A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties

Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

Functional homogenization of bumblebee communities in alpine landscapes under projected climate change

Background: Bumblebees represent an active pollinator group in mountain regions and assure the pollination of many different plant species from low to high elevations. Plant-pollinator interactions are mediated by functional traits. Shift in bumblebee functional structure under climate change may impact plant-pollinator interactions in mountains. Here, we estimated bumblebee upward shift in elevation, community turnover, and change in functional structure under climate change. Method: We sampled bumblebee species at 149 sites along the elevation gradient. We used stacked species distribution models (S-SDMs) forecasted under three climate change scenarios (A2, A1B, RCP3PD) to model the potential distribution of the Bombus species. Furthermore, we used species proboscis length measurements to assess the functional change in bumblebee assemblages along the elevation gradient. Results: We found species-specific response of bumblebee species to climate change. Species differed in their predicted rate of range contraction and expansion. Losers were mainly species currently restricted to high elevation. Under the most severe climate change scenarios (A2), we found a homogenization of proboscis length structure in bumblebee communities along the elevation gradient through the upward colonization of high elevation by species with longer proboscides. Conclusions: Here, we show that in addition to causing the shift in the distribution of bumblebee species, climate change may impact the functional structure of communities. The colonization of high elevation areas by bumblebee species with long proboscides may modify the structure of plant-pollination interaction networks by increasing the diversity of pollination services at high elevation.

Do stacked species distribution models reflect altitudinal diversity patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.

Spatiotemporal variability in radial growth of trees in the Central Pyrenees: climatic and site influences.

To understand how tree growth has responded to recent climate warming, an understanding of the tree-climate-site complex is necessary. To achieve this, radial growth variability among 204 trees established before 1850 was studied in relation to both climatic and site factors. Seventeen forest stands were sampled in the Spanish Central Pyrenees. Three species were studied: Pinus uncinata, Abies alba, and Pinus sylvestris. For each tree, a ring-width residual chronology was built. All trees cross-dated well, indicating a common influence of the regional climate. For the 1952-1993 period, the radial growth of all species, especially P. uncinata, was positively correlated with warm Novembers during the year before ring formation and warm Mays of the year the annual ring formed. Differences in species-stand elevation modulated the growth-climate associations. Radial growth in P. uncinata at high elevation sites was reduced when May temperatures were colder and May precipitation more abundant. In the 20th century, two contrasting periods in radial growth were observed: one (1900-1949) with low frequency of narrow and wide rings, low mean annual sensitivity, and low common growth variation; and another (1950-1994) with the reverse characteristics. The increased variability in radial growth since the 1950s was observed for all species and sites, which suggests a climatic cause. The low shared variance among tree chronologies during the first half of the 20th century may result from a"relaxation" of the elevation gradient, allowing local site conditions to dominate macroclimatic influence. These temporal trends may be related to the recently reported increase of climatic variability and warmer conditions. This study emphasizes the need to carefully assess the relationships between radial growth and site conditions along ecological gradients to improve dendroclimatic reconstructions.

The role of geography and ecology in shaping repeated patterns of morphological and genetic differentiation between European minnows (Phoxinus phoxinus) from the Pyrenees and the Alps

Neutral and selective processes c an drive repeated patterns of evolu tion in dif ferent groups of populationsexp eriencing similar ecol ogica l gradients. In this paper, we used a combinat ion of nucl ear and mitochondrialDNA markers, as well as geometric morphometrics, to investigate repeated patterns of morphological andgenetic divergence of E uropean minnows in two mountain ranges : the Pyrenees and the Al ps. Europeanminnows (Phoxinus phoxinus) are cyprinid fish i nha bitin g most freshwater bodies in Europe, including those indifferent mountain r anges that could act as major geographical barriers to gene flow. We explored patterns ofP. phoxinus phenotypic and genetic di versi fication along a gradi ent of alti tude common to the two mountainranges, and tested for isolation by distance (IBD), isolation by environment (IBE) and isolation by adaptation(IBA). The results indicated that populations from the Pyr enees a nd the Alps bel ong to two well differentiated,reciprocally monophyletic mt DNA lineages. Substantial genetic differentiation due to geographical isolationwithin and between populations from the Pyrenees and the Alps was also found using rapidly evolving AFLPsmarkers (isolation by distance or IBD), as well as morphological differences between mountain ranges. Als o,morphology varied strong ly with elevation and so did genetic differentiation to a lower extent. Despitemoderate evidence for IBE and IBA, and therefore of repeated evolution, substantial population heterogeneitywas found at the genetic level, suggesting that selection and population specific genetic drift act in concert toaffect genetic divergence.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Environmental influence on the phenotype of ant workers revealed by common garden experiment

