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Both processes integrate individual responses to the abiotic environment and biotic interactions. Thus, it is difficult to clearly identify the underlying abiotic and biotic factors that ultimately impact community structure by looking at community‐level patterns of trait divergence or convergence alone.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>We used a functional trait‐based and multiscale approach to assess how biotic interactions and aridity determine the functional structure of semi‐arid shrublands sampled along a large aridity gradient in \u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>pain. At the regional scale, we investigated functional differences among species (axes of specialization) to identify important traits for community assembly. At the community scale, we evaluated the relative impact of \u003Cjats:styled-content style=\"fixed-case\">HF\u003C\u002Fjats:styled-content> and \u003Cjats:styled-content style=\"fixed-case\">ND\u003C\u002Fjats:styled-content> on community structure using a null model approach. Finally, at the plant neighbourhood scale, we evaluated the impact of biotic interactions on community structure by investigating the spatial patterns of trait aggregation.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>The shrub species surveyed can be separated along four axes of specialization based on their above‐ground architecture and leaf morphology. Our community scale analysis suggested that the functional structure of semi‐arid communities was clearly non‐random, \u003Cjats:styled-content style=\"fixed-case\">HF\u003C\u002Fjats:styled-content> and \u003Cjats:styled-content style=\"fixed-case\">ND\u003C\u002Fjats:styled-content> acting independently on different traits to determine community structure along the aridity gradient. At the plant neighbourhood scale, the spatial distribution of species was also clearly not random, suggesting that competition and facilitation impacted on the observed changes in the functional diversity of shrubland communities along the aridity gradient.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>: Our results demonstrated that \u003Cjats:styled-content style=\"fixed-case\">HF\u003C\u002Fjats:styled-content> and \u003Cjats:styled-content style=\"fixed-case\">ND\u003C\u002Fjats:styled-content> acted simultaneously on independent traits to jointly determine community structure. Most importantly, our multiscale approach suggested that competition and facilitation interplayed with aridity to determine this structure. Competition appeared to be constant along the aridity gradient and explained the high functional diversity observed in semi‐arid shrublands. 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This focus ignores the importance of other assembly processes such as equalizing fitness processes and facilitation. The contribution of different processes to community assembly can be elucidated by examining functional diversity patterns of traits that differ in their contribution to different assembly processes.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>2.\u003C\u002Fjats:bold> In alpine tundra, we explored trait patterns along a stress–resource gradient that varied in productivity, nitrogen availability and soil moisture. We explore whether functional diversity is low in abiotic stressful environments and increases in more benign environments as competition becomes more important, and if equalizing fitness processes and facilitation affect functional diversity. We calculated community‐weighted mean trait values and functional diversity for specific leaf area (SLA), leaf area, stomatal conductance, plant height and chlorophyll content as well as multivariate functional diversity and phylogenetic diversity.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>3.\u003C\u002Fjats:bold> At the community level, functional diversity increased at both ends of the gradient: high resource availability was associated with greater functional diversity in height and leaf area, and lower resource availability was associated with greater functional diversity in SLA, stomatal conductance, and chlorophyll content. As a result of this trade‐off in functional diversity among traits, multivariate functional diversity did not change across the gradient. Phylogenetic diversity increased with increasing resource availability.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>4.