealing that eDNA in river-water also incorporates biodiversity information across terrestrial and aquatic biomes. Environmental DNA transported in river networks offers a novel and spatially integrated way to assess total biodiversity for whole landscapes and will transform biodiversity data acquisition in ecology.
1,919 downloads ecology
Climate change during the last five decades has impacted significantly on natural ecosystems and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian Order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical and habitat variables for all 87 species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current distribution models and only those deemed ‘modellable’ through our framework were projected under future climate scenarios (58 species). We then used phylogenetically-controlled regressions to test whether species traits were correlated with predicted responses to climate change. Climate change will impact more than two-thirds of the Lagomorpha, with leporids (rabbits, hares and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management.
1,907 downloads ecology
Pollen is the main protein and lipid source for honey bees (Apis mellifera), and nutritionally impoverished landscapes pose a threat to colony development. To determine colony nutritional demands, we analyzed a yearly cycle of bee-collected pollen from colonies in the field and compared it to colony worker production and honey bee body composition, for the first time in social insects. We monitored monthly bee production in ten colonies at each of seven sites throughout Israel, and trapped pollen bi-monthly in five additional colonies at each of four of these sites. Pollen mixtures from each sampling date and site were analyzed for weight, total protein, total fatty acids (FAs), and FA composition. Compared to more temperate climates, the eastern Mediterranean allows a relatively high yearly colony growth of ca. 300,000 to 400,000 bees. Colonies at higher elevation above sea level showed lower growth rates. Queen egg-laying rate did not seem to limit growth, as peaks in capped brood areas showed that queens lay a prolific 2,000 eggs a day on average, with up to 3,300 eggs in individual cases. Pollen uptake varied significantly among sites and seasons, with an overall annual mean total 16.8 kg per colony, containing 7.14 kg protein and 677 g fat. Overall mean pollen protein content was high (39.8%), and mean total FA content was 3.8%. Production cost, as expressed by the amount of nutrient used per bee, was least variable for linoleic acid and protein, suggesting these as the best descriptive variables for total number of bees produced. Linolenic acid levels in pollen during the autumn were relatively low, and supplementing colonies with this essential FA may mitigate potential nutritional deficiency. The essentiality of linoleic and linolenic acids was consistent with these FAs' tendency to be present at higher levels in collected pollen than in the expected nutrients in bee bodies, demonstrating a well-developed adjustment between pollinator nutritional demands and the nutritional value of food offered by pollinated plants.
1,902 downloads ecology
Determining the host-parasitoid interactions and parasitism rates for invasive species entering novel environments is an important first step in assessing potential routes for biocontrol and integrated pest management. Conventional insect rearing techniques followed by taxonomic identification are widely used to obtain such data, but this can be time consuming and prone to biases. Here we present a Next Generation Sequencing approach for use in ecological studies which allows for individual level metadata tracking of large numbers of invertebrate samples through the use of hierarchically organised molecular identification tags. We demonstrate its utility using a sample data set examining both species identity and levels of parasitism in late larval stages of the Oak Processionary Moth (Thaumetopoea processionea - Linn. 1758), an invasive species recently established in the UK. Overall we find that there are two main species exploiting the late larval stages of Oak Processionary Moth in the UK with the main parasitoid (Carcelia iliaca - Ratzeburg, 1840) parasitising 45.7% of caterpillars, while a rare secondary parasitoid (Compsilura conccinata - Meigen, 1824) was also detected in 0.4% of caterpillars. Using this approach on all life stages of the Oak Processionary Moth may demonstrate additional parasitoid diversity. We discuss the wider potential of nested tagging DNA-metabarcoding for constructing large, highly-resolved species interaction networks.
1,848 downloads ecology
Introduced species of mammals in New Zealand have had catastrophic effects on populations of diverse native species. Quantifying the diets of these omnivorous and predatory species is critical for understanding which native species are most impacted, and to prioritize which mammal species and locations should be targeted with control programmes. A variety of methods have been applied to quantify diet components in animals, including visual inspection of gut contents (Daniel 1973; Pierce and Boyle 1991), stable isotope analysis (Major et al. 2007; Carreon-Martinez and Heath 2010), and time-lapse video (Brown and Brown 1997; Dunlap and Pawlik 1996). Increasingly, DNA-based metabarcoding methods are being used (King et al. 2008; Soininen et al. 2009). These metabarcoding methods require a PCR step using primers that bind to highly conserved genomic regions (e.g. mitochondrial COI) to amplify specific regions for sequencing. This step introduces significant bias, primarily due to the lack of a universal primer set (King et al. 2008). Here we show that direct metagenomic sequencing using the Oxford Nanopore Minion allows rapid quantification of rat diets. Using a sample of rats collected from within 100km of Auckland, NZ, we show that these rats consume a wide variety of plant, invertebrate, vertebrate, and fungal taxa, with substantial differences in diet content between locales. We then show that, based on diet content alone, it is possible to pinpoint the sampling location of an individual rat within tens of kilometres. We expect that the rapidly increasing accuracy and throughput of nanopore-based sequencing, as well as increases in the species diversity of genomic databases, will soon allow rapid and unbiased assessments of animal diets in field settings.
