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Question: Is there a relationship between size and death in the Iona-lived, deep-rooted tree, Acacia erioloba, in a semi-arid savanna? What is the size-class distribution of A. erioloba mortality? Does the mortality distribution differ from total tree size distribution? Does A. erioloba mortality distribution match the mortality distributions recorded thus far in other environments? Location: Dronfield Ranch, near Kimberley, Kalahari, South Africa. Methods: A combination of aerial photographs and a satellite image covering 61 year was used to provide long-term spatial data on mortality. We used aerial photographs of the study area from 1940, 1964, 1984, 1993 and a satellite image from 2001 to follow three plots covering 510 ha. We were able to identify and individually follow ca. 3000 individual trees from 1940 till 2001. Results: The total number of trees increased over time. No relationship between total number of trees and mean tree size was detected. There were no trends over time in total number of deaths per plot or in size distributions of dead trees. Kolmogorov-Smirnov tests showed no differences in size class distributions for living trees through time. The size distribution of dead trees was significantly different from the size distribution of all trees present on the plots. Overall, the number of dead trees was low in small size classes, reached a peak value when canopy area was 20 - 30 m(2), and declined in lamer size-classes. Mortality as a ratio of dead vs. total trees peaked at intermediate canopy sizes too. Conclusion: A. erioloba mortality was size-dependent, peaking at intermediate sizes. The mortality distribution differs from all other tree mortality distributions recorded thus far. We suggest that a possible mechanism for this unusual mortality distribution is intraspecific competition for water in this semi-arid environment.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
Movement ecology aims to provide common terminology and an integrative framework of movement research across all groups of organisms. Yet such work has focused on unitary organisms so far, and thus the important group of filamentous fungi has not been considered in this context. With the exception of spore dispersal, movement in filamentous fungi has not been integrated into the movement ecology field. At the same time, the field of fungal ecology has been advancing research on topics like informed growth, mycelial translocations, or fungal highways using its own terminology and frameworks, overlooking the theoretical developments within movement ecology. We provide a conceptual and terminological framework for interdisciplinary collaboration between these two disciplines, and show how both can benefit from closer links: We show how placing the knowledge from fungal biology and ecology into the framework of movement ecology can inspire both theoretical and empirical developments, eventually leading towards a better understanding of fungal ecology and community assembly. Conversely, by a greater focus on movement specificities of filamentous fungi, movement ecology stands to benefit from the challenge to evolve its concepts and terminology towards even greater universality. We show how our concept can be applied for other modular organisms (such as clonal plants and slime molds), and how this can lead towards comparative studies with the relationship between organismal movement and ecosystems in the focus.
Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.
Resilience is a major research focus covering a wide range of topics from biodiversity conservation to ecosystem (service) management. Model simulations can assess the resilience of, for example, plant species, measured as the return time to conditions prior to a disturbance. This requires process-based models (PBM) that implement relevant processes such as regeneration and reproduction and thus successfully reproduce transient dynamics after disturbances. Such models are often complex and thus limited to either short-term or small-scale applications, whereas many research questions require species predictions across larger spatial and temporal scales. We suggest a framework to couple a PBM and a statistical species distribution model (SDM), which transfers the results of a resilience analysis by the PBM to SDM predictions. The resulting hybrid model combines the advantages of both approaches: the convenient applicability of SDMs and the relevant process detail of PBMs in abrupt environmental change situations. First, we simulate dynamic responses of species communities to a disturbance event with a PBM. We aggregate the response behavior in two resilience metrics: return time and amplitