Chaos is not rare in natural ecosystems

Chaotic dynamics are thought to be rare in natural populations but this may be due to methodological and data limitations, rather than the inherent stability of ecosystems. Following extensive simulation testing, we applied multiple chaos detection methods to a global database of 172 population time series and found evidence for chaos in >30%. In contrast, fitting traditional one-dimensional models identified <10% as chaotic. Chaos was most prevalent among plankton and insects and least among birds and mammals. Lyapunov exponents declined with generation time and scaled as the -1/6 power of body mass among chaotic populations. These results demonstrate that chaos is not rare in natural populations, indicating that there may be intrinsic limits to ecological forecasting and cautioning against the use of steady-state approaches to conservation and management.

Agricultural intensification and climate change have increased the threat from weeds

Weeds represent a significant threat to crop yields and global food security. We analysed data on weed competition from the world's longest running agricultural experiment to ask whether potential yield losses from weeds have increased in response to management and environmental change since the advent of the Green Revolution in the 1960s. On plots where inorganic nitrogen fertiliser has been applied, potential yield losses from weeds have consistently increased since 1969. This was explained by a warming climate, measured as air temperature averaged over the growing season for the weeds, and a shift towards shorter crop cultivars. Weeds also reduced yield proportionally more on plots with higher rates of nitrogen which had higher yields when weeds were controlled; the relative benefit of herbicides was, therefore, proportional to potential crop yield. Reducing yield losses from weed competition is increasingly challenging because of the evolution of herbicide resistance. Our results demonstrate that weeds now represent a greater inherent threat to crop production than before the advent of herbicides and integrated, sustainable solutions to weed management are urgently needed to protect the high yield potential of modern crop genotypes.

Limited contributions of plant pathogens to density-dependent seedling mortality of mast fruiting Bornean trees

Fungal pathogens are implicated in driving tropical plant diversity by facilitating strong, negative density-dependent mortality of conspecific seedlings (C-NDD). Assessment of the role of fungal pathogens in mediating coexistence derives from relatively few tree species and predominantly the Neotropics, limiting our understanding of their role in maintaining hyper-diversity in many tropical forests. A key question is whether fungal pathogen-mediated C-NDD seedling mortality is ubiquitous across diverse plant communities. Using a manipulative shadehouse experiment, we tested the role of fungal pathogens in mediating C-NDD seedling mortality of eight mast fruiting Bornean trees, typical of the species-rich forests of South East Asia. We demonstrate species-specific responses of seedlings to fungicide and density treatments, generating weak negative density-dependent mortality. Overall seedling mortality was low and likely insufficient to promote overall community diversity. Although conducted in the same way as previous studies, we find little evidence that fungal pathogens play a substantial role in determining patterns of seedling mortality in a SE Asian mast fruiting forest, questioning our understanding of how Janzen-Connell mechanisms structure the plant communities of this globally important forest type.

Legacy of historic ozone exposure on plant community and food web structure

Information on whole community responses is needed to predict direction and magnitude of changes in plant and animal abundance under global changes. This study quantifies the effect of past ozone exposure on a weed community structure and arthropod colonization. We used the soil seed bank resulting from a long-term ozone exposure to reestablish the plant community under a new low-pollution environment. Two separate experiments using the same original soil seed bank were conducted. Plant and arthropod richness and species abundance was assessed during two years. We predicted that exposure to episodic high concentrations of ozone during a series of growing cycles would result in plant assemblies with lower diversity (lower species richness and higher dominance), due to an increase in dominance of the stress tolerant species and the elimination of the ozone-sensitive species. As a consequence, arthropod-plant interactions would also be changed. Species richness of the recruited plant communities from different exposure histories was similar (≈ 15). However, the relative abundance of the dominant species varied according to history of exposure, with two annual species dominating ozone enriched plots (90 ppb: Spergula arvensis, and 120 ppb: Calandrinia ciliata). Being consistent both years, the proportion of carnivore species was significantly higher in plots with history of higher ozone concentration (≈3.4 and ≈7.7 fold higher in 90 ppb and 120 ppb plots, respectively). Our study provides evidence that, past history of pollution might be as relevant as management practices in structuring agroecosystems, since we show that an increase in tropospheric ozone may influence biotic communities even years after the exposure.

Ability of matrix models to explain the past and predict the future of plant populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Climate effects and feedback structure determining weed population dynamics in a long-term experiment

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements.

