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de Beer IW, Hui C, Botella C, Richardson DM. Drivers of compositional turnover of narrow-ranged versus widespread naturalised woody plants in South Africa. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1106197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
IntroductionAlien trees and shrubs have become increasingly common invaders globally and have caused major negative impacts to ecosystems and society. Non-native woody plant species make up the majority of legislated invasive alien taxa in South Africa and contribute substantially to recorded negative impacts. It is of management interest to elucidate the macroecological processes that mediate the assembly of alien taxa, as this is expected to be associated with anthropogenic factors (e.g., human activity, introduction events, pathways of propagule dispersal mediated by humans) and bioclimatic factors (such as diurnal temperature range and precipitation gradients). These analyses require large species-occurrence datasets with comprehensive sampling across broad environmental conditions. Efforts of citizen scientists produce large numbers of occurrence records in a consistent manner which may be utilised for scientific investigations.MethodsResearch Grade occurrence data on naturalised plants of South Africa were extracted from the citizen scientist platform iNaturalist. Sampling bias was mitigated using statistical modelling of background points estimated from a Target Group of species which identifies well sampled communities. The drivers of assembly for alien plants at different range sizes were identified using multi-site generalised dissimilarity modelling (MS-GDM) of zeta diversity. The predicted compositional similarity between all cells was computed based on the subset of identified well sampled communities and using generalised dissimilarity modelling (GDM). From this, alien bioregions were identified using a k-means cluster analysis.Results and DiscussionBioclimatic factors significantly influenced community turnover in inland areas with large diurnal temperature ranges, and in areas with high precipitation. Communities separated by large geographical distances had significantly different compositions, indicating little contribution of long-range propagule movement by humans, and the presence of localised introduction hubs within the country which harbour unique species compositions. Analyses also showed a significant contribution of road density to turnover, which may be moderated by the habitat service provided by road verges. The same is true for natural dispersal via rivers in arid areas. The distribution of naturalised tree and shrub species is geographically clustered and forms six alien bioregions that are distinct from the South African biomes defined by native species distributionanalysis.
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Wang L, Li Y, Zhao Z, Zhu M, Hu T. Tidal flat aquaculture pollution governs sedimentary antibiotic resistance gene profiles but not bacterial community based on metagenomic data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 833:155206. [PMID: 35421458 DOI: 10.1016/j.scitotenv.2022.155206] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 03/29/2022] [Accepted: 04/08/2022] [Indexed: 06/14/2023]
Abstract
Coastal tidal flats are intersection zones between terrestrial and marine environments and are considered repositories of pollutants from anthropogenic activities (e.g., fishery and aquaculture). Specifically, the prevalence of antibiotics and antibiotic resistance genes (ARGs) in coastal aquaculture environments pose critical threats to estuarine ecosystems. However, the contribution of aquaculture to the occurrence and abundance of ARGs and community assemblies has not been fully explored in tidal flat zones. Thus, we investigated ARGs profiles, ARG-carrying host bacteria, and their associate microbial community in the Dongtai and Sheyang tidal flat aquaculture regions of Jiangsu, China using metagenomic assembly methods. The antibiotic concentrations in the sediment samples ranged from nd to 35.50 ng/g dw, and the antibiotic pollution in the Dongtai tidal flat was more severe than in the Sheyang tidal flats. Metagenomic assembly indicated that a total of 247 ARG subtypes associated with ARG 33 types were characterized across all samples and their abundance in the Dongtai region exceeded that in the Sheyang region. Meanwhile, 21 bacteria in the tidal flat aquaculture were identified as ARG-carrying pathogens, including Escherichia coli, Vibrio fluvialis, and Staphylococcus aureus. Using neutral and null modeling analysis to determine the community ecological processes, the results revealed bacterial and ARG communities were generally dominated by stochastic and deterministic processes, respectively. The above results suggested that aquaculture pollution was contributed to shape ARG profiles in tidal flats. The observed deterministic processes affecting the ARG community in tidal flat aquaculture also provides an effective foundation to control the risks of environmental antibiotic resistance through reducing aquaculture antibiotic usage.
