The data void in modeling current and future distributions of tropical species

Conserving biodiversity in the face of climate change requires a predictive ecology of species distributions. Nowhere is this need more acute than in the tropics, which harbor the majority of Earth's species and face rapid and large climate and land‐use changes. However, the study of species distributions and their responses to climate change in high diversity tropical regions is potentially crippled by a lack of basic data. We analyzed a database representing more than 800 000 unique geo‐referenced natural history collections to determine what fraction of tropical plant species has sufficient numbers of available collections for use in the habitat or niche models commonly used to predict species responses to climate change. We found that more than nine out of 10 species from the three principle tropical realms are so poorly collected (n < 20 records) that they are essentially invisible to modern modeling and conservation tools. In order to predict the impact of climate change on tropical species, efforts must be made to increase the amount of data available from tropical countries through a combination of collecting new specimens and digitizing existing records.     

Influence of simulated climate change and eutrophication on three‐spined stickleback populations: a large scale mesocosm experiment

1. Shallow lakes and their ectothermic inhabitants are particularly vulnerable to the effects of climatic warming. These impacts are likely to depend on nutrient loading, especially if the combination of warming and eutrophication leads to severe hypoxia. 2. To investigate effects of realistic warming and nutrient loading on a fish species with high tolerance of warming and hypoxia, we observed population changes and timing of reproduction of three‐spined sticklebacks in 24 outdoor shallow freshwater ecosystems with combinations of temperature (ambient and ambient +4 °C) and three nutrient treatments over 16 months. 3. Warming reduced stickleback population biomass by 60% (population size by 76%) and nutrient‐addition reduced biomass by about 80% (population size 95%). Nutrients and warming together resulted in extinction of the stickleback populations. These losses were mainly attributed to the increased likelihood of severe hypoxia in heated and nutrient‐addition mesocosms. 4. Warming of nutrient‐rich waters can thus have dire consequences for freshwater ectotherm populations. The loss even of a hardy fish suggests a precarious future for many less tolerant species in such eutrophic systems under current climate change predictions.     

Assessing forest growth across southwestern Oregon under a range of current and future global change scenarios using a process model, 3‐PG

With improvements in mapping regional distributions of vegetation using satellite‐derived information, there is an increasing interest in the assessment of current limitations on forest growth and in making projections of how productivity may be altered in response to changing climatic conditions and management policies. We utilised a simplified physiologically based process model (3‐PG) across a 54 000 km² mountainous region of southwestern Oregon, USA, to evaluate the degree to which maximum periodic mean annual increment (PAI) of forests could be predicted at a set of 448 forest inventory plots. The survey data were pooled into six broad forest types (coastal rain forest, interior coast range forest, mixed conifer, dry‐site Douglas‐fir, subalpine forest, and pine forest) and compared to the 3‐PG predictions at a spatial resolution of 1 km². We found good agreement (r² = 0.84) between mean PAI values of forest productivity for the six forest types with those obtained from field surveys. With confidence at this broader level of integration, we then ran model simulations to evaluate the constraints imposed by (i) soil fertility under current climatic conditions, (ii) the effect of doubling monthly precipitation across the region, and (iii) a widely used climatic change scenario that involves modifications in monthly mean temperatures and precipitation, as well as a doubling in atmospheric CO₂ concentrations. These analyses showed that optimum soil fertility would more than double growth, with the greatest response in the subalpine type and the least increase in the coastal rain forests. Doubling the precipitation increased productivity in the pine type (> 50%) with reduced responses elsewhere. The climate change scenario with doubled atmospheric CO₂ increased growth by 50% on average across all forest types, primarily as a result of a projected 33% increase in photosynthetic capacity. This modelling exercise indicates that, at a regional scale, a general relationship exists between simulated maximum leaf area index and maximum aboveground growth, supporting the contention that satellite‐derived estimates of leaf area index may be good measures of the potential productivity of temperate evergreen forests.     