1,844 downloads ecology
Long distance migrations are well known to occur in many baleen whale species. Yet, a global synthesis of this information is lacking. Here, we study baleen whales as a group and at a global scale, first analyzing the grey and peer-reviewed literature for information on the location of baleen whale calving and feeding grounds around the world. This information was then combined with modeled-data produced from an Earth System Model to estimate the global distribution of baleen whale calving and feeding habitats. A simple network theoretic heuristic was then used to identify the shortest over-water path connecting habitats. These shortest paths map well to known major migration routes for a number of species, suggesting that migration has evolved primarily to minimize travel distances. Identifying distance minimizing routes globally, that have demonstrable consistency to known migration routes for certain baleen whale species, offers a useful baseline perspective on large-scale migration patterns, from which many perturbations can by judged. As an example, we used our modeled migration routes to identify regions of the ocean that are likely hotspots of whale ship-strikes. Such information is useful for developing global conservation and management priorities for baleen whales.
1,839 downloads ecology
1. Detecting aquatic macroorganisms with environmental DNA (eDNA) is a new survey method with broad applicability. However, the origin, state, and fate of aqueous macrobial eDNA - which collectively determine how well eDNA can serve as a proxy for directly observing organisms and how eDNA should be captured, purified, and assayed - are poorly understood. 2. The size of aquatic particles provides clues about their origin, state, and fate. We used sequential filtration size fractionation to measure, for the first time, the particle size distribution (PSD) of macrobial eDNA, specifically Common Carp (hereafter referred to as Carp) eDNA. We compared it to the PSDs of total eDNA (from all organisms) and suspended particle matter (SPM). We quantified Carp mitochondrial eDNA using a custom qPCR assay, total eDNA with fluorometry, and SPM with gravimetric analysis. 3. In a lake and a pond, we found Carp eDNA in particles from >180 to <0.2 µm, but it was most abundant from 1-10 µm. Total eDNA was most abundant below 0.2 µm and SPM was most abundant above 100 µm. SPM was ≤0.1% total eDNA, and total eDNA was ≤0.0004% Carp eDNA. 0.2 µm filtration maximized Carp eDNA capture (85%±6%) while minimizing total (i.e., non-target) eDNA capture (48%±3%), but filter clogging limited this pore size to a volume <250 mL. To mitigate this limitation we estimated a continuous PSD model for Carp eDNA and derived an equation for calculating isoclines of pore size and water volume that yield equivalent amounts of Carp eDNA. 4. Our results suggest that aqueous macrobial eDNA predominantly exists inside mitochondria or cells, and that settling plays an important role in its fate. For optimal eDNA capture, we recommend 0.2 µm filtration or a combination of larger pore size and water volume that exceeds the 0.2 µm isocline. In situ filtration of large volumes could maximize detection probability when surveying large habitats for rare organisms. Our method for eDNA particle size analysis enables future research to compare the PSDs of eDNA from other organisms and environments, and to easily apply them for ecological monitoring.
1,829 downloads ecology
This study introduces statistical boosting for capture-mark-recapture (CMR) models. It is a shrinkage estimator that constrains the complexity of a CMR model in order to promote automatic variable-selection and avoid over-fitting. I discuss the philosophical similarities between boosting and AIC model-selection, and show through simulations that a boosted Cormack-Jolly-Seber model often out-performs AICc methods, in terms of estimating survival and abundance, yet yields qualitatively similar estimates. This new boosted CMR framework is highly extensible and could provide a rich, unified framework for addressing many topics in CMR, such as non-linear effects (splines and CART-like trees), individual-heterogeneity, and spatial components.