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Affiliation(s)
- Linqiong Wang
- Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Xikang Road #1, Nanjing, China; College of Oceanography, Hohai University, Xikang Road #1, Nanjing, China
| | - Yi Li
- College of Environment, Hohai University, Xikang Road #1, Nanjing, China.
| | - Zhe Zhao
- Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Xikang Road #1, Nanjing, China; College of Oceanography, Hohai University, Xikang Road #1, Nanjing, China
| | - Mengjie Zhu
- College of Environment, Hohai University, Xikang Road #1, Nanjing, China
| | - Tong Hu
- College of Environment, Hohai University, Xikang Road #1, Nanjing, China
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Gao Q, Gao S, Bates C, Zeng Y, Lei J, Su H, Dong Q, Qin Z, Zhao J, Zhang Q, Ning D, Huang Y, Zhou J, Yang Y. The microbial network property as a bio-indicator of antibiotic transmission in the environment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 758:143712. [PMID: 33277004 DOI: 10.1016/j.scitotenv.2020.143712] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 10/18/2020] [Accepted: 11/10/2020] [Indexed: 06/12/2023]
Abstract
Interspecies interaction is an essential mechanism for bacterial communities to develop antibiotic resistance via horizontal gene transfer. Nonetheless, how bacterial interactions vary along the environmental transmission of antibiotics and the underpinnings remain unclear. To address it, we explore potential microbial associations by analyzing bacterial networks generated from 16S rRNA gene sequences and functional networks containing a large number of antibiotic-resistance genes (ARGs). Antibiotic concentration decreased by more than 4000-fold along the environmental transmission chain from manure samples of swine farms to aerobic compost, compost-amended agricultural soils, and neighboring agricultural soils. Both bacterial and functional networks became larger in nodes and links with decreasing antibiotic concentrations, likely resulting from lower antibiotics stress. Nonetheless, bacterial networks became less clustered with decreasing antibiotic concentrations, while functional networks became more clustered. Modularity, a key topological property that enhances system resilience to antibiotic stress, remained high for functional networks, but the modularity values of bacterial networks were the lowest when antibiotic concentrations were intermediate. To explain it, we identified a clear shift from deterministic processes, particularly variable selection, to stochastic processes at intermediate antibiotic concentrations as the dominant mechanism in shaping bacterial communities. Collectively, our results revealed microbial network dynamics and suggest that the modularity value of association networks could serve as an important indicator of antibiotic concentrations in the environment.
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Affiliation(s)
- Qun Gao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shuhong Gao
- School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Colin Bates
- Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA
| | - Yufei Zeng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jiesi Lei
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hang Su
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Qiang Dong
- Institute of Chemical Defense, Beijing 102205, China
| | - Ziyan Qin
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jianshu Zhao
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30318, USA
| | - Qiuting Zhang
- Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA
| | - Daliang Ning
- Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA
| | - Yi Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University, Beijing 100871, China
| | - Jizhong Zhou
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA; Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Yunfeng Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
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Robinson TB, Martin N, Loureiro TG, Matikinca P, Robertson MP. Double trouble: the implications of climate change for biological invasions. NEOBIOTA 2020. [DOI: 10.3897/neobiota.62.55729] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The implications of climate change for biological invasions are multifaceted and vary along the invasion process. Changes in vectors and pathways are likely to manifest in changes in transport routes and destinations, together with altered transit times and traffic volume. Ultimately, changes in the nature of why, how, and where biota are transported and introduced will pose biosecurity challenges. These challenges will require increased human and institutional capacity, as well as proactive responses such as improved early detection, adaptation of present protocols and innovative legal instruments. Invasion success and spread are expected to be moderated by the physiological response of alien and native biota to environmental changes and the ensuing changes in biotic interactions. These in turn will likely affect management actions aimed at eradicating, containing, and mitigating invasions, necessitating an adaptive approach to management that is sensitive to potentially unanticipated outcomes.