Large‐scale comparison of protein essential dynamics from molecular dynamics simulations and coarse‐grained normal mode analyses

A large‐scale comparison of essential dynamics (ED) modes from molecular dynamic simulations and normal modes from coarse‐grained normal mode methods (CGNM) was performed on a dataset of 335 proteins. As CGNM methods, the elastic network model (ENM) and the rigid cluster normal mode analysis (RCNMA) were used. Low‐frequency normal modes from ENM correlate very well with ED modes in terms of directions of motions and relative amplitudes of motions. Notably, a similar performance was found if normal modes from RCNMA were used, despite a higher level of coarse graining. On average, the space spanned by the first quarter of ENM modes describes 84% of the space spanned by the five ED modes. Furthermore, no prominent differences for ED and CGNM modes among different protein structure classes (CATH classification) were found. This demonstrates the general potential of CGNM approaches for describing intrinsic motions of proteins with little computational cost. For selected cases, CGNM modes were found to be more robust among proteins that have the same topology or are of the same homologous superfamily than ED modes. In view of recent evidence regarding evolutionary conservation of vibrational dynamics, this suggests that ED modes, in some cases, might not be representative of the underlying dynamics that are characteristic of a whole family, probably due to insufficient sampling of some of the family members by MD. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown.     

BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change

A new computation framework (BIOMOD: BIOdiversity MODelling) is presented, which aims to maximize the predictive accuracy of current species distributions and the reliability of future potential distributions using different types of statistical modelling methods. BIOMOD capitalizes on the different techniques used in static modelling to provide spatial predictions. It computes, for each species and in the same package, the four most widely used modelling techniques in species predictions, namely Generalized Linear Models (GLM), Generalized Additive Models (GAM), Classification and Regression Tree analysis (CART) and Artificial Neural Networks (ANN). BIOMOD was applied to 61 species of trees in Europe using climatic quantities as explanatory variables of current distributions. On average, all the different modelling methods yielded very good agreement between observed and predicted distributions. However, the relative performance of different techniques was idiosyncratic across species, suggesting that the most accurate model varies between species. The results of this evaluation also highlight that slight differences between current predictions from different modelling techniques are exacerbated in future projections. Therefore, it is difficult to assess the reliability of alternative projections without validation techniques or expert opinion. It is concluded that rather than using a single modelling technique to predict the distribution of several species, it would be more reliable to use a framework assessing different models for each species and selecting the most accurate one using both evaluation methods and expert knowledge.     

Climate change influences on global distributions of dengue and chikungunya virus vectors

Numerous recent studies have illuminated global distributions of human cases of dengue and other mosquito-transmitted diseases, yet the potential distributions of key vector species have not been incorporated integrally into those mapping efforts. Projections onto future conditions to illuminate potential distributional shifts in coming decades are similarly lacking, at least outside Europe. This study examined the global potential distributions of Aedes aegypti and Aedes albopictus in relation to climatic variation worldwide to develop ecological niche models that, in turn, allowed anticipation of possible changes in distributional patterns into the future. Results indicated complex global rearrangements of potential distributional areas, which—given the impressive dispersal abilities of these two species—are likely to translate into actual distributional shifts. This exercise also signalled a crucial priority: digitization and sharing of existing distributional data so that models of this sort can be developed more rigorously, as present availability of such data is fragmentary and woefully incomplete.     

Time series analysis of climate‐related factors and their impact on a red‐listed noble crayfish population in northern Sweden

1. Global climate change is predicted to raise water temperatures and alter flow regimes in northern river systems. Climate‐related factors might have profound impacts on survival, reproduction and distribution of freshwater species such as red‐listed noble crayfish (Astacus astacus) in its northern limit of distribution. 2. In this study, noble crayfish capture data over 27 years from the River Ljungan, Sweden, were examined. Time series of catch per unit effort (CPUE) were analysed in relation to the North Atlantic Oscillation (NAO) index, regional weather factors and water flow. CPUE was assumed to reflect differences in population size. Two models were constructed to explore the relative impact of different climate factors and density dependence on variability of catch sizes. 3. The most parsimonious model for CPUE time series, explaining 72% of the variance in CPUE, included density‐dependent population dynamics of the crayfish and climate or weather factors. The specific effect from density dependence in the model was 37%, while climate/weather factors contributed with 35% of the variation. The most important climate/weather factors are variations in NAO index and water flow. Temperature did not improve the model fit to capture data. 4. The best model was evaluated using independent data sets that gave correlations between model predictions and data ranging from 0.44 to 0.53. The density dependence shows a time lag of 1 year, while climate variables show time lags from 2 to 6 years in relation to CPUE, indicating effects on different cohorts of the crayfish population. 5. Both density dependence and climatic factors play a significant role in population fluctuations of noble crayfish. A 6‐year time lag for NAO index is puzzling but indicates that some as yet unidentified factors related to NAO might act on the juvenile stages of the population. Water flow shows a 2‐year lag to the CPUE, and high flow in the river may affect adult survival. The reasons for fluctuation of crayfish catches in response to climate need to be identified, and fishing quotas should consider the different cohort sizes because of variation in environment. Reintroduction programmes for crayfish need to consider effects of climate change when designing management strategies.     