\u003C\u002Fjats:bold> We find evidence for at least three assembly processes along the gradient. Abiotic filtering by wind and cold exposure may reduce functional diversity in height and leaf area at the low resource end of the gradient. Also at low resource availability, increasing functional diversity in the other three traits suggests competition for below‐ground resources. At the resource‐rich end of the gradient, increased functional diversity in height and leaf area suggests increased competition for light or facilitation.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>5.\u003C\u002Fjats:bold>\n          \u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>: Our results suggest that multiple assembly processes (abiotic filtering, above‐ground competition, and below‐ground competition) operate simultaneously to structure plant communities along a stress–resource gradient. These processes would be obscured by a single multivariate trait index or phylogenetic diversity and are only evident by analysing functional diversity patterns of individual traits.\u003C\u002Fjats:p>",{"EN":880},"Inferring community assembly mechanisms from functional diversity patterns: the importance of multiple assembly processes",{"VOID":822},[242],"https:\u002F\u002Fbesjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.1365-2745.2011.01945.x",[885,916],{"id":886,"sortIndex":25,"researcher":24,"roles":887,"affiliations":888,"properties":909},"66a68b64-a7d4-4e4f-8324-ebe380ae61db",[],[889,899],{"id":890,"sortIndex":133,"affiliation":891,"properties":24},"82b7f3fe-8435-4a75-b2e7-a5a288543d2a",{"id":892,"createTime":893,"updateTime":893,"relativeEntities":894,"slug":895,"properties":896,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"69fe9d9e-d5a4-42d2-91fb-c1efc4536541","2024-10-06T23:48:23.455+00:00",[],"Present-address-Department-of-Environmental-Science-and-Policy-3132-Wickson-Hall-University-of-California-Davis-Davis-CA-95616-USA-",{"title":897},{"EN":898},"Present address: Department of Environmental Science and Policy, 3132 Wickson Hall, University of California Davis, Davis, CA 95616, USA.",{"id":900,"sortIndex":25,"affiliation":901,"properties":24},"323a28a7-942e-4fb8-9ed1-783cdeb05e8e",{"id":902,"createTime":903,"updateTime":903,"relativeEntities":904,"slug":905,"properties":906,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"9cbd275f-47a8-4eb2-a3aa-131fb517752a","2024-10-06T23:48:23.449+00:00",[],"Department-of-Ecology-and-Evolutionary-Biology-321-Steinhaus-Hall-University-of-California-Irvine-Irvine-CA-92697-USA",{"title":907},{"EN":908},"Department of Ecology and Evolutionary Biology, 321 Steinhaus Hall, University of California Irvine, Irvine, CA 92697, USA",{"openalex":910,"orcid":912,"title":914},{"VOID":911},"A5071778816",{"VOID":913},"https:\u002F\u002Forcid.org\u002F0000-0003-1808-0048",{"EN":915},"Marko J. 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However, fundamental gaps remain in our understanding of how \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> contributes to mechanisms that create spatial variation in the functional‐trait composition of communities (functional β‐diversity). Importantly, \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> may influence the perceived importance of environmental filtering across spatial scales.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>We examined how \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> contributes to functional β‐diversity and environmental filtering in woody plant communities in a temperate forest in the Ozark ecoregion, Missouri, \u003Cjats:styled-content style=\"fixed-case\">USA\u003C\u002Fjats:styled-content>. To test the hypothesis that \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> contributes to changes in the perceived importance of environmental filtering across scales, we compared patterns of functional β‐diversity across soil‐resource and topographic gradients at three spatial grains and three spatial extents. To quantify the contribution of \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> to functional β‐diversity, we compared patterns that included \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> in five traits (leaf area, specific leaf area, leaf water content, leaf toughness and chlorophyll content) to patterns based on species‐mean trait values.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>Functional β‐diversity that included \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> increased with spatial extent and decreased with spatial grain, suggesting stronger environmental filtering within spatially extensive landscapes that contain populations locally adapted to different habitats. In contrast, functional β‐diversity based on species‐mean trait values increased with spatial extent but did not change with spatial grain, suggesting weaker environmental filtering among larger communities which each contain a variety of habitats and locally adapted populations.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>. Although studies typically infer community assembly mechanisms from species‐mean trait values, our study suggests that mean trait values may mask the strength of assembly mechanisms such as environmental filtering, especially in landscape‐scale studies that encompass strong environmental gradients and locally adapted populations. Our study highlights the utility of integrating \u003Cjats:styled-content style=\"fixed-case\">ITV\u003C\u002Fjats:styled-content> into studies of functional β‐diversity to better understand the ecological conditions under which trait variation within and among species contributes most strongly to patterns of biodiversity across spatial scales.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\n\u003C\u002Fjats:p>",{"EN":1218},"When does intraspecific trait variation contribute to functional beta‐diversity?",{"VOID":1220},"10.1111\u002F1365-2745.12518",[242],"https:\u002F\u002Fbesjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002F1365-2745.12518",[1224,1245,1267],{"id":1225,"sortIndex":134,"researcher":24,"roles":1226,"affiliations":1227,"properties":1238},"2b0b1cd4-4281-4980-b023-a93633c234b8",[],[1228],{"id":1229,"sortIndex":25,"affiliation":1230,"properties":24},"d31ac2da-9af2-40c5-95f9-d6496a7c7cc7",{"id":1231,"createTime":1232,"updateTime":1232,"relativeEntities":1233,"slug":1234,"properties":1235,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"25bceb13-0eb7-444b-bb7f-3d87b3cc661b","2024-10-06T23:48:04.100+00:00",[],"Department-of-Biology-and-Tyson-Research-Center-Washington-University-in-St-Louis-St-Louis-MO-63130-USA",{"title":1236},{"EN":1237},"Department of Biology and Tyson Research Center, Washington University in St. Louis, St. Louis, MO, 63130 USA",{"openalex":1239,"orcid":1241,"title":1243},{"VOID":1240},"A5061131967",{"VOID":1242},"https:\u002F\u002Forcid.org\u002F0000-0002-2058-8468",{"EN":1244},"Jonathan A. 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Casper 2007 Ecological Society of America San Jose CA",{},{"id":24,"text":2644,"url":24,"identifiers":2645},"10.1111\u002Fj.1365-2745.2009.01635.x",{"doi":2644},{"id":24,"text":2647,"url":24,"identifiers":2648},"10.1086\u002F657044",{"doi":2647},{"id":24,"text":2650,"url":24,"identifiers":2651},"10.1098\u002Frstb.2012.0074",{"doi":2650},{"id":24,"text":2653,"url":24,"identifiers":2654},"10.2307\u002F2258962",{"doi":2653},{"id":24,"text":2656,"url":24,"identifiers":2657},"10.1016\u002FS0169-5347(98)01381-0",{"doi":2656},{"id":24,"text":2659,"url":24,"identifiers":2660},"10.1111\u002Fj.1442-1984.2007.00190.x",{"doi":2659},{"id":24,"text":2662,"url":24,"identifiers":2663},"10.1890\u002F12-1712.1",{"doi":2662},{"id":24,"text":2665,"url":24,"identifiers":2666},"10.2307\u002F2260717",{"doi":2665},{"id":24,"text":2668,"url":24,"identifiers":2669},"Silvertown J., 1997, Plant Life Histories: Ecology, Phylogeny and Evolution",{},{"id":24,"text":2671,"url":24,"identifiers":2672},"10.2307\u002F2389746",{"doi":2671},{"id":24,"text":2674,"url":24,"identifiers":2675},"Silvertown J., 2001, Evolution of senescence in iteroparous perennial plants, Evolutionary Ecology Research, 3, 393",{},{"id":24,"text":2677,"url":24,"identifiers":2678},"10.1046\u002Fj.1523-1739.1996.10020591.x",{"doi":2677},{"id":24,"text":2680,"url":24,"identifiers":2681},"10.2307\u002F2261525",{"doi":2680},{"id":24,"text":2683,"url":24,"identifiers":2684},"10.1890\u002F04-0434",{"doi":2683},{"id":24,"text":2686,"url":24,"identifiers":2687},"10.1111\u002Fj.1472-4642.2007.00398.x",{"doi":2686},{"id":24,"text":2689,"url":24,"identifiers":2690},"10.1111\u002Fj.2041-210X.2012.00222.x",{"doi":2689},{"id":24,"text":2692,"url":24,"identifiers":2693},"10.1111\u002Fj.1461-0248.2011.01659.x",{"doi":2692},{"id":24,"text":2695,"url":24,"identifiers":2696},"10.1111\u002Fj.1365-2745.2009.01632.x",{"doi":2695},{"id":24,"text":2698,"url":24,"identifiers":2699},"10.18637\u002Fjss.v022.i11",{"doi":2698},{"id":24,"text":2701,"url":24,"identifiers":2702},"10.1016\u002Fj.biocon.2007.06.011",{"doi":2701},{"id":24,"text":2704,"url":24,"identifiers":2705},"10.1007\u002F978-3-642-51652-8",{"doi":2704},{"id":24,"text":2707,"url":24,"identifiers":2708},"Tuljapurkar S., 1996, Structured‐Population Models in Marine, Terrestrial and Freshwater Systems",{},{"id":24,"text":2710,"url":24,"identifiers":2711},"10.1890\u002F0012-9658(2006)87[1497:FSTAIV]2.0.CO;2",{"doi":2710},{"id":24,"text":2713,"url":24,"identifiers":2714},"10.2307\u002F2401258",{"doi":2713},{"id":24,"text":2716,"url":24,"identifiers":2717},"10.1038\u002F487285a",{"doi":2716},{"id":24,"text":2719,"url":24,"identifiers":2720},"10.1007\u002FBF00344691",{"doi":2719},{"id":24,"text":2722,"url":24,"identifiers":2723},"10.1007\u002Fs11538-008-9312-7",{"doi":2722},{"id":24,"text":2725,"url":24,"identifiers":2726},"10.1007\u002FBF00347472",{"doi":2725},{"id":24,"text":2728,"url":24,"identifiers":2729},"10.2307\u002F1936930",{"doi":2728},{"id":24,"text":2731,"url":24,"identifiers":2732},"10.1111\u002Fj.1365-2745.2006.01209.x",{"doi":2731},{"id":24,"text":2734,"url":24,"identifiers":2735},"10.1111\u002Fcobi.12130",{"doi":2734},{"id":2737,"createTime":2738,"updateTime":2738,"relativeEntities":2739,"slug":2740,"properties":2741,"entityType":239,"verifyStatus":389,"verifyTime":2753,"verifyNote":391,"syncStatus":23,"languages":2754,"translateLanguages":24,"viewCount":25,"primaryUrl":2755,"fullTextUrl":24,"authors":2756,"publicationType":254,"publisherRelationship":2907,"citationCount":2944,"citationInfo":2945,"publishDate":2947,"publishYear":612,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":2948,"isForceReanalyzing":298},"fa180e14-2453-4f0c-9a4e-0db92a9dfb0b","2024-10-06T23:47:29.033+00:00",[],"Evidence-for-scale-and-disturbance-dependent-trait-assembly-patterns-in-dry-semi-natural-grasslands",{"mag":2742,"keywords":2744,"openalex":2745,"abstract":2747,"title":2749,"doi":2751},{"VOID":2743},"2002869208",{},{"VOID":2746},"W2002869208",{"EN":2748},"\u003Cjats:title>Summary\u003C\u002Fjats:title>\u003Cjats:p>\n\u003Cjats:list>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:bold> \u003C\u002Fjats:bold>The mechanisms driving nonrandom assembly patterns in plant communities have long been of interest in ecological research. Competing ecological theories predict that coexisting species may either be more functionally dissimilar than expected by chance (with functional ‘divergence’ mainly reflecting niche differentiation) or be functionally more similar than expected (with functional ‘convergence’ reflecting either the outcome of environmental filtering or weaker‐competitor exclusion effects). Assembly patterns are usually assessed at a single scale and disturbance regime, whereas considering different spatial scales and disturbance regimes may clarify the underlying assembly mechanisms.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:bold> \u003C\u002Fjats:bold>We tested the prediction that convergence and divergence are scale‐ and disturbance‐ dependent in grazed and abandoned species‐rich dry grasslands within a 22 km\u003Cjats:sup>2\u003C\u002Fjats:sup> landscape in south‐eastern Sweden. Convergence and divergence were tested for plant species' traits and phylogenetic relationships at three nested spatial scales: within 412 plots (50 × 50 cm, divided into 10 × 10 cm subplots), within 117 grassland patches (from 0.02 to 11.63 ha) and within the whole landscape (across patches).\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:bold> \u003C\u002Fjats:bold>At the finest scale (10 × 10 cm subplots within plots), coexisting species were more different than expected by chance (divergence), both functionally and phylogenetically, suggesting niche differentiation. At the intermediate scale (50 × 50 cm plots within patches), coexisting species showed convergence, suggesting environmental filtering. No significant deviations from random expectations were detected at the broadest scale (patches within the 22 km\u003Cjats:sup>2\u003C\u002Fjats:sup> landscape) – suggesting the prevalence of dispersal limitation at this scale. The fact that nonrandom patterns were particularly evident under grazed conditions is consistent with the prediction that assembly patterns are disturbance dependent.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:bold> \u003C\u002Fjats:bold>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>. This study shows that multiple trait‐based assembly processes operate simultaneously in species‐rich communities, across spatial scales and disturbance regimes. The results support earlier theoretical predictions that divergence between coexisting species may be an important driver of community assembly, particularly at finer spatial scales, where species compete for the same local resources. In contrast, environmental filtering is expected at broader spatial scales, where species growing in particular environmental conditions share traits that are adaptive under those conditions. Within given habitat types, dispersal limitation may, however, override environmental filtering at increasing spatial scales of observation.