A field test of inverse modeling of seed dispersal

PREMISE OF THE STUDY

Seed dispersal distance-a key process in plant population dynamics-remains poorly understood because of the difficulty of finding a source plant so well isolated from conspecifics that seeds or seedlings can be unambiguously attributed to it. Inverse modeling (IM) of seed dispersal, a simple statistical technique for parameterizing dispersal kernels, has been widely used since 1992; surprisingly, however, this approach has never been verified in the field.

METHODS

We released from 20 nearby trees the winged seeds of a liana species, Entada polystachya, near the coast in a tropical, dry forest in Jalisco, Mexico.

KEY RESULTS

With a two-parameter log-normal function, we found that IM predicted both the shape and scale parameters well as long as we used the entire data set. When, however, we subsampled (thus simulating the use of transects for seedlings or an array of seed traps), the estimates of the scale and shape parameters were often more than double the real values. The problem was due to the marked anisotropy (directional bias; in this case, in the direction of the diurnal sea breeze) of the individual dispersal curves. When we randomized the direction of dispersal of individual seeds from the trees (keeping dispersal distances unchanged), predictions of parameter values were excellent.

CONCLUSIONS

Inverse modeling must include directional parameters when dealing with areas where strong anisotropy is to be expected, e.g., for wind dispersal of seeds near coasts or pollination by any vector where a plant species is limited to a strongly linear habitat such as river banks.

Density-structured models for plant population dynamics

Density-structured models are structured population models in which the state variable is the proportion of populations or sites in a small number of discrete density states. Although such models have rarely been used, they have the advantage that they are straightforward to parameterize, make few assumptions about population dynamics, and permit rapid data collection using coarse density assessment. In this article, we highlight their use in relating population dynamics to environmental variation and their robustness to measurement error. We show that density-structured models are able to accurately represent population dynamics under a wide range of conditions. We look at the effects of including a persistent seedbank and describe numerical approximations for the mean and variance of population size. For simulated data, we determine the extent to which the underlying continuous process may be inferred from density-structured data. Finally, we discuss issues of parameter estimation and applications for which these types of models may be useful.

Testing the Janzen-Connell mechanism: pathogens cause overcompensating density dependence in a tropical tree

The Janzen-Connell hypothesis is a leading explanation for plant-species diversity in tropical forests. It suggests that specialized natural enemies decrease offspring survival at high densities beneath parents, giving locally rarer species an advantage. This mechanism, in its original form, assumes that density dependence is overcompensating: mortality must be disproportionately high at the highest densities, with few offspring recruiting below their parents. We tested this assumption using parallel shadehouse and field density-series experiments on seedlings of a tropical tree, Pleradenophora longicuspis. We found strong, overcompensating mortality driven by fungal pathogens, causing 90% (shadehouse) or 100% (field) mortality within 4 weeks of germination, and generating a negative relationship between initial and final seedling densities. Fungicide treatment led to much lower, density-independent, mortality. Overcompensating mortality was extremely rapid, and could be missed without detailed monitoring. Such dynamics may prevent dead trees from being replaced by conspecifics, promoting coexistence as envisioned by the Janzen-Connell hypothesis.

Pathogens, density dependence and the coexistence of tropical trees

There is increasing interest in the role played by density-dependent mortality from natural enemies, particularly plant pathogens, in promoting the coexistence and diversity of tropical trees. Here, we review four issues in the analysis of pathogen-induced density dependence that have been overlooked or inadequately addressed. First, the methodology for detecting density dependence must be robust to potential biases. Observational studies, in particular, require a careful analysis to avoid biases generated by measurement error, and existing studies could be criticized on these grounds. Experimental studies manipulating plant density and pathogen incidence will often be preferable, or should be run in parallel. Second, the form of density dependence is not well understood and, in particular, there are no data indicating whether pathogens cause compensating or overcompensating density responses. Owing to this, we argue that the potential for pathogen-induced density dependence to generate diversity-enhancing outcomes, such as the Janzen-Connell effect, remains uncertain, as coexistence is far more probable if density dependence is overcompensating. Third, there have been few studies examining the relative importance of intra- or interspecific density dependence resulting from pathogens (or, more widely, natural enemies). This is essentially equivalent to asking to what extent pathogens are host-specific. If pathogens are generalists, then mortality rates will respond to overall plant density, irrespective of plant species identity. This will weaken the intraspecific density dependence and reduce the diversity-promoting effects of pathogens. Finally, we highlight the need for studies that integrate observations and experiments on pathogens and density dependence into the whole life cycle of trees, because as yet it is not possible to be certain of the degree to which pathogens contribute to observed dynamics.