Body size‐dependent responses of a marine fish assemblage to climate change and fishing over a century‐long scale

Commercial fishing and climate change have influenced the composition of marine fish assemblages worldwide, but we require a better understanding of their relative influence on long‐term changes in species abundance and body‐size distributions. In this study, we investigated long‐term (1911–2007) variability within a demersal fish assemblage in the western English Channel. The region has been subject to commercial fisheries throughout most of the past century, and has undergone interannual changes in sea temperature of over 2.0 °C. We focussed on a core 30 species that comprised 99% of total individuals sampled in the assemblage. Analyses showed that temporal trends in the abundance of smaller multispecies size classes followed thermal regime changes, but that there were persistent declines in abundance of larger size classes. Consistent with these results, larger‐growing individual species had the greatest declines in body size, and the most constant declines in abundance, while abundance changes of smaller‐growing species were more closely linked to preceding sea temperatures. Together these analyses are suggestive of dichotomous size‐dependent responses of species to long‐term climate change and commercial fishing over a century scale. Small species had rapid responses to the prevailing thermal environment, suggesting their life history traits predisposed populations to respond quickly to changing climates. Larger species declined in abundance and size, reflecting expectations from sustained size‐selective overharvesting. These results demonstrate the importance of considering species traits when developing indicators of human and climatic impacts on marine fauna.     

The vulnerability of species to range expansions by predators can be predicted using historical species associations and body size

Climate change threatens species directly through environmental changes and indirectly through its effects on species interactions. We need tools to predict which species are most vulnerable to these threats. Pairwise species associations and body size are simple but promising predictors of the relative impact of species introduced outside of their historical ranges. We examined the vulnerability of 30 fish species to the impacts of three centrarchid predators that are being introduced to lakes north of their historical range boundaries. Species that were negatively associated with each centrarchid in their historical range were more likely to be lost from lakes with centrarchid introductions. Total body length was most important in predicting impact for the most gape-limited predator. At the regional scale, our method identifies those species most vulnerable to introductions facilitated by climate change and can easily be applied to a range of taxa undergoing range expansions.     

中国特有种天山猪毛菜的地理分布及潜在分布区预测

基于野外调查的居群分布信息和20个环境变量(包括海拔及19个气候变量),采用最大熵模型( MaxEnt)和地理信息系统( ArcGIS)对中国特有种天山猪毛菜( Salsola junatovii Botsch.)的潜在分布区进行预测;并采用受试者工作特征曲线( ROC)和刀切法( jackknife test)分别检验MaxEnt模型的精度和评估各环境变量在决定潜在分布区时的贡献量。结果显示：天山猪毛菜主要分布在中国新疆南部的12个县(包括托克逊县、和硕县、和静县、焉耆县、拜城县、库车县、温宿县、乌什县、阿合奇县、阿图什县、乌恰县和阿克陶县),但在相关文献记载的曾有分布的阿克苏市、柯坪县和喀什市则本调查中没有发现。通过MaxEnt模型预测,天山猪毛菜的潜在适生区主要集中在新疆南部(包括天山南坡和塔里木盆地西南缘)以及甘肃的西部和东部等,新疆西部地区有零星分布;在调查的15个居群中,除居群14(位于乌恰县西部)外,其他14个居群均位于潜在适生区内,其中的7个居群位于非常适宜的潜在适生区内,表明利用MaxEnt模型预测天山猪毛菜的潜在适生区效果较好。在20个环境变量中,对预测结果贡献量位居前3位的环境变量为最冷季度平均温度、最冷月最低温和最干季度平均温度,表明该种的分布与低温相关。此外,对天山猪毛菜潜在适生区与实际分布区差异的成因进行了分析。     

The influence of climate change scenarios on populations of the mayfly Cloeon dipterum