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\n\u003C\u002Fjats:p>",{"EN":2750},"Evidence for scale‐ and disturbance‐dependent trait assembly patterns in dry semi‐natural grasslands",{"VOID":2752},"10.1111\u002F1365-2745.12139","2024-10-06T23:47:29.032+00:00",[242],"https:\u002F\u002Fbesjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002F1365-2745.12139",[2757,2779,2799,2831,2852,2869,2886],{"id":2758,"sortIndex":134,"researcher":24,"roles":2759,"affiliations":2760,"properties":2772},"02f40179-155c-4542-b62a-39e24b26810c",[],[2761],{"id":2762,"sortIndex":25,"affiliation":2763,"properties":24},"dacd383e-bd4c-45ce-b51a-a532d57208cf",{"id":2764,"createTime":2765,"updateTime":2766,"relativeEntities":2767,"slug":2768,"properties":2769,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"a1399dd6-4fa1-42be-ac94-531decbdc9d8","2024-01-28T07:05:28.674+00:00","2024-10-06T23:47:29.082+00:00",[],"Institute-of-Geology-Tallinn-University-of-Technology-Ehitajate-tee-5-Tallinn-19086-Estonia",{"title":2770},{"VI":2771},"Institute of Geology, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia",{"openalex":2773,"orcid":2775,"title":2777},{"VOID":2774},"A5040992840",{"VOID":2776},"https:\u002F\u002Forcid.org\u002F0000-0002-6555-3066",{"EN":2778},"Triin Reitalu",{"id":2780,"sortIndex":72,"researcher":24,"roles":2781,"affiliations":2782,"properties":2794},"226eadeb-4984-4c44-bde8-4006b9c9b059",[],[2783],{"id":2784,"sortIndex":25,"affiliation":2785,"properties":24},"3243b5d3-c3e4-4b60-b42f-414c1ed53f81",{"id":2786,"createTime":2787,"updateTime":2788,"relativeEntities":2789,"slug":2790,"properties":2791,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"57d05eda-f2f6-4f5e-9a59-05bc21b4266f","2024-09-24T21:09:12.280+00:00","2024-10-06T23:47:29.070+00:00",[],"Department-of-Physical-Geography-and-Ecosystem-Science-Lund-University-S%C3%B6lvegatan-12-SE-223-62-Lund-Sweden",{"title":2792},{"EN":2793},"Department of Physical Geography and Ecosystem Science Lund University Sölvegatan 12 SE‐223 62 Lund Sweden",{"openalex":2795,"title":2797},{"VOID":2796},"A5065190097",{"EN":2798},"Martin T. 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of grassland communities has long been scrutinized through the lens of functional diversity. Studies generally point to an overwhelming influence of climate on observed patterns of functional diversity, despite experimental evidence demonstrating the importance of biotic interactions. We postulate that this is because most observational studies neglect both scale dependencies of assembly processes and phenotypic variation between individuals. Here, we test for changes in the importance of abiotic filtering and biotic interactions along a stress gradient by explicitly accounting for different scales. In addition to quantifying intraspecific trait variability (ITV), we also vary the two components of spatial scale, including grain (i.e. community size) and extent (i.e. the geographical area that defines the species pool).\u003C\u002Fjats:p>\n\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\n\u003Cjats:p>We sampled 20 grassland communities in ten sites distributed along a 975‐m elevation gradient. At each site, we measured seven functional traits for a total of 2020 individuals at different spatial grains. We related community functional diversity metrics to the main environmental gradient of our study area, growing season length (GSL), and assessed the dependence of these relationships on spatial grain, spatial extent and ITV.\u003C\u002Fjats:p>\n\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\n\u003Cjats:p>At large spatial grain and extent, the imprint of environmental filtering on functional diversity became more important with increasing stress (i.e. functional diversity decreased with shorter GSL). At small spatial grain and extent, we found a convex relationship between functional diversity and GSL congruent with the hypothesis that competition is dominant at low‐stress levels while facilitative interactions are dominant at high‐stress levels (i.e. high functional diversity at both extremes of the stress gradient). Importantly, the effect of intraspecific variability on assembly rules was noticeable only at small spatial grain and extent.