Inés Ibáñez

PREDICTING BIODIVERSITY CHANGE: OUTSIDE THE CLIMATE ENVELOPE, BEYOND THE SPECIES–AREA CURVE

Efforts to anticipate threats to biodiversity take the form of species richness predictions (SRPs) based on simple correlations with current climate and habitat area. We review the major approaches that have been used for SRP, species-area curves and climate envelopes, and suggest that alternative research efforts may provide more understanding and guidance for management. Extinction prediction suffers from a number of limitations related to data and the novelty of future environments. We suggest additional attention to (1) identification of variables related to biodiversity that are diagnostic and potentially more predictable than extinction, (2) constraints on species dispersal and reproduction that will determine population persistence and range shifts, including limited sources or potential immigrants for many regions, and (3) changes in biotic interactions and phenology. We suggest combinations of observational and experimental approaches within a framework available for ingesting heterogeneous data sources. Together, these recommendations amount to a shift in emphasis from prediction of extinction numbers to identification of vulnerabilities and leading indicators of change, as well as suggestions for surveillance tools needed to evaluate important variables and the experiments likely to provide most insight.

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.

FECUNDITY OF TREES AND THE COLONIZATION–COMPETITION HYPOTHESIS

Colonization-competition trade-offs represent a stabilizing mechanism that is thought to maintain diversity of forest trees. If so, then early-successional species should benefit from high capacity to colonize new sites, and late-successional species should be good competitors. Tests of this hypothesis in forests have been precluded by an inability to estimate the many factors that contribute to seed production and dispersal, particularly the many types of stochasticity that contribute to fecundity data. We develop a hierarchical Bayes modeling structure, and we use it to estimate fecundity schedules from the two types of data that ecologists typically collect, including seed-trap counts and observations of tree status. The posterior density is obtained using Markov-chain Monte Carlo techniques. The flexiblestructure yields estimatesofsizeandcovariateeffectsonseedproduction,variability associated with population heterogeneity, and interannual stochasticity (variability and se- rial autocorrelation), sex ratio, and dispersal. It admits the errors in data associated with the ability to accurately recognize tree status and process misspecification. We estimate year-by-year seed-production rates for all individuals in each of nine sample stands from two regions and up to 11 years. A rich characterization of differences among species and relationships among individuals allows evaluation of a number of hypotheses related to masting, effective population sizes, and location and covariate effects. It demonstrates large bias in previous methods. We focus on implications for colonization-competition and a related hypothesis, the successional niche—trade-offs in the capacity to exploit high re- source availability in early successional environments vs. the capacity to survive low- resource conditions late in succession. Contrary to predictions of trade-off hypotheses, we find no relationship between suc- cessional status and fecundity, dispersal, or expected arrivals at distant sites. Resultssuggest a mechanism for maintenance of diversity that may be more general than colonization- competition and successional niches. High variability and strong individual effects (vari- ability within populations) generate massive stochasticity in recruitment that, when com- bined with storage, may provide a stabilizing mechanism. The storage effect stabilizes diversity when species differences ensure that responses to stochasticity are not highly correlated among species. Process variability and individual effects mean that many species have the advantage at different times and places even in the absence of deterministic trade-offs. Not only does colonization vary among species, but also individual behavior is highly stochastic and weakly correlated among members of the same population. Although these factors are the dominant sources of variability in data sets (substantially larger than the deterministic relationships typically examined), they have not been not included in the models that ecologists have used to evaluate mechanisms of species coexistence (e.g., even individual-based models lack random individual effects). Recognition of the mechanisms of coexistence requires not only heuristic models that capture the principal sources of stochasticity, but also data-modeling techniques that allow for their estimation.

Plant invasions in the landscape.

Biological invasions and changes in land-use are two components of global change affecting biodiversity worldwide. There is overriding evidence that invasions can dramatically change the landscape and that particular land-use types facilitate invasions. Still, these issues have not formally percolated into risk analysis of biological invasions, and only recently has the influence of the surrounding landscape on invasive species spread started to be considered. In this paper we review the literature on the influence of the surrounding landscape on the local level of plant invasions (i.e., abundance and richness of alien plants in plant communities). Our review confirms that there are more alien plant species and they are more abundant at fragment edges than in the interior of fragments. The decline on the level of invasion towards the interior of fragments is sharp. To a lesser extent, there is higher invasion in small isolated fragments than in large connected patches. However, despite their relevance, the influence of connectivity and shape of the fragments have been scarcely explored. Besides the fact that a site has more invaders if surrounded by a human-dominated landscape than by a natural one, the past history and the configuration of that landscape are also important. Invasion within land-uses is often associated with the historical legacy of changes in land-use, indicating that current land-uses might represent an invasion credit to future invasions. Accurate accounts of the invasion process and effective conservation programs will depend on such considerations.

EXPLOITING TEMPORAL VARIABILITY TO UNDERSTAND TREE RECRUITMENT RESPONSE TO CLIMATE CHANGE

Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in the southern Appalachian Mountains. We monitored seedling establishment for 10 years in five plots located along an elevational gradient of five dominant tree species: Acer rubrum, Betula spp., Liriodendron tulipifera, Nyssa sylvatica, and Quercus rubra. A hierarchical Bayes model allowed us to incorporate different sources of information, observation errors, and the inherent variability of the establishment process. From our analysis, spring temperatures and heterogeneity in soil moisture emerge as key drivers, and they act through nonlinear population demographic processes. We found that all species benefited from warmer springs, in particular the species found on dry slopes, N. sylvatica, and those dominant at higher elevations, Betula spp. and Q. rubra. This last species also benefited from dry environments. Conversely, L. tulipifera, which is abundant on mesic sites, experienced highest establishment rates at high moisture. The mechanisms behind these results may differ among species. Higher temperatures are apparently more important for some, while dry conditions and reduced pathogenic attacks on their seeds and new seedlings have a large impact for others. Our results suggest that only communities found at higher elevations are in danger of regional extinction when their habitats disappear given the current climatic trends. We conclude that the recruitment dynamics of the communities where these species are dominant could be affected by minor changes in climate in ways that cannot be predicted using only climate envelopes, which use different variables and miss the nonlinearities.