Many organism traits vary along environmental gradients. Common garden experiments provide powerful means to disentangle the role of intrinsic factors, such as genetic or maternal effects, from extrinsic environmental factors in shaping phenotypic variation. Here, we investigate body size and lipid content variation in workers of the socially polymorphic ant Formica selysi along several independent elevation gradients in Switzerland. We compare field-collected workers and workers sampled as eggs from the same colonies but reared in common laboratory conditions. Overall, field-collected workers from high elevation are larger than those from low elevation, but the trend varies substantially among valleys. The same pattern is recovered when the eggs are reared in a common garden, which indicates that body size variation along elevation gradients and valleys is partly explained by genetic or maternal effects. However, both body size and lipid content exhibit significantly greater variation in field-collected workers than in laboratory-reared workers. Hence, much of the phenotypic variation results from a plastic response to the environment, rather than from genetic differences. Eggs from different elevations also show no significant difference in development time in the common garden. Overall, selection on individual worker phenotypes is unlikely to drive the altitudinal distribution of single- and multiple-queen colonies in this system, as phenotypic variation tends to be plastic and can be decoupled from social structure. This study provides insights into the interplay between individual phenotypic variation and social organization and how the two jointly respond to differing environmental conditions.

The composition of airborne and grain-dust fungal communities is shaped at regional scale by plant genotypes and farming practices

Chronic exposure to airborne fungi has been associated with different respiratory symptoms and pathologies in occupational populations, such as grain workers. However, the homogeneity in the fungal species composition of these bioaerosols on a large geographical scale and the different drivers that shape these fungal communities remain unclear. In this study, the diversity of fungi in grain dust and in the aerosols released during harvesting was determined across 96 sites at a geographical scale of 560 km(2) along an elevation gradient of 500 m by tag-encoded 454-pyrosequencing of the internal transcribed spacer (ITS) sequences. Associations between the structure of fungal communities in the grain dust and different abiotic (farming system, soil characteristics, geographic and climatic parameters) and biotic (wheat cultivar, previous crop culture) factors were explored. These analyses revealed a strong relationship between the airborne and grain dust fungal communities and showed the presence of allergenic and mycotoxigenic species in most samples, which highlights the potential contribution of these fungal species to work-related respiratory symptoms of grain workers. The farming system was the major driver of the alpha and beta phylogenetic diversity of fungal communities. In addition, elevation and soil CaCO3 concentrations shaped the alpha diversity whereas wheat cultivar, cropping history and the number of freezing days per year shaped the taxonomic beta diversity of these communities.

Will climate change increase the risk of plant invasions into mountains?

Mountain ecosystems have been less adversely affected by invasions of non-native plants than most other ecosystems, partially because most invasive plants in the lowlands are limited by climate and cannot grow under harsher high-elevation conditions. However, with ongoing climate change, invasive species may rapidly move upwards and threaten mid- then high-elevation mountain ecosystems. We evaluated this threat by predicting current and future potential distributions of 48 invasive plant species distributed in Switzerland (CH) and New South Wales (NSW), two areas where climate interacts differently with the elevation gradient. Using a species distribution modeling approach combining two scales, which builds on high-resolution data (< 250 m) but accounts for the global climatic niche of species, we found that different environmental drivers limit the elevation range of invasive species in the two regions, leading to region-specific species responses to climate change. Whereas the optimal suitability for plant invaders is predicted to markedly shift from the lowland to the montane or subalpine zone in CH, such an upward shift is far less pronounced in NSW where montane and subalpine elevations are currently already suitable. Non-native species able to invade the upper reaches of mountains in a future climate will be cold-tolerant in the Swiss Alps but preferring wet soils in the Australian Alps. Other plant traits were only marginally associated with elevation limits. These results demonstrate that a more systematic consideration of future distributions of invasive species is required in conservation plans of not yet invaded mountainous ecosystems.