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Novoa A, Richardson DM, Pyšek P, Meyerson LA, Bacher S, Canavan S, Catford JA, Čuda J, Essl F, Foxcroft LC, Genovesi P, Hirsch H, Hui C, Jackson MC, Kueffer C, Le Roux JJ, Measey J, Mohanty NP, Moodley D, Müller-Schärer H, Packer JG, Pergl J, Robinson TB, Saul WC, Shackleton RT, Visser V, Weyl OLF, Yannelli FA, Wilson JRU. Invasion syndromes: a systematic approach for predicting biological invasions and facilitating effective management. Biol Invasions 2020. [DOI: 10.1007/s10530-020-02220-w] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
AbstractOur ability to predict invasions has been hindered by the seemingly idiosyncratic context-dependency of individual invasions. However, we argue that robust and useful generalisations in invasion science can be made by considering “invasion syndromes” which we define as “a combination of pathways, alien species traits, and characteristics of the recipient ecosystem which collectively result in predictable dynamics and impacts, and that can be managed effectively using specific policy and management actions”. We describe this approach and outline examples that highlight its utility, including: cacti with clonal fragmentation in arid ecosystems; small aquatic organisms introduced through ballast water in harbours; large ranid frogs with frequent secondary transfers; piscivorous freshwater fishes in connected aquatic ecosystems; plant invasions in high-elevation areas; tall-statured grasses; and tree-feeding insects in forests with suitable hosts. We propose a systematic method for identifying and delimiting invasion syndromes. We argue that invasion syndromes can account for the context-dependency of biological invasions while incorporating insights from comparative studies. Adopting this approach will help to structure thinking, identify transferrable risk assessment and management lessons, and highlight similarities among events that were previously considered disparate invasion phenomena.
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Latombe G, Canavan S, Hirsch H, Hui C, Kumschick S, Nsikani MM, Potgieter LJ, Robinson TB, Saul W, Turner SC, Wilson JRU, Yannelli FA, Richardson DM. A four‐component classification of uncertainties in biological invasions: implications for management. Ecosphere 2019. [DOI: 10.1002/ecs2.2669] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- G. Latombe
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Department of Mathematical Sciences Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - S. Canavan
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Kirstenbosch Research Centre South African National Biodiversity Institute Private Bag X7 Claremont 7735 South Africa
| | - H. Hirsch
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - C. Hui
- Department of Mathematical Sciences Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Mathematical and Physical Biosciences African Institute for Mathematical Sciences Cape Town 7945 South Africa
| | - S. Kumschick
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Kirstenbosch Research Centre South African National Biodiversity Institute Private Bag X7 Claremont 7735 South Africa
| | - M. M. Nsikani
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - L. J. Potgieter
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - T. B. Robinson
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - W.‐C. Saul
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Department of Mathematical Sciences Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - S. C. Turner
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - J. R. U. Wilson
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
- Kirstenbosch Research Centre South African National Biodiversity Institute Private Bag X7 Claremont 7735 South Africa
| | - F. A. Yannelli
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
| | - D. M. Richardson
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Stellenbosch 7602 South Africa
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Latombe G, Richardson DM, Pyšek P, Kučera T, Hui C. Drivers of species turnover vary with species commonness for native and alien plants with different residence times. Ecology 2018; 99:2763-2775. [DOI: 10.1002/ecy.2528] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 08/06/2018] [Accepted: 08/30/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Guillaume Latombe
- Department of Mathematical Sciences Centre for Invasion Biology Stellenbosch University Matieland 7600 South Africa
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Matieland 7600 South Africa
| | - David M. Richardson
- Department of Botany and Zoology Centre for Invasion Biology Stellenbosch University Matieland 7600 South Africa
| | - Petr Pyšek
- Department of Invasion Ecology The Czech Academy of Sciences Institute of Botany CZ‐252 43 Průhonice Czech Republic
- Department of Ecology Faculty of Science Charles University Viničná 7 CZ‐128 44 Praha2 Czech Republic
| | - Tomáš Kučera
- Department of Ecosystem Biology Faculty of Science University of South Bohemia Branišovská 1760, CZ‐370 05 České Budějovice Czech Republic
| | - Cang Hui
- Department of Mathematical Sciences Centre for Invasion Biology Stellenbosch University Matieland 7600 South Africa
- Theoretical Ecology Group African Institute for Mathematical Sciences Cape Town 7945 South Africa
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Nuwagaba S, Zhang F, Hui C. Robustness of rigid and adaptive networks to species loss. PLoS One 2017; 12:e0189086. [PMID: 29216245 PMCID: PMC5720727 DOI: 10.1371/journal.pone.0189086] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2017] [Accepted: 11/18/2017] [Indexed: 11/29/2022] Open
Abstract
Controversies in the complexity-stability debate have been attributed to the methodologies used such as topological vs. dynamical approaches or rigid vs. adaptive foraging behaviour of species. Here, we use a bipartite network model that incorporates both topological and population dynamics to investigate the robustness of 60 real ecological networks to the loss of generalist and specialist species. We compare the response in both adaptive and rigid networks. Our results show that the removal of generalists leads to the most secondary extinctions, implying that conservation strategies should aim to protect generalist species in the ecosystem. We also show that adaptive behaviour renders networks vulnerable to species loss at initial stages but enhances long term stability of the system. However, whether adaptive networks are more robust to species loss than rigid ones depends on the structure of the network. Specifically, adaptive networks with modularity < 0.3 are more robust than rigid networks of the same modularity. Interestingly, the more modular a network is, the less robust it is to external perturbations.