1,818 downloads ecology
Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to make ecosystem maps from remote sensing data. We have developed a free and open-access online remote sensing and environmental modelling application, REMAP (the remote ecosystem monitoring and assessment pipeline; https://remap-app.org) that enables volunteers, managers, and scientists with little or no experience in remote sensing to develop high-resolution classified maps of land cover and land use change over time. REMAP utilizes the geospatial data storage and analysis capacity of the Google Earth Engine, and requires only spatially resolved training data that define map classes of interest (e.g., ecosystem types). The training data, which can be uploaded or annotated interactively within REMAP, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in REMAP represent topographic (e.g. slope, elevation), spectral (Landsat Archive image composites) and climatic variables (precipitation, temperature) that can inform on the distribution of ecosystems and land cover classes. The ability of REMAP to develop and export high-quality classified maps in a very short (<10 minute) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, REMAP can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales, and supporting environmental education initiatives.
1,815 downloads ecology
Succinate dehydrogenase inhibitors (SDHIs) are now widely used worldwide as fungicides to limit the proliferation of molds in cereal crops, or to better preserve fruits, vegetables, and seeds from these molds, as well as to facilitate the lawn care for public spaces and golf courses. According to the companies that produce them, the SDHIs quite specifically inhibit the activity of the succinate dehydrogenase in the molds. We here establish that these inhibitors readily inhibit the earthworm and the human enzyme, raising a new concern on the danger of their large scale utilization in agriculture. This is all the more worrying as we know that the loss of function, partial or total, of the SDH activity caused by genetic variants causes severe human neurological diseases, or leads to the development of tumors and/or cancers.
1,813 downloads ecology
Erin A Mordecai, Jeremy M. Cohen, Michelle V Evans, Prithvi Gudapati, Leah R. Johnson, Catherine A Lippi, Kerri Miazgowicz, Courtney C Murdock, Jason R Rohr, Sadie J. Ryan, Van Savage, Marta S Shocket, Anna Stewart Ibarra, Matthew B Thomas, Daniel P Weikel
Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.
1,755 downloads ecology
Neotropical migratory birds are declining across the Western Hemisphere, but conservation efforts have been hampered by the inability to assess where migrants are most limited–the breeding grounds, migratory stopover sites, or wintering areas. A major challenge has been the lack of an efficient, reliable, and broadly applicable method for connecting populations across the annual cycle. Here we show how high-resolution genetic markers can be used to identify populations of a migratory bird, the Wilson's warbler (Cardellina pusilla), at fine enough spatial scales to facilitate assessing regional drivers of demographic trends. By screening 1626 samples using 96 single nucleotide polymorphisms (SNPs) selected from a large pool of candidates (~450,000), we identify novel region-specific migratory routes and timetables of migration along the Pacific Flyway. Our results illustrate that high-resolution genetic markers are more reliable, accurate, and amenable to high throughput screening than previously described tracking techniques, making them broadly applicable to large-scale monitoring and conservation of migratory organisms.
1,753 downloads ecology
Matteo Dainese, Emily A. Martin, Marcelo Aizen, Matthias Albrecht, Ignasi Bartomeus, Riccardo Bommarco, Luisa G. Carvalheiro, Rebecca Chaplin-Kramer, Vesna Gagic, Lucas A. Garibaldi, Jaboury Ghazoul, Heather Grab, Mattias Jonsson, Daniel S Karp, Christina M. Kennedy, David Kleijn, Claire Kremen, Douglas A. Landis, Deborah K. Letourneau, Lorenzo Marini, Katja Poveda, Romina Rader, Henrik G. Smith, Teja Tscharntke, Georg K.S. Andersson, Isabelle Badenhausser, Svenja Baensch, Antonio Diego M. Bezerra, Felix J.J.A. Bianchi, Virginie Boreux, Vincent Bretagnolle, Berta Caballero-Lopez, Pablo Cavigliasso, Aleksandar Cetkovic, Natacha P. Chacoff, Alice Classen, Sarah Cusser, Felipe D. da Silva e Silva, G. Arjen de Groot, Jan H. Dudenhoffer, Johan Ekroos, Thijs Fijen, Pierre Franck, Breno M. Freitas, Michael P.D. Garratt, Claudio Gratton, Juanhipolito Hipolito, Andrea Holzschuh, Lauren Hunt, Aaron L. Iverson, Shalene Jha, Tamar Keasar, Tania N. Kim, Miriam Kishinevsky, Bjorn K. Klatt, Alexandra Klein, Kristin M. Krewenka, Smitha Krishnan, Ashley E. Larsen, Claire Lavigne, Heide Leire, Bea Maas, Maike Nesper, Rachel E. Mallinger, Eliana Martinez, Alejandra Martinez-Salinas, Tim D. Meehan, Matthew G.E. Mitchell, Gonzalo A.R. Molina, Lovisa Nilsson, Megan O'Rourke, Marcell K. Peters, Milan Plecas, SImon G. Potts, Davi de L. Ramos, Jay A. Rosenheim, Maj Rundlof, Adrien Rusch, Agustin Saez, Jeroen Scheper, Matthias Schleuning, Julia Schmack, Amber R. Sciligo, Colleen Seymour, Dara A. Stanley, Rebecca Stewart, Jane C. Stout, Louis Sutter, Mayura B. Takada, Hisatomo Taki, Giovanni Tamburini, Matthias Tschumi, Blandina F. Viana, Catrin Westphal, Bryony K. Wilcox, Steve D. Wratten, Akira Yoshioka, Carlos Zaragoza, Wei Zhang, Yi Zou, Ingolf Steffan-Dewenter