The fish zonation of the Itanha,m river basin in the Atlantic Forest of southeast Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Vertical and Horizontal Vegetation Structure across Natural and Modified Habitat Types at Mount Kilimanjaro

In most habitats, vegetation provides the main structure of the environment. This complexity can facilitate biodiversity and ecosystem services. Therefore, measures of vegetation structure can serve as indicators in ecosystem management. However, many structural measures are laborious and require expert knowledge. Here, we used consistent and convenient measures to assess vegetation structure over an exceptionally broad elevation gradient of 866–4550m above sea level at Mount Kilimanjaro, Tanzania. Additionally, we compared (human)-modified habitats, including maize fields, traditionally managed home gardens, grasslands, commercial coffee farms and logged and burned forests with natural habitats along this elevation gradient. We distinguished vertical and horizontal vegetation structure to account for habitat complexity and heterogeneity. Vertical vegetation structure (assessed as number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) displayed a unimodal elevation pattern, peaking at intermediate elevations in montane forests, whereas horizontal structure (assessed as coefficient of variation of number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) was lowest at intermediate altitudes. Overall, vertical structure was consistently lower in modified than in natural habitat types, whereas horizontal structure was inconsistently different in modified than in natural habitat types, depending on the specific structural measure and habitat type. Our study shows how vertical and horizontal vegetation structure can be assessed efficiently in various habitat types in tropical mountain regions, and we suggest to apply this as a tool for informing future biodiversity and ecosystem service studies.

Disturbances, elevation, topography and spatial proximity drive vegetation patterns along an altitudinal gradient of a top biodiversity hotspot

The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10-1,093 m a.s.l.) in the Atlantic Rainforest-a top hotspot for biodiversity conservation-and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest. © 2013 Springer Science+Business Media Dordrecht.

Forest structure and live aboveground biomass variation along an elevational gradient of tropical Atlantic moist forest (Brazil)

Live aboveground biomass (AGB) is an important source of uncertainty in the carbon balance from the tropical regions in part due scarcity of reliable estimates of live AGB and its variation across landscapes and forest types. Studies of forest structure and biomass stocks of Neotropical forests are biased toward Amazonian and Central American sites. In particular, standardized estimates of aboveground biomass stocks for the Brazilian Atlantic forest are rarely available. Notwithstanding the role of environmental variables that control the distribution and abundance of biomass in tropical lowland forests has been the subject of considerable research, the effect of short, steep elevational gradients on tropical forest structure and carbon dynamics is not well known. In order to evaluate forest structure and live AGB variation along an elevational gradient (0-1100 m a.s.l.) of coastal Atlantic Forest in SE Brazil, we carried out a standard census of woody stems >= 4.8 cm dbh in 13 1-ha permanent plots established on four different sites in 2006-2007. Live AGB ranged from 166.3 Mg ha(-1) (bootstrapped 95% CI: 1444,187.0) to 283.2 Mg ha(-1) (bootstrapped 95% CI: 253.0,325.2) and increased with elevation. We found that local-scale topographic variation associated with elevation influences the distribution of trees >50 cm dbh and total live AGB. Across all elevations, we found more stems (64-75%) with limited crown illumination but the largest proportion of the live AGB (68-85%) was stored in stems with highly illuminated or fully exposed crowns. Topography, disturbance and associated changes in light and nutrient supply probably control biomass distribution along this short but representative elevational gradient. Our findings also showed that intact Atlantic forest sites stored substantial amounts of carbon aboveground. The live tree AGB of the stands was found to be lower than Central Amazonian forests, but within the range of Neotropical forests, in particular when compared to Central American forests. Our comparative data suggests that differences in live tree AGB among Neotropical forests are probably related to the heterogeneous distribution of large and medium-sized diameter trees within forests and how the live biomass is partitioned among those size classes, in accordance with general trends found by previous studies. In addition, the elevational variation in live AGB stocks suggests a large spatial variability over coastal Atlantic forests in Brazil, clearly indicating that it is important to consider regional differences in biomass stocks for evaluating the role of this threatened tropical biome in the global carbon cycle. (C) 2010 Elsevier B.V. All rights reserved.