COEXISTENCE: HOW TO IDENTIFY TROPHIC TRADE-OFFS

Analyses of growth response to resource availability are the basis for inter- preting whether trophic trade-offs contribute to diversity. If different species respond most to resources that are limiting at different times, then those differences may trade off with other trophic or life-history traits that, together, help to maintain diversity. The statistical models used to infer trophic differences do not accommodate uncertainty in resources and variability in how individuals use resources. We provide hierarchical models for resource- growth responses that accommodate stochasticity in parameters and in data, despite the fact that causes are typically unknown. A complex joint posterior distribution taken over > 102 parameters is readily integrated to provide a comprehensive accounting of uncertainty in the growth response, together with a small number of hyperparameters that summarize the population response. An application involving seedling growth response to light avail- ability shows that large trophic differences among species suggested by traditional models can be an artifact of the assumption that all individuals respond identically. The hierarchical analysis indicates broad trophic overlap, with the implication that slow dynamics play a more important role in preserving diversity than is widely believed.

TREE GROWTH INFERENCE AND PREDICTION FROM DIAMETER CENSUSES AND RING WIDTHS

Estimation of tree growth is based on sparse observations of tree diameter, ring widths, or increments read from a dendrometer. From annual measurements on a few trees (e.g., increment cores) or sporadic measurements from many trees (e.g., diameter censuses on mapped plots), relationships with resources, tree size, and climate are extrapolated to whole stands. There has been no way to formally integrate different types of data and problems of estimation that result from (1) multiple sources of observation error, which frequently result in impossible estimates of negative growth, (2) the fact that data are typically sparse (a few trees or a few years), whereas inference is needed broadly (many trees over many years), (3) the fact that some unknown fraction of the variance is shared across the population, and (4) the fact that growth rates of trees within competing stands are not independent. We develop a hierarchical Bayes state space model for tree growth that addresses all of these challenges, allowing for formal inference that is consistent with the available data and the assumption that growth is nonnegative. Prediction follows directly, incorporating the full uncertainty from inference with scenarios for filling the gaps for past growth rates and for future conditions affecting growth. An example involving multiple species and multiple stands with tree-ring data and up to 14 years of tree census data illustrates how different levels of information at the tree and stand level contribute to inference and prediction.

Positive and negative interactions between environmental conditions affecting Cercocarpus ledifolius seedling survival

We evaluated the balance between positive and negative effects of environmental conditions on first-year seedling survival of the tree Cercocarpus ledifolius during two summers, 1996 and 1997. The experimental design was fully crossed with two levels of water, with and without supplementation, two levels of herbivory, with and without protection, and three major microhabitats, open interspaces, under the canopy of Artemisia tridentata shrubs, and under the canopy of mature C. ledifolius trees. Effects of drought and herbivory on seedling survival depended on the year. Water supplementation and herbivory protection during the dry summer of 1996 (27.7xa0mm) generally increased seedling survival. Additionally, survival tended to be greatest beneath C. ledifolius canopies. More important ecologically were the significant interactions. In 1996, water supplementation increased survival more with than without herbivory protection. The three-way interaction, treatment-microhabitat combination, was most important; by far the greatest survival was in the water supplementation and herbivory protection in the tree microhabitat. During the wet summer of 1997 (158.5xa0mm), neither water supplementation, herbivory protection, nor microhabitat were significant as main effects. The water-supplemented and herbivory-protected treatment again combined to yield highest survival, but this time in open interspaces rather than beneath trees. Our study shows how the importance of individual limiting factors and the relative favorableness of particular microhabitats appear to change across years depending on environmental conditions.

Evaluating the sources of potential migrant species: implications under climate change.

As changes in climate become more apparent, ecologists face the challenge of predicting species responses to the new conditions. Most forecasts are based on climate envelopes (CE), correlative approaches that project future distributions on the basis of the current climate often assuming some dispersal lag. One major caveat with this approach is that it ignores the complexity of factors other than climate that contribute to a species distributional range. To overcome this limitation and to complement predictions based on CE modeling we carried out a transplant experiment of resident and potential-migrant species. Tree seedlings of 18 species were planted side by side from 2001 to 2004 at several locations in the Southern Appalachians and in the North Carolina Piedmont (U.S.A.). Growing seedlings under a large array of environmental conditions, including those forecasted for the next decades, allowed us to model seedling survival as a function of variables characteristic of each site, and from here we were able to make predictions on future seedling recruitment. In general, almost all species showed decreased survival in plots and years with lower soil moisture, including both residents and potential migrants, and in both locations, the Southern Appalachians and the Piedmont. The detrimental effects that anticipated arid conditions could have on seedling recruitment contradict some of the projections made by CE modeling, where many of the species tested are expected to increase in abundance or to expand their ranges. These results point out the importance of evaluating the potential sources of migrant species when modeling vegetation response to climate change, and considering that species adapted to the new climate and the local conditions may not be available in the surrounding regions.

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 approachs flexibility will be useful for forecasting ongoing phenological responses to changes in climate variability in addition to seasonal trends.