\u003C\u002Fjats:p>\n\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\n\u003Cjats:p>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>. Our study reveals how the combination of abiotic stress and biotic interactions shapes the functional diversity of alpine grasslands at different spatial scales, and highlights the importance of phenotype variation between individuals for community assembly processes at fine spatial scale. 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Marchon J. Praverdand J.‐N. Bilat J. Guisan A. Rasmann S.&Pellissier L.(2016)Community‐level plant palatability increases with elevation as insect herbivore abundance declines. 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Bates D. DebRoy S.&Sarkar D.(2007)Linear and nonlinear mixed effects models. 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Appropriately representing functional composition is therefore essential for predicting the consequences of environmental context and management actions for the provisioning of multiple ecosystem services (\u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s) in heterogeneous landscapes.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>Functional indices can be constructed from single or multiple traits; however, it is not clear how they differ in information content or ability to predict biodiversity – ecosystem function relationships in complex landscapes. Here, we compare the utility of analogous single‐ and multi‐trait indices in linking environmental variation and functional composition to \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s in a heterogeneous landscape, relating functional indices based on three plant traits [height, relative growth rate and root density (\u003Cjats:styled-content style=\"fixed-case\">RD\u003C\u002Fjats:styled-content>)] to variation in the physical environment and to two \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s (forage production and soil carbon) and their net \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content> level.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>Two orthogonal gradients, elevation and soil bulk density (\u003Cjats:styled-content style=\"fixed-case\">BD\u003C\u002Fjats:styled-content>), explained significant variation in several dimensions of functional composition comprised of single traits. These traits in turn significantly predicted variation in \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s and their net values. Only one index measured with multiple traits (functional richness) varied with the physical environment, while none predicted variation in \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content> or net \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content> levels.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>One \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>, soil carbon, increased with the community‐average value of \u003Cjats:styled-content style=\"fixed-case\">RD\u003C\u002Fjats:styled-content>, while the other, forage production, was related to the range and community‐average value of height. In turn, average \u003Cjats:styled-content style=\"fixed-case\">RD\u003C\u002Fjats:styled-content> increased with soil \u003Cjats:styled-content style=\"fixed-case\">BD\u003C\u002Fjats:styled-content> while the average and range of height declined with elevation. Due to these environmental patterns, soil carbon and forage production did not covary strongly, leading to moderate net \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content> levels across the landscape.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>: Single‐trait indices of functional composition best linked variation in environmental gradients with productivity and soil carbon. Because the environment–trait functioning relationships were independent of one another, the \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s were independently distributed across the landscape, providing little evidence of synergies or trade‐offs. Single‐ and multi‐trait indices contained unique information about functional composition of these communities, and both are likely to have a place in predicting variation in \u003Cjats:styled-content style=\"fixed-case\">ES\u003C\u002Fjats:styled-content>s under different scenarios.