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Affiliation(s)
- Savannah Nuwagaba
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland, South Africa
| | - Feng Zhang
- MOE Key Laboratory for Grassland Ecosystem and Center for Quantitative Biology, Gansu Agricultural University, Lanzhou, China
| | - Cang Hui
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland, South Africa
- Mathematical and Physical Biosciences, African Institute for Mathematical Sciences, Muizenberg, South Africa
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Miller JT, Hui C, Thornhill A, Gallien L, Le Roux JJ, Richardson DM. Is invasion success of Australian trees mediated by their native biogeography, phylogenetic history, or both? AOB PLANTS 2016; 9:plw080. [PMID: 28039115 PMCID: PMC5391713 DOI: 10.1093/aobpla/plw080] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Revised: 08/23/2016] [Accepted: 09/30/2016] [Indexed: 06/06/2023]
Abstract
For a plant species to become invasive it has to progress along the introduction-naturalization-invasion (INI) continuum which reflects the joint direction of niche breadth. Identification of traits that correlate with and drive species invasiveness along the continuum is a major focus of invasion biology. If invasiveness is underlain by heritable traits, and if such traits are phylogenetically conserved, then we would expect non-native species with different introduction status (i.e. position along the INI continuum) to show phylogenetic signal. This study uses two clades that contain a large number of invasive tree species from the genera Acacia and Eucalyptus to test whether geographic distribution and a novel phylogenetic conservation method can predict which species have been introduced, became naturalized, and invasive. Our results suggest that no underlying phylogenetic signal underlie the introduction status for both groups of trees, except for introduced acacias. The more invasive acacia clade contains invasive species that have smoother geographic distributions and are more marginal in the phylogenetic network. The less invasive eucalyptus group contains invasive species that are more clustered geographically, more centrally located in the phylogenetic network and have phylogenetic distances between invasive and non-invasive species that are trending toward the mean pairwise distance. This suggests that highly invasive groups may be identified because they have invasive species with smoother and faster expanding native distributions and are located more to the edges of phylogenetic networks than less invasive groups.
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Affiliation(s)
- Joseph T Miller
- National Research Collections Australia, CSIRO National Facilities and Collections, GPO Box 1600, Canberra, ACT 2601, Australia.
- Office of International Science and Engineering, National Science Foundation, Arlington, Virginia 22230, USA
| | - Cang Hui
- Department of Mathematical Sciences, Centre for Invasion Biology, Stellenbosch University, Matieland 7620, South Africa
- BioMath Group, African Institute for Mathematical A10 Sciences, Cape Town 7652, South Africa
| | - Andrew Thornhill
- University and Jepson Herbaria, and Department of Integrative Biology, University of California, Berkeley, CA 94720-2465, USA
| | - Laure Gallien
- Centre for Invasion Biology, Department of Botany & Zoology, Stellenbosch University, Matieland 7620, South Africa
| | - Johannes J Le Roux
- Centre for Invasion Biology, Department of Botany & Zoology, Stellenbosch University, Matieland 7620, South Africa
| | - David M Richardson
- Centre for Invasion Biology, Department of Botany & Zoology, Stellenbosch University, Matieland 7620, South Africa
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Nuwagaba S, Zhang F, Hui C. A hybrid behavioural rule of adaptation and drift explains the emergent architecture of antagonistic networks. Proc Biol Sci 2016; 282:20150320. [PMID: 25925104 DOI: 10.1098/rspb.2015.0320] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Ecological processes that can realistically account for network architectures are central to our understanding of how species assemble and function in ecosystems. Consumer species are constantly selecting and adjusting which resource species are to be exploited in an antagonistic network. Here we incorporate a hybrid behavioural rule of adaptive interaction switching and random drift into a bipartite network model. Predictions are insensitive to the model parameters and the initial network structures, and agree extremely well with the observed levels of modularity, nestedness and node-degree distributions for 61 real networks. Evolutionary and community assemblage histories only indirectly affect network structure by defining the size and complexity of ecological networks, whereas adaptive interaction switching and random drift carve out the details of network architecture at the faster ecological time scale. The hybrid behavioural rule of both adaptation and drift could well be the key processes for structure emergence in real ecological networks.
