Intensifying postfire weather and biological invasion drive species loss in a Mediterranean-type biodiversity hotspot.

Prolonged periods of extreme heat or drought in the first year after fire affect the resilience and diversity of fire-dependent ecosystems by inhibiting seed germination or increasing mortality of seedlings and resprouting individuals. This interaction between weather and fire is of growing concern as climate changes, particularly in systems subject to stand-replacing crown fires, such as most Mediterranean-type ecosystems. We examined the longest running set of permanent vegetation plots in the Fynbos of South Africa (44 y), finding a significant decline in the diversity of plots driven by increasingly severe postfire summer weather events (number of consecutive days with high temperatures and no rain) and legacy effects of historical woody alien plant densities 30 y after clearing. Species that resprout after fire and/or have graminoid or herb growth forms were particularly affected by postfire weather, whereas all species were sensitive to invasive plants. Observed differences in the response of functional types to extreme postfire weather could drive major shifts in ecosystem structure and function such as altered fire behavior, hydrology, and carbon storage. An estimated 0.5 °C increase in maximum temperature tolerance of the species sets unique to each survey further suggests selection for species adapted to hotter conditions. Taken together, our results show climate change impacts on biodiversity in the hyperdiverse Cape Floristic Region and demonstrate an important interaction between extreme weather and disturbance by fire that may make flammable ecosystems particularly sensitive to climate change.

Climate change both facilitates and inhibits invasive plant ranges in New England.

Forecasting ecological responses to climate change, invasion, and their interaction must rely on understanding underlying mechanisms. However, such forecasts require extrapolation into new locations and environments. We linked demography and environment using experimental biogeography to forecast invasive and native species' potential ranges under present and future climate in New England, United States to overcome issues of extrapolation in novel environments. We studied two potentially nonequilibrium invasive plants' distributions, Alliaria petiolata (garlic mustard) and Berberis thunbergii (Japanese barberry), each paired with their native ecological analogs to better understand demographic drivers of invasions. Our models predict that climate change will considerably reduce establishment of a currently prolific invader (A. petiolata) throughout New England driven by poor demographic performance in warmer climates. In contrast, invasion of B. thunbergii will be facilitated because of higher growth and germination in warmer climates, with higher likelihood to establish farther north and in closed canopy habitats in the south. Invasion success is in high fecundity for both invasive species and demographic compensation for Apetiolata relative to native analogs. For A. petiolata, simulations suggest that eradication efforts would require unrealistic efficiency; hence, management should focus on inhibiting spread into colder, currently unoccupied areas, understanding source-sink dynamics, and understanding community dynamics should A. petiolata (which is allelopathic) decline. Our results-based on considerable differences with correlative occurrence models typically used for such biogeographic forecasts-suggest the urgency of incorporating mechanism into range forecasting and invasion management to understand how climate change may alter current invasion patterns.

Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts.

Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041-2050 and 2090-2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.

Climatic controls on ecosystem resilience: Postfire regeneration in the Cape Floristic Region of South Africa.

Conservation of biodiversity and natural resources in a changing climate requires understanding what controls ecosystem resilience to disturbance. This understanding is especially important in the fire-prone Mediterranean systems of the world. The fire frequency in these systems is sensitive to climate, and recent climate change has resulted in more frequent fires over the last few decades. However, the sensitivity of postfire recovery and biomass/fuel load accumulation to climate is less well understood than fire frequency despite its importance in driving the fire regime. In this study, we develop a hierarchical statistical framework to model postfire ecosystem recovery using satellite-derived observations of vegetation as a function of stand age, topography, and climate. In the Cape Floristic Region (CFR) of South Africa, a fire-prone biodiversity hotspot, we found strong postfire recovery gradients associated with climate resulting in faster recovery in regions with higher soil fertility, minimum July (winter) temperature, and mean January (summer) precipitation. Projections using an ensemble of 11 downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) suggest that warmer winter temperatures in 2080-2100 will encourage faster postfire recovery across the region, which could further increase fire frequency due to faster fuel accumulation. However, some models project decreasing precipitation in the western CFR, which would slow recovery rates there, likely reducing fire frequency through lack of fuel and potentially driving local biome shifts from fynbos shrubland to nonburning semidesert vegetation. This simple yet powerful approach to making inferences from large, remotely sensed datasets has potential for wide application to modeling ecosystem resilience in disturbance-prone ecosystems globally.