Population Cycles Produced by Delayed Density Dependence in an Annual Plant

In contrast to insect and animal populations, little attention has been directed to the study of cycles in plant populations. It has been argued on theoretical grounds that plants present stable dynamics. Nevertheless, there are examples where plant populations appear to exhibit oscillatory dynamics, but the oscillatory signal is variable and comes from very short time series data. Using a combination of time series, models, and empirical results, we present evidence of population cycles for Descurania sophia in a 16-year field experiment. Endogenous and exogenous causal mechanisms were studied to identify processes underlying this temporal dynamic. Our results show a 4-year cycle produced by delayed density dependence. We suggest that high nutrient levels might be responsible for the observed dynamics of D. sophia. Our results suggest that although plant population dynamics may be stabilized by direct density dependence, delayed density dependence could destabilize dynamics.

Characterising spatial and temporal variation in the finite rate of population increase across the northern range boundary of the annual grass Vulpia fasciculata

Understanding the factors that influence plant distributions is a considerable challenge for ecologists in the face of environmental change. Here, we quantify spatial and temporal variation in the finite rate of population increase of the annual grass Vulpia fasciculata. Specifically, we test the hypothesis that the northern range boundary is associated with finite rates of population increase of less than one. Seeds of three ecotypes of the annual grass V. fasciculata were introduced annually across a range of sites in Great Britain both within (11) and to the north (4) of its current range boundary in each of 4 years. Populations failed to establish at 17% of target sites due to disturbance. At the remaining target sites, the finite rate of population increase, lambda, varied from 0.06 to 33.3 with a geometric mean of 1.88. Of the total variance in the rate of population growth, site and year effects accounted independently for 40% of the variation and in interaction for 50%; ecotype accounted for less than 5% of the variation. Variation in the weather between sites and years had little impact on plant performance, and there was no indication that the rate of population growth was lower to the north of the current range boundary. We conclude that current climatic conditions on the coast of Great Britain are not limiting the distribution of V. fasciculata and that seeds from across its current range have roughly equivalent colonising potential.

The Evolution of Oscillatory Behavior in Age‐Structured Species

A major challenge in ecology is to explain why so many species show oscillatory population dynamics and why the oscillations commonly occur with particular periods. The background environment, through noise or seasonality, is one possible driver of these oscillations, as are the components of the trophic web with which the species interacts. However, the oscillation may also be intrinsic, generated by density-dependent effects on the life history. Models of structured single-species systems indicate that a much broader range of oscillatory behavior than that seen in nature is theoretically possible. We test the hypothesis that it is selection that acts to constrain the range of periods. We analyze a nonlinear single-species matrix model with density dependence affecting reproduction and with trade-offs between reproduction and survival. We show that the evolutionarily stable state is oscillatory and has a period roughly twice the time to maturation, in line with observed patterns of periodicity. The robustness of this result to variations in trade-off function and density dependence is tested.

Dynamics in a discrete two-species competition model: coexistence and over-compensation

The dynamic features of an over-compensating discrete two-species competition system with stable coexistence are recaptured, and it is shown how the probabilities of the different possible ecological scenarios, e.g. coexistence, may be calculated when the assumption of no over-compensation is loosened. A Bayesian methodology for calculating the probability that stable oscillations or chaos may occur in plant populations or communities is outlined. The methodology is exemplified using an experimental population of Arabidopsis thaliana. It is concluded that, when making ecological predictions it is preferable and possibly important to test for the possibility of chaotic population dynamics due to over-compensation rather than assuming a priori that over-compensation does not occur.

Weeds in fields with contrasting conventional and genetically modified herbicide-tolerant crops. II. Effects on individual species

We compared the effects of the management of genetically modified herbicide-tolerant (GMHT) and conventional beet, maize and spring oilseed rape on 12 weed species. We sampled the seedbank before and after cropping. During the season we counted plants and measured seed rain and biomass. Ratios of densities were used to calculate emergence, survival, reproduction and seedbank change. Treatments significantly affected the biomass of six species in beet, eight in maize and five in spring oilseed rape. The effects were generally consistent, with biomass lower in GMHT beet and spring oilseed rape and higher in GMHT maize. With few exceptions, emergence was higher in GMHT crops. Subsequent survival was significantly lowered for eight species in beet and six in spring oilseed rape in the GMHT treatments. It was increased for five species in maize and one in spring oilseed rape. Significant effects on seedbank change were found for four species. However, for many species in beet and spring oilseed rape (19 out of 24 cases), seed densities were lower in the seedbank after GMHT cropping. These differences compounded over time would result in large decreases in population densities of arable weeds. In maize, populations may increase.