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Affiliation(s)
- S Nuwagaba
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland 7602, South Africa
| | - F Zhang
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland 7602, South Africa
| | - C Hui
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland 7602, South Africa Mathematical and Physical Biosciences, African Institute for Mathematical Sciences, Cape Town 7945, South Africa
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Liu Z, Zhang F, Hui C. Density-dependent dispersal complicates spatial synchrony in tri-trophic food chains. POPUL ECOL 2015. [DOI: 10.1007/s10144-015-0515-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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13
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The electronic structure of metal oxide/organo metal halide perovskite junctions in perovskite based solar cells. Sci Rep 2015; 5:8704. [PMID: 25731963 PMCID: PMC4346802 DOI: 10.1038/srep08704] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 02/02/2015] [Indexed: 11/08/2022] Open
Abstract
Cross-sections of a hole-conductor-free CH3NH3PbI3 perovskite solar cell were characterized with Kelvin probe force microscopy. A depletion region width of about 45 nm was determined from the measured potential profiles at the interface between CH3NH3PbI3 and nanocrystalline TiO2, whereas a negligible depletion was measured at the CH3NH3PbI3/Al2O3 interface. A complete solar cell can be realized with the CH3NH3PbI3 that functions both as light harvester and hole conductor in combination with a metal oxide. The band diagrams were estimated from the measured potential profile at the interfaces, and are critical findings for a better understanding and further improvement of perovskite based solar cells.
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Han X, Hui C. Niche construction on environmental gradients: the formation of fitness valley and stratified genotypic distributions. PLoS One 2014; 9:e99775. [PMID: 24915290 PMCID: PMC4051751 DOI: 10.1371/journal.pone.0099775] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Accepted: 05/19/2014] [Indexed: 01/30/2023] Open
Abstract
The process of niche construction can alter the trajectory of natural selection through organism-environment feedback. As such, the mechanism and impact of niche construction can be better investigated along environmental gradients. Here we investigate how the process of niche construction affects the distribution of genotypes and fitness landscape along an environmental gradient under three selection regimes, namely heterozygote superiority, genetic loci which dictates niche construction ability being either selectively neutral or non-neutral. Using a spatially explicit cellular automaton, we show that niche construction can stratify genetic diversity by forming band-like distributions consisting of different genotypic compositions and promote reproduction isolation by forming a divide with reduced average fitness along the gradients, termed a fitness valley. The band structure and the presence of a fitness valley depend on heterogeneous environments, resource-dependent fitness and the selection acting on the gene loci affecting the niche-constructing ability. Our work adds to the growing body of evidence on criticizing species distribution models which assume that the environment alone can determine species distributions. Based on the results, we argue that conservation planning should target preserving or restoring environmental gradients.