Human land use threatens global biodiversity and compromises multiple ecosystem functions critical to food production. Whether crop yield-related ecosystem services can be maintained by few abundant species or rely on high richness remains unclear. Using a global database from 89 crop systems, we partition the relative importance of abundance and species richness for pollination, biological pest control and final yields in the context of on-going land-use change. Pollinator and enemy richness directly supported ecosystem services independent of abundance. Up to 50% of the negative effects of landscape simplification on ecosystem services was due to richness losses of service-providing organisms, with negative consequences for crop yields. Maintaining the biodiversity of ecosystem service providers is therefore vital to sustain the flow of key agroecosystem benefits to society.
1,672 downloads ecology
Popular frameworks for studying habitat selection include resource-selection functions (RSFs) and step-selection functions (SSFs) estimated using logistic and conditional logistic regression, respectively. Both frameworks compare environmental covariates associated with locations animals visit with environmental covariates at a set of locations assumed available to the animal. Conceptually, random coefficients could be used to accommodate inter-individual heterogeneity with either approach, but straightforward and efficient one-step procedures for fitting SSFs with random coefficients are currently lacking. We take advantage of the fact that the conditional logistic regression model (i.e., the SSF) is likelihood-equivalent to a Poisson model with stratum-specific intercepts. By interpreting the intercepts as a random effect with a large (fixed) variance, inference becomes feasible with standard Bayesian techniques, but also with frequentist methods that allow one to fix the variance of a random effect. We compare this approach to other commonly applied alternatives, including random intercept-only models, and to a two-step algorithm for fitting mixed-effects models. We also reinforce the need to weight available points when fitting RSFs, since models fit using "infinitely weighted logistic regression" have been shown to be equivalent to an inhomogeneous Poisson process (IPP). We generalize this result to "infinitely weighted Poisson regression", which converges to the same underlying IPP distribution. Using data from Eurasian otters (Lutra lutra) and mountain goats (Oreamnos americanus), we illustrate that our models lead to valid and feasible inference. In addition, we conduct a simulation study to demonstrate the importance of including random slopes when estimating individual- and population-level habitat-selection parameters. By providing coded examples using integrated nested Laplace approximations (INLA) and Template Model Builder (TMB) for Bayesian and frequentist analysis via the R packages R-INLA and glmmTMB, we hope to make efficient estimation of RSFs and SSFs with random effects accessible to anyone in the field. SSFs with individual-specific coefficients are particularly attractive since they can provide insights into movement and habitat-selection processes at fine-spatial and temporal scales, but these models had previously been very challenging to fit.
1,671 downloads ecology
Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio-temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population structure. Spatial capture-recapture (SCR) represents an individual-based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g., camera trapping, non-invasive DNA sampling). We describe ways in which SCR methods stand to revolutionize the study of animal population ecology.
1,655 downloads ecology
The rate of carbon uptake by land plants depends on the ratio of leaf-internal to ambient carbon dioxide partial pressures, here termed χ. This quantity is a key determinant of both primary production and transpiration and the relationship between them. But current models for χ are empirical and incomplete, contributing to the many uncertainties afflicting model estimates and future projections of terrestrial carbon uptake. Here we show that a simple evolutionary optimality hypothesis generates functional relationships between χ and growth temperature, vapour pressure deficit and elevation that are precisely and quantitatively consistent with empirical χ values from a worldwide data set containing > 3500 stable carbon isotope measurements. A single global equation embodying these relationships then unifies the empirical light use efficiency model with the standard model of C3photosynthesis, and successfully predicts gross primary production as measured at flux sites. This achievement is notable because of the equation′s simplicity (with just two parameters, both independently estimated) and applicability across biomes and plant functional types. Thereby it provides a theoretical underpinning, grounded in eco-evolutionary principles, for large-scale analysis of the CO2 and water exchanges between atmosphere and land.