Functional Traits in Parallel Evolutionary Radiations and Trait-Environment Associations in the Cape Floristic Region of South Africa.

Evolutionary radiations with extreme levels of diversity present a unique opportunity to study the role of the environment in plant evolution. If environmental adaptation played an important role in such radiations, we expect to find associations between functional traits and key climatic variables. Similar trait-environment associations across clades may reflect common responses, while contradictory associations may suggest lineage-specific adaptations. Here, we explore trait-environment relationships in two evolutionary radiations in the fynbos biome of the highly biodiverse Cape Floristic Region (CFR) of South Africa. Protea and Pelargonium are morphologically and evolutionarily diverse genera that typify the CFR yet are substantially different in growth form and morphology. Our analytical approach employs a Bayesian multiple-response generalized linear mixed-effects model, taking into account covariation among traits and controlling for phylogenetic relationships. Of the pairwise trait-environment associations tested, 6 out of 24 were in the same direction and 2 out of 24 were in opposite directions, with the latter apparently reflecting alternative life-history strategies. These findings demonstrate that trait diversity within two plant lineages may reflect both parallel and idiosyncratic responses to the environment, rather than all taxa conforming to a global-scale pattern. Such insights are essential for understanding how trait-environment associations arise and how they influence species diversification.

Beyond seasonal climate: statistical estimation of phenological responses to weather.

Phenological events, such as the timing of flowering or insect emergence, are influenced by a complex combination of climatic and non-climatic factors. Although temperature is generally considered most important, other weather events such as frosts and precipitation events can also influence many species' phenology. Non-climatic variables such as photoperiod and site-specific habitat characteristics can also have important effects on phenology. Forecasting phenological shifts due to climate change requires understanding and quantifying how these multiple factors combine to affect phenology. However, current approaches to analyzing phenological data have a limited ability for quantifying multiple drivers simultaneously. Here, we use a novel statistical approach to estimate the combined effects of multiple variables, including local weather events, on the phenology of several taxa (a tree, an insect, and a fungus). We found that thermal forcing had a significant positive effect on each species, frost events delayed the phenology of the tree and butterfly, and precipitation had a positive effect on fungal fruiting. Using data from sites across latitudinal gradients, we found that these effects are remarkably consistent across sites once latitude and other site effects are accounted for. This consistency suggests an underlying biological response to these variables that is not commonly estimated using data from field observations. This approach's flexibility will be useful for forecasting ongoing phenological responses to changes in climate variability in addition to seasonal trends.

Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology.

Understanding the drivers of phenological events is vital for forecasting species' responses to climate change. We developed flexible Bayesian survival regression models to assess a 29-year, individual-level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time-varying (chill and heat units) and time-invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2-6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time-to-event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.

Development and characterization of microsatellite markers for Berberis thunbergii (Berberidaceae).

PREMISE OF THE STUDY: Microsatellite markers were isolated and characterized in Berberis thunbergii, an invasive and ornamental shrub in the eastern United States, to assess genetic diversity among populations and potentially identify horticultural cultivars. METHODS AND RESULTS: A total of 12 loci were identified for the species. Eight of the loci were polymorphic and were screened in 24 individuals from two native (Tochigi and Ibaraki prefectures, Japan) and one invasive (Connecticut, USA) population and 21 horticultural cultivars. The number of alleles per locus ranged from three to seven, and observed heterozygosity ranged from 0.048 to 0.636. CONCLUSIONS: These new markers will provide tools for examining genetic relatedness of B. thunbergii plants in the native and invasive range, including phylogeographic studies and assessment of rapid evolution in the invasive range. These markers may also provide tools for examining hybridization with other related species in the invasive range.

Low levels of climate niche conservatism may explain clade diversity patterns in the South African genus Pelargonium (Geraniaceae).

PREMISE OF THE STUDY: Sharp climatic gradients in South Africa and in particular in the Cape Floristic Region (CFR) provide a diversity of niches over short distances that may have promoted ecological diversification in local clades. Here we measured the extent to which closely related species occupy divergent climates and test whether niche lability is correlated with higher species diversity in the genus. METHOD: We integrated phylogenetic information and environmental niche models (ENM) to assess the levels of climate niche conservatism. ENMs for 113 species of Pelargonium were calculated using maximum entropy. We used two tests, one assessing climate niche equivalency and the other testing niche similarity between sister species and within sections. We also examined whether niche similarity was correlated with phylogenetic relatedness across the genus. KEY RESULTS: Niche similarity was mostly independent of phylogenetic relationships. Compared to random expectations, 23% of closely related species pairs had climate niches that were more similar, and only 6.5% were more disparate; the remaining 70% of comparisons had similarities that fell within random expectations. Similar trends were observed when analyses were restricted to only sister species pairs. Although the overall proportion of niche divergence was low, this was significantly related to sectional diversity. We also found a negative relationship between diversity and the proportion of random niches. CONCLUSIONS: Lack of widespread niche conservatism in a highly heterogeneous landscape and few instances of significant climate niche lability suggest that an adaptive divergence process was implicated in the Pelargonium radiation.

Disentangling the paradox of insect phenology: are temporal trends reflecting the response to warming?

The strength and direction of phenological responses to changes in climate have been shown to vary significantly both among species and among populations of a species, with the overall patterns not fully resolved. Here, we studied the temporal and spatial variability associated with the response of several insect species to recent global warming. We use hierarchical models within a model comparison framework to analyze phenological data gathered over 40 years by the Japan Meteorological Agency on the emergence dates of 14 insect species at sites across Japan. Contrary to what has been predicted with global warming, temporal trends of annual emergence showed a later emergence day for some species and sites over time, even though temperatures are warming. However, when emergence data were analyzed as a function of temperature and precipitation, the overall response pointed out an earlier emergence day with warmer conditions. The apparent contradiction between the response to temperature and trends over time indicates that other factors, such as declining populations, may be affecting the date phenological events are being recorded. Overall, the responses by insects were weaker than those found for plants in previous work over the same time period in these ecosystems, suggesting the potential for ecological mismatches with deleterious effects for both suites of species. And although temperature may be the major driver of species phenology, we should be cautious when analyzing phenological datasets as many other factors may also be contributing to the variability in phenology.

Can entropy maximization use functional traits to explain species abundances? A comprehensive evaluation.

Entropy maximization (EM) is a method that can link functional traits and community composition by predicting relative abundances of each species in a community using limited trait information. We developed a complementary suite of tests to examine the strengths and limitations of EM and the community-aggregated traits (CATs; i.e., weighted averages) on which it depends that can be applied to virtually any plant community data set. We show that suites of CATs can be used to differentiate communities and that EM can address the classic problem of characterizing ecological niches by quantifying constraints (CATs) on complex trait relationships in local communities. EM outperformed null models and comparable regression models in communities with different levels of dominance, diversity, and trait similarity. EM predicted well the abundance of the dominant species that drive community-level traits; it typically identified rarer species as such, although it struggled to predict the abundances of the rarest species in some cases. Predictions were sensitive to choice of traits, were substantially improved by using informative priors based on null models, and were robust to variation in trait measurement due to intraspecific variability or measurement error. We demonstrate how similarity in species' traits confounds predictions and provide guidelines for applying EM.

Developing dynamic mechanistic species distribution models: predicting bird-mediated spread of invasive plants across northeastern North America.

Species distribution models are a fundamental tool in ecology, conservation biology, and biogeography and typically identify potential species distributions using static phenomenological models. We demonstrate the importance of complementing these popular models with spatially explicit, dynamic mechanistic models that link potential and realized distributions. We develop general grid-based, pattern-oriented spread models incorporating three mechanisms--plant population growth, local dispersal, and long-distance dispersal--to predict broadscale spread patterns in heterogeneous landscapes. We use the model to examine the spread of the invasive Celastrus orbiculatus (Oriental bittersweet) by Sturnus vulgaris (European starling) across northeastern North America. We find excellent quantitative agreement with historical spread records over the last century that are critically linked to the geometry of heterogeneous landscapes and each of the explanatory mechanisms considered. Spread of bittersweet before 1960 was primarily driven by high growth rates in developed and agricultural landscapes, while subsequent spread was mediated by expansion into deciduous and coniferous forests. Large, continuous patches of coniferous forests may substantially impede invasion. The success of C. orbiculatus and its potential mutualism with S. vulgaris suggest troubling predictions for the spread of other invasive, fleshy-fruited plant species across northeastern North America.

Forecasting phenology under global warming.

As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953-2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology.

Multivariate forecasts of potential distributions of invasive plant species.

The fact that plant invasions are an ongoing process makes generalizations of invasive spread extraordinarily challenging. This is particularly true given the idiosyncratic nature of invasions, in which both historical and local conditions affect establishment success and hinder our ability to generate guidelines for early detection and eradication of invasive species. To overcome these limitations we have implemented a comprehensive approach that examines plant invasions at three spatial scales: regional, landscape, and local levels. At each scale, in combination with the others, we have evaluated the role of key environmental variables such as climate, landscape structure, habitat type, and canopy closure in the spread of three commonly found invasive woody plant species in New England, Berberis thunbergii, Celastrus orbiculatus, and Euonymus alatus. We developed a spatially explicit hierarchical Bayesian model that allowed us to take into account the ongoing nature of the spread of invasive species and to incorporate presence/absence data from the species' native ranges as well as from the invaded regions. Comparisons between predictions from climate-only models with those from the multiscale forecasts emphasize the importance of including landscape structure in our models of invasive species' potential distributions. In addition, predictions generated using only native range data performed substantially worse than those that incorporated data from the target range. This points out important limitations in extrapolating distributional ranges from one region to another.

Comparative performance of invasive and native Celastrus species across environmental gradients.

The ability to understand and predict the success of invasive plant species in their new ranges is increased when there is a sympatric native congener available for comparison. Celastrus orbiculatus (oriental bittersweet) is a liana introduced into the United States in the mid-1800s from East Asia as an ornamental plant. Its native congener, Celastrus scandens (American bittersweet), ranges from the east coast of the United States as far west as Wyoming. In the Northeastern United States, C. orbiculatus is continuing to expand its range while C. scandens appears to be in serious decline. One hypothesis for this decline is that C. scandens does not have such a wide range of ecological tolerances in the current landscape as C. orbiculatus, which seems to tolerate a greater range of resource conditions. To investigate this hypothesis, we transplanted these two species into ten sites that spanned a full range of light and soil moisture conditions to compare their establishment and performance in terms of aboveground growth (biomass and height) and mortality. After two years, C. orbiculatus showed significantly lower mortality and greater biomass across all resource conditions compared to C. scandens. In addition, C. orbiculatus preferred more mesic soil moisture conditions, while C. scandens performed better in drier soil moisture conditions. Since much of the Northeastern United States is now forested, this preference for mesic soil conditions could make it more successful than C. scandens in the region. This study shows the utility of manipulative experiments, particularly those using congeneric native species as benchmarks, for assessing the causes and predicting the course of invasions.

Springs and wire plants: anachronistic defences against Madagascar's extinct elephant birds.