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Affiliation(s)
- Xiaozhuo Han
- School of Applied Mathematics, Guangdong University of Technology, Tianhe District, Guangzhou, China
| | - Cang Hui
- Centre for Invasion Biology, Department of Mathematical Sciences, University of Stellenbosch, Matieland, South Africa
- Mathematical and Physical Biosciences, African Institute for Mathematical Sciences, Muizenberg, South Africa
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Donaldson JE, Hui C, Richardson DM, Robertson MP, Webber BL, Wilson JRU. Invasion trajectory of alien trees: the role of introduction pathway and planting history. GLOBAL CHANGE BIOLOGY 2014; 20:1527-37. [PMID: 24343918 DOI: 10.1111/gcb.12486] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 11/19/2013] [Indexed: 05/24/2023]
Abstract
Global change is driving a massive rearrangement of the world's biota. Trajectories of distributional shifts are shaped by species traits, the recipient environment and driving forces with many of the driving forces directly due to human activities. The relative importance of each in determining the distributions of introduced species is poorly understood. We consider 11 Australian Acacia species introduced to South Africa for different reasons (commercial forestry, dune stabilization and ornamentation) to determine how features of the introduction pathway have shaped their invasion history. Projections from species distribution models (SDMs) were developed to assess how the reason for introduction influences the similarity between climatic envelopes in native and alien ranges. A lattice model for an idealized invasion was developed to assess the relative contribution of intrinsic traits and introduction dynamics on the abundance and extent over the course of simulated invasions. SDMs show that alien populations of ornamental species in South Africa occupy substantially different climate space from their native ranges, whereas species introduced for forestry occupy a similar climate space in native and introduced ranges. This may partly explain the slow spread rates observed for some alien ornamental plants. Such mismatches are likely to become less pronounced with the current drive towards 'eco gardens' resulting in more introductions of ornamental species with a close climate match between native and newly introduced regions. The results from the lattice model showed that the conditions associated with the introduction pathway (especially introduction pressure) dominate early invasion dynamics. The placement of introduction foci in urban areas limited the extent and abundance of invasive populations. Features of introduction events appear to initially mask the influence of intrinsic species traits on invasions and help to explain the relative success of species introduced for different purposes. Introduction dynamics therefore can have long-lasting influences on the outcomes of species redistributions, and must be explicitly considered in management plans.
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Affiliation(s)
- Jason E Donaldson
- Department of Botany and Zoology, Centre for Invasion Biology, Stellenbosch University, Matieland, 7602, South Africa
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Minoarivelo HO, Hui C, Terblanche JS, Pond SLK, Scheffler K. Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model. OIKOS 2014; 123:1250-1260. [PMID: 25294947 DOI: 10.1111/oik.00857] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant - pollinator and plant - frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.
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Affiliation(s)
- H O Minoarivelo
- H. O. Minoarivelo and K. Scheffler ( ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa
| | - C Hui
- H. O. Minoarivelo and K. Scheffler ( ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa
| | - J S Terblanche
- H. O. Minoarivelo and K. Scheffler ( ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa
| | - S L Kosakovsky Pond
- H. O. Minoarivelo and K. Scheffler ( ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa
| | - K Scheffler
- H. O. Minoarivelo and K. Scheffler ( ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa
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Gaertner M, Biggs R, Te Beest M, Hui C, Molofsky J, Richardson DM. Invasive plants as drivers of regime shifts: identifying high-priority invaders that alter feedback relationships. DIVERS DISTRIB 2014. [DOI: 10.1111/ddi.12182] [Citation(s) in RCA: 180] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Affiliation(s)
- Mirijam Gaertner
- Centre for Invasion Biology; Department of Botany and Zoology; Stellenbosch University; Private Bag X1 Matieland 7602 South Africa
- Environmental Resource Management Department (ERMD); Westlake Conservation Office; City of Cape Town Ou Kaapse Weg Tokai 7966 Cape Town South Africa
| | - Reinette Biggs
- Stockholm Resilience Centre; Stockholm University; SE 106 91 Stockholm Sweden
- Stellenbosch Institute for Advanced Study (STIAS); Wallenberg Research Centre at Stellenbosch University; Marais Street Stellenbosch 7600 South Africa
- Centre for Studies in Complexity; Stellenbosch University; Private Bag X1 Matieland 7602 South Africa
| | - Mariska Te Beest
- Department of Ecology and Environmental Science; Umeå University; SE 901 87 Umeå Sweden
- Department of Conservation Ecology and Entomology and Centre for Invasion Biology; Department of Botany and Zoology; Stellenbosch University; Private Bag X1 Matieland 7602 South Africa
| | - Cang Hui
- Centre for Invasion Biology; Department of Botany and Zoology; Stellenbosch University; Private Bag X1 Matieland 7602 South Africa
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University; Matieland 7602, South Africa; African Institute for Mathematical Sciences; Muizenberg 7945 VT South Africa
| | - Jane Molofsky
- Department of Plant Biology; University of Vermont; Burlington VT 05405 USA
| | - David M. Richardson
- Centre for Invasion Biology; Department of Botany and Zoology; Stellenbosch University; Private Bag X1 Matieland 7602 South Africa
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Singh SK, Paini DR, Ash GJ, Hodda M. Prioritising plant-parasitic nematode species biosecurity risks using self organising maps. Biol Invasions 2013. [DOI: 10.1007/s10530-013-0588-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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