Populations of the mayfly Cloeon dipterum from 48 ponds (3000 l fibre-glass tanks of 1 m depth) were monitored over the course of 1 year. To simulate possible patterns of climatic change, the ponds were subject to three temperature treatments: continuous heating to 3 °C above ambient; heating to 3 °C above ambient during the summer only; and no heating. Further experimental complexity included enhanced nutrient input into the ponds and the presence or absence of fish, giving a factorial combination of 3 temperature regimes × 2 nutrient levels × presence/absence of fish predation.Few nymphs were found in the presence of fish. Where fish were absent, the temperature treatments did not significantly affect nymph abundances, and only marginally influenced mean nymph body-lengths. In contrast, the nutrient treatment had significant effects on both nymph abundance and size, with greater numbers of generally larger nymphs occurring in those fish-free ponds receiving additional nutrients. Adult emergence began earlier in the year from the heated ponds, particularly those ponds receiving additional nutrients. Adult body-length differed between temperature treatments, but consistent patterns were difficult to ascertain because of interactions with nutrient treatment and seasonal effects.Our results show that during the short term at least, elevated temperature as a simulation of climate change does not have an overwhelming influence on either mayfly abundance or size. The influence of temperature is subtle and subject to complex interaction with other habitat variables. We therefore suggest that the direct consequences of small changes in temperature will likely be of little significance to C. dipterum, relative to indirect effects operating through interactions with predation and nutrient input.     

Global mapping of Jatropha curcas yield based on response of fitness to present and future climate

Although acclaimed as a biofuel crop with high potential to sustainably replace fossil fuels, Jatropha curcas L. remains a poorly studied plant. Reliable yield assessments with conventional methods require agroclimatic and physiological knowledge, which is not yet available for Jatropha. To fill this gap, we tested a novel two‐step approach integrating knowledge from biogeography and population biology with available Jatropha field data. In the first step, using MaxEnt, a widely implemented model in biogeography, we predicted Jatropha fitness in response to climate by relating natural occurrence recorded in herbaria with bioclimatic geodatasets. In the second step, we relied on population biology principles supported by seed mass addition experiments to relate fitness to reproductive potential, hence seed yield. Jatropha seed yield in response to climate was mapped worldwide for actual (1950–2000 average) and future (2020) climate conditions. The modelled Jatropha seed yield was validated against a set of on‐field yield assessments (R²=0.67, P<0.001). The discrepancies between estimated and measured yields were partially explained by model uncertainties, as quantified by the sensitivity analysis of our modelling (R²=0.57, P=0.001). Jatropha has a pan‐tropical distribution, plus specific adaptability to hot temperate areas. Climate variables most significantly affecting modelled yield response were annual average temperature, minimum temperature, annual precipitation and precipitation seasonality.     

The role of climate,habitat, and species co‐occurrence as drivers of change in small mammal distributions over the past century

Species distribution models are commonly used to predict species responses to climate change. However, their usefulness in conservation planning and policy is controversial because they are difficult to validate across time and space. Here we capitalize on small mammal surveys repeated over a century in Yosemite National Park, USA, to assess accuracy of model predictions. Historical (1900–1940) climate, vegetation, and species occurrence data were used to develop single‐ and multi‐species multivariate adaptive regression spline distribution models for three species of chipmunk. Models were projected onto the current (1980–2007) environmental surface and then tested against modern field resurveys of each species. We evaluated models both within and between time periods and found that even with the inclusion of biotic predictors, climate alone is the dominant predictor explaining the distribution of the study species within a time period. However, climate was not consistently an adequate predictor of the distributional change observed in all three species across time. For two of the three species, climate alone or climate and vegetation models showed good predictive performance across time. The stability of the distribution from the past to present observed in the third species, however, was not predicted by our modeling approach. Our results demonstrate that correlative distribution models are useful in understanding species' potential responses to environmental change, but also show how changes in species‐environment correlations through time can limit the predictive performance of models.     

Carbon stocks in above‐ground biomass of monoculture plantations,mixed species plantations and environmental restoration plantings in north‐east Australia

Summary The emergence of carbon markets has provided a potential source of funding for reforestation projects. However, there is concern amongst ecologists that these markets will promote the establishment of monoculture plantations rather than more diverse restoration plantings, on the assumption that fast‐growing monocultures are likely to store more carbon than restoration plantings. We examined the validity of this assumption for three predominantly rainforest plantation types established in the moist tropical uplands of north‐east Australia: monoculture plantations of native rainforest conifers (n = 5, mean age 13 years); mixed species plantations of rainforest cabinet timber species, rainforest conifers and eucalypts (n = 5, mean age 13 years); and, environmental restoration plantings comprised mostly of a diverse range of rainforest trees (n = 10, mean age 14 years). We found that restoration plantings stored significantly more carbon in above‐ground biomass than monoculture plantations of native conifers (on average, 106 t vs 62 t carbon per ha); and tended to store more carbon than mixed species timber plantations which were intermediate in value (86 t carbon per ha). Carbon stocks were higher in restoration plantings than in monoculture and mixed species plantations for three reasons. First, and most importantly, restoration plantings were more densely stocked than monoculture and mixed species plantations. Second, there were more large diameter trees in restoration plantings than monoculture plantations. Third, the trees used in restoration plantings had a higher average wood density than the conifers used in monoculture plantations. While, on average, wood density was higher in mixed species plantations than restoration plantings, the much higher stocking rate of restoration plantings meant they stored more carbon than mixed species plantations. We conclude that restoration plantings in the moist tropics of north‐east Australia can accumulate relatively high amounts of carbon within two decades of establishment. Comparison with reference rainforest sites suggests that restoration plantings could maintain their high stocking rates (and therefore high biomass) as they develop in future decades. However, because restoration plantings are currently much more expensive to establish than monoculture plantations, restoration plantings are unlikely to be favoured by carbon markets. Novel reforestation techniques and designs are required if restoration plantings are to both provide habitat for rainforest biota and store carbon in biomass at a cost comparable to monoculture plantations.     

Experimental simulations about the effects of overexploitation and habitat fragmentation on populations facing environmental warming

Populations of many species are dramatically declining worldwide, but the causal mechanism remains debated among different human-related threats. Coping with this uncertainty is critical to several issues about the conservation and future of biodiversity, but remains challenging due to difficulties associated with the experimental manipulation and/or isolation of the effects of such threats under field conditions. Using controlled microcosm populations, we quantified the individual and combined effects of environmental warming, overexploitation and habitat fragmentation on population persistence. Individually, each of these threats produced similar and significant population declines, which were accelerated to different degrees depending upon particular interactions. The interaction between habitat fragmentation and harvesting generated an additive decline in population size. However, both of these threats reduced population resistance causing synergistic declines in populations also facing environmental warming. Declines in population size were up to 50 times faster when all threats acted together. These results indicate that species may be facing risks of extinction higher than those anticipated from single threat analyses and suggest that all threats should be mitigated simultaneously, if current biodiversity declines are to be reversed.     

Cross‐biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

We analyzed results from 10‐year long field incubations of foliar and fine root litter from the Long‐term Intersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these models changed over short to long time periods. Six genera of foliar and three genera of root litters were studied with a 10‐fold range in the ratio of acid unhydrolyzable fraction (AUF, or ‘lignin’) to N. Litter was incubated at 27 field sites across numerous terrestrial biomes including arctic and alpine tundra, temperate and tropical forests, grasslands and warm deserts. We used three separate mathematical models of first‐order (exponential) decomposition, emphasizing either the first year or the entire decade. One model included the proportion of relatively stable material as an asymptote. For short‐term (first‐year) decomposition, nonlinear regressions of exponential or power function form were obtained with r² values of 0.82 and 0.64 for foliar and fine‐root litter, respectively, across all biomes included. AUF and AUF : N ratio were the most explanative litter quality variables, while the combined temperature‐moisture terms AET (actual evapotranspiration) and CDI (climatic decomposition index) were best for climatic effects. Regressions contained some systematic bias for grasslands and arctic and boreal sites, but not for humid tropical forests or temperate deciduous and coniferous forests. The ability of the regression approach to fit climate‐driven decomposition models of the 10‐year field results was dramatically reduced from the ability to capture drivers of short‐term decomposition. Future work will require conceptual and methodological improvements to investigate processes controlling decadal‐scale litter decomposition, including the formation of a relatively stable fraction and its subsequent decomposition.     