The extinction of large vertebrates in the last few millennia has left a legacy of evolutionary anachronisms. Among these are plant structural defences that persist long after the extinction of the browsers. A peculiar, and controversial, example is a suite of traits common in divaricate (wide-angled branching) plants from New Zealand. Divaricate architecture has been interpreted as an adaptive response to cold climates or an anachronistic defence against the extinct moas. Madagascar, a larger tropical island, also had a fauna of large flightless birds, the elephant birds. If these extinct ratites selected for similar plant defences, we expected to find convergent features between New Zealand and Malagasy plants, despite their very different climates. We searched the southern thickets of Madagascar for plants with putative anti-ratite defences and scored candidate species for a number of traits common to many New Zealand divaricates. We found many Malagasy species in 25 families and 36 genera shared the same suite of traits, the 'wire plant' syndrome, as divaricates in New Zealand that resist ratite browsing. Neither ecologically, nor phylogenetically, matched species from South Africa shared these traits. Malagasy wire plants differ from many New Zealand divaricates in lacking the distinctive concentration of leaves in the interior of shrubs. We suggest that New Zealand divaricates have a unique amalgam of traits that acted as defences and also confer tolerance to cold. We conclude that many woody species in the thickets of southern Madagascar share, with New Zealand, anachronistic structural defences against large extinct bird browsers.

Building statistical models to analyze species distributions.

Models of the geographic distributions of species have wide application in ecology. But the nonspatial, single-level, regression models that ecologists have often employed do not deal with problems of irregular sampling intensity or spatial dependence, and do not adequately quantify uncertainty. We show here how to build statistical models that can handle these features of spatial prediction and provide richer, more powerful inference about species niche relations, distributions, and the effects of human disturbance. We begin with a familiar generalized linear model and build in additional features, including spatial random effects and hierarchical levels. Since these models are fully specified statistical models, we show that it is possible to add complexity without sacrificing interpretability. This step-by-step approach, together with attached code that implements a simple, spatially explicit, regression model, is structured to facilitate self-teaching. All models are developed in a Bayesian framework. We assess the performance of the models by using them to predict the distributions of two plant species (Proteaceae) from South Africa's Cape Floristic Region. We demonstrate that making distribution models spatially explicit can be essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results. Adding hierarchical levels to the models has further advantages in allowing human transformation of the landscape to be taken into account, as well as additional features of the sampling process.

Comment on "Neutral ecological theory reveals isolation and rapid speciation in a biodiversity hot spot".

Latimer et al. (Reports, 9 September 2005, p. 1722) used an approximate likelihood function to estimate parameters of Hubbell's neutral model of biodiversity. Reanalysis with the exact likelihood not only yields different estimates but also shows that two similar likelihood maxima for very different parameter combinations can occur. This reveals a limitation of using species abundance data to gain insight into speciation and dispersal.

Differential responses of invasive Celastrus orbiculatus (Celastraceae) and native C. scandens to changes in light quality.

When plants are subjected to leaf canopy shade in forest understories or from neighboring plants, they not only experience reduced light quantity, but light quality in lowered red : far red light (R : FR). Growth and other developmental responses of plants in reduced R : FR can vary and are not consistent across species. We compared how an invasive liana, Celastrus orbiculatus, and its closely related native congener, C. scandens, responded to changes in the R : FR under controlled, simulated understory conditions. We measured a suite of morphological and growth attributes under control, neutral shading, and low R : FR light treatments. Celastrus orbiculatus showed an increase in height, aboveground biomass, and total leaf mass in reduced R : FR treatments as compared to the neutral shade, while C. scandens had increased stem diameter, single leaf area, and leaf mass to stem mass ratio. These differences provide a mechanistic understanding of the ability of C. orbiculatus to increase height and actively forage for light resources in forest understories, while C. scandens appears unable to forage for light and instead depends upon a light gap forming. The plastic growth response of C. orbiculatus in shaded conditions points to its success in forested habitats where C. scandens is largely absent.

Neutral ecological theory reveals isolation and rapid speciation in a biodiversity hot spot.

South Africa's Mediterranean-climate fynbos shrubland is a hot spot of species diversity, but its diversity patterns contrast strongly with other high-diversity areas, including the Amazon rain forest. With its extremely high levels of endemism and species turnover, fynbos is made up of dissimilar local communities that are species-rich but relatively poor in rare species. Using neutral ecological theory, we show that the relative species-abundance distributions in fynbos can be explained by migration rates that are two orders of magnitude lower than they are in tropical rain forests. Speciation rates, which are indexed by the "biodiversity parameter" Theta, are estimated to be higher than they are in any previously examined plant system.