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\n\u003C\u002Fjats:p>",{"EN":3648},"Single‐trait functional indices outperform multi‐trait indices in linking environmental gradients and ecosystem services in a complex landscape",{"VOID":3650},"10.1111\u002F1365-2745.12013",[242],"https:\u002F\u002Fbesjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002F1365-2745.12013",[3654,3675],{"id":3655,"sortIndex":25,"researcher":24,"roles":3656,"affiliations":3657,"properties":3668},"bfc44d63-4928-4aaa-b5c7-4f491a52f26c",[],[3658],{"id":3659,"sortIndex":25,"affiliation":3660,"properties":24},"31bafdce-a90a-432a-ba99-6a1bdd99021e",{"id":3661,"createTime":3662,"updateTime":3662,"relativeEntities":3663,"slug":3664,"properties":3665,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"7f0c1ad9-0476-4d3c-9ec6-d24b02a60800","2024-10-06T23:47:23.166+00:00",[],"Department-of-Environmental-Science-Policy-and-Management-University-of-California-Berkeley-137-Mulford-Hall-3144-Berkeley-CA-94720-USA",{"title":3666},{"EN":3667},"Department of Environmental Science, Policy and Management University of California Berkeley 137 Mulford Hall #3144 Berkeley CA 94720 USA",{"openalex":3669,"orcid":3671,"title":3673},{"VOID":3670},"A5060131828",{"VOID":3672},"https:\u002F\u002Forcid.org\u002F0000-0003-0974-9811",{"EN":3674},"Bradley J. 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ecosystems are highly sensitive to not only precipitation amount, but also precipitation pattern, particularly variability in the size and timing of growing season rainfall events. Both rainfall event size and timing are expected to be altered by climate change, but the relative responses of dryland ecosystems to changes in rainfall event size versus timing have not been resolved. Here, we disentangle the effects of these different aspects of precipitation pattern on ecosystem dynamics.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>We experimentally assessed how these two aspects of rainfall variability impacted a semi‐arid grassland ecosystem by altering an ambient precipitation pattern to eliminate variability in (a) rainfall event size (all events were made the same size), (b) rainfall event timing (all events were uniformly spaced in time) and (c) both. Total precipitation amount was constant for all treatments. We measured responses of soil moisture, ecosystem carbon flux (e.g. net primary production and soil CO\u003Cjats:sub>2\u003C\u002Fjats:sub> flux), plant community composition and physiological responses of the dominant C\u003Cjats:sub>4\u003C\u002Fjats:sub> grass, \u003Cjats:italic>Bouteloua gracilis\u003C\u002Fjats:italic>.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>Removing variability in rainfall event size altered ecosystem dynamics more than a pattern of uniform event timing, but the largest impact occurred when variability in both were removed. Notably, eliminating variability in both event size and timing increased above‐ground net primary productivity by 23%, consistent with reduced water stress in the dominant C\u003Cjats:sub>4\u003C\u002Fjats:sub> grass, while also reducing seasonal variability in soil CO\u003Cjats:sub>2\u003C\u002Fjats:sub> flux by 35%, reflecting lower seasonal variability in soil moisture.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\n\u003Cjats:list-item>\u003Cjats:p>\u003Cjats:italic>Synthesis\u003C\u002Fjats:italic>. Unique responses to different aspects of precipitation variability highlight the complexity of predicting how dryland ecosystems will be affected by climate change‐induced shifts in rainfall patterns. Our results provide novel support for the key roles of rainfall event size and timing, in addition to total precipitation amount, as determinants of ecosystem function.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\n\u003C\u002Fjats:p>",{"EN":3896},"Deconstructing precipitation variability: Rainfall event size and timing uniquely alter ecosystem dynamics",{"VOID":3898},"10.1111\u002F1365-2745.13724",[242],"https:\u002F\u002Fbesjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002F1365-2745.13724",[3902,3923,3951],{"id":3903,"sortIndex":133,"researcher":24,"roles":3904,"affiliations":3905,"properties":3916},"5d880aec-fdd1-49bc-a625-1cddf8f915ef",[],[3906],{"id":3907,"sortIndex":25,"affiliation":3908,"properties":24},"50c96540-4a81-49ea-a346-8bfbfc2e1e3a",{"id":3909,"createTime":3910,"updateTime":3910,"relativeEntities":3911,"slug":3912,"properties":3913,"entityType":61,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"77ac61ad-4a0c-488d-bb40-d5c903c0d770","2024-09-04T23:36:46.886+00:00",[],"Graduate-Degree-Program-in-Ecology-and-Department-of-Biology-Colorado-State-University-Fort-Collins-CO-USA",{"title":3914},{"EN":3915},"Graduate Degree Program in Ecology and Department of Biology Colorado State University Fort Collins CO USA",{"openalex":3917,"orcid":3919,"title":3921},{"VOID":3918},"A5067667884",{"VOID":3920},"https:\u002F\u002Forcid.org\u002F0000-0002-7707-3246",{"EN":3922},"Ingrid J. 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