Effects of climate‐driven primary production change on marine food webs: implications for fisheries and conservation

Climate change is altering the rate and distribution of primary production in the world's oceans. Primary production is critical to maintaining biodiversity and supporting fishery catches, but predicting the response of populations to primary production change is complicated by predation and competition interactions. We simulated the effects of change in primary production on diverse marine ecosystems across a wide latitudinal range in Australia using the marine food web model Ecosim. We link models of primary production of lower trophic levels (phytoplankton and benthic producers) under climate change with Ecosim to predict changes in fishery catch, fishery value, biomass of animals of conservation interest, and indicators of community composition. Under a plausible climate change scenario, primary production will increase around Australia and generally this benefits fisheries catch and value and leads to increased biomass of threatened marine animals such as turtles and sharks. However, community composition is not strongly affected. Sensitivity analyses indicate overall positive linear responses of functional groups to primary production change. Responses are robust to the ecosystem type and the complexity of the model used. However, model formulations with more complex predation and competition interactions can reverse the expected responses for some species, resulting in catch declines for some fished species and localized declines of turtle and marine mammal populations under primary productivity increases. We conclude that climate‐driven primary production change needs to be considered by marine ecosystem managers and more specifically, that production increases can simultaneously benefit fisheries and conservation. Greater focus on incorporating predation and competition interactions into models will significantly improve the ability to identify species and industries most at risk from climate change.     

Greenhouse gas,upwelling‐favorable winds,and the future of coastal ocean upwelling ecosystems

Coastal ocean upwelling ecosystems generally represent the most productive large marine ecosystems of the world's oceans, in terms of both primary production rates and tonnages of exploitable fish produced. The Peruvian upwelling system, in particular, stands out as a major factor in world fish production. The Pacific trade winds have traditionally been considered to be the primary driving force for the upwelling system off Peru, but are projected to weaken as climate change proceeds. This leads to concern that the upwelling process in the Peru system, to which its productivity is linked, may likewise weaken. However, other mechanisms involving greenhouse‐associated intensification of thermal low‐pressure cells over the coastal landmasses of upwelling regions suggest general intensification of wind‐driven ocean upwelling in coastal upwelling regions of the world's oceans. But although certain empirical results have supported this expectation, it has not been consistently corroborated in climate model simulations, possibly because the scale of the coastal intensification may be small relative to the scales that are appropriately reflected in the standard models. Here we summarize available evidence for the intensification mechanism and present a proxy test that uses variations in water vapor, the dominant natural greenhouse gas, to offer multiple‐realization empirical evidence for action of the proposed mechanism in the real world situation. While many potential consequences to the future of marine ecosystems would codepend on climate change‐related changes in the thermocline and nutricline structures, an important subset, involving potential increased propensities for hypoxia, noxious gas eruptions, toxic red tide blooms, and/or jellyfish outbreaks, may depend more directly on changes in the upwelling‐favorable wind itself. A prospective role of fisheries in either mitigating or reinforcing this particular class of effects is suggested.     

The hydroclimatic and ecophysiological basis of cloud forest distributions under current and projected climates

Background

Tropical montane cloud forests (TMCFs) are characterized by a unique set of biological and hydroclimatic features, including frequent and/or persistent fog, cool temperatures, and high biodiversity and endemism. These forests are one of the most vulnerable ecosystems to climate change given their small geographic range, high endemism and dependence on a rare microclimatic envelope. The frequency of atmospheric water deficits for some TMCFs is likely to increase in the future, but the consequences for the integrity and distribution of these ecosystems are uncertain. In order to investigate plant and ecosystem responses to climate change, we need to know how TMCF species function in response to current climate, which factors shape function and ecology most and how these will change into the future.

Scope

This review focuses on recent advances in ecophysiological research of TMCF plants to establish a link between TMCF hydrometeorological conditions and vegetation distribution, functioning and survival. The hydraulic characteristics of TMCF trees are discussed, together with the prevalence and ecological consequences of foliar uptake of fog water (FWU) in TMCFs, a key process that allows efficient acquisition of water during cloud immersion periods, minimizing water deficits and favouring survival of species prone to drought-induced hydraulic failure.

Conclusions

Fog occurrence is the single most important microclimatic feature affecting the distribution and function of TMCF plants. Plants in TMCFs are very vulnerable to drought (possessing a small hydraulic safety margin), and the presence of fog and FWU minimizes the occurrence of tree water deficits and thus favours the survival of TMCF trees where such deficits may occur. Characterizing the interplay between microclimatic dynamics and plant water relations is key to foster more realistic projections about climate change effects on TMCF functioning and distribution.