1,622 downloads ecology
The gut microbiomes of birds and other animals are increasingly being studied in ecological and evolutionary contexts. While methods for preserving samples and processing high-throughput sequence data to characterise bacterial communities have received considerable attention, there has been little evaluation of non-invasive sampling methods. Numerous studies on birds and reptiles have made inferences about gut microbiota using cloacal sampling, however, it is not known whether the bacterial community of the cloaca provides an accurate representation of the avian gut microbiome. We examined the accuracy with which cloacal swabs and faecal samples measure the microbiota in three different parts of the gastrointestinal tract (ileum, caecum, and colon) using a case study on juvenile ostriches, Struthio camelus, and high-throughput 16S rRNA sequencing. We found that faeces were significantly better than cloacal swabs in representing the bacterial community of the colon. Cloacal samples had a higher abundance of Gammaproteobacteria and fewer Clostridia relative to the gut and faecal samples. However, both faecal and cloacal samples were poor representatives of the microbial communities in the caecum and ileum. Furthermore, the accuracy of the sampling methods in measuring the abundance of different bacterial taxa was highly variable: Bacteroidetes was the most highly correlated phylum between all three gut sections and both methods, whereas colonic Actinobacteria correlated strongly only with faecal samples. This study demonstrates that sampling methods can have significant effects on the inferred gut microbiome in studies of birds. Based on our results, we recommend sampling faeces, whenever possible, as this provides the most accurate assessment of the colon microbiome. The fact that neither sampling technique portrayed the bacterial community of the ileum or the caecum illustrates the difficulty in non-invasively monitoring gut bacteria located further up in the gastrointestinal tract. These results have important implications for the interpretation of avian gut microbiome studies.
1,606 downloads ecology
The current outbreak of Zika virus poses a threat of unknown magnitude to human health. While the range of the virus has been cataloged growing slowly over the last 50 years, the recent explosive expansion in the Americas indicates that the full potential distribution of Zika remains uncertain. Moreover, most current epidemiology relies on its similarities to dengue fever, a phylogenetically closely related disease of unknown similarity in spatial range or ecological niche. Here we compile the first spatially explicit global occurrence dataset from Zika viral surveillance and serological surveys, and construct ecological niche models to test basic hypotheses about its spread and potential establishment. The hypothesis that the outbreak of cases in Mexico and North America are anomalous and outside the ecological niche of the disease, and may be linked to El Nino or similar climatic events, remains plausible at this time. Comparison of the Zika niche against the known distribution of dengue fever suggests that Zika is more constrained by the seasonality of precipitation and diurnal temperature fluctuations, likely confining the disease to the tropics outside of pandemic scenarios. Projecting the range of the diseases in conjunction with vector species (Aedes africanus, Ae. aegypti, and Ae. albopictus) that transmit the pathogens, under climate change, suggests that Zika has potential for northward expansion; but, based on current knowledge, Zika is unlikely to fill the full range its vectors occupy. With recent sexual transmission of the virus known to have occurred in the United States, we caution that our results only apply to the vector-borne aspect of the disease, and while the threat of a mosquito-carried Zika pandemic may be overstated in the media, other transmission modes of the virus may emerge and facilitate naturalization worldwide.
1,599 downloads ecology
Complex adaptive systems provides a unified framework for explaining ecosystem phenomena. In the past twenty years, complex adaptive systems has been sharpened from an abstract concept into a series of tools that can be used to solve concrete problems. These advances have been led by the development of new techniques for coupling ecological and evolutionary dynamics, for integrating dynamics across multiple scales of organization, and for using data to infer the complex interactions among different components of ecological systems. Focusing on the development and usage of these new methods, we explore how they have led to an improved understanding of three universal features of complex adaptive systems, emergent patterns; tipping points and critical phenomena; and cooperative behavior. We restrict our attention primarily to marine ecosystems, which provide numerous successful examples of the application of complex adaptive systems. Many of these are currently undergoing dramatic changes due to anthropogenic perturbations, and we take the opportunity to discuss how complex adaptive systems can be used to improve the management of public goods and to better preserve critical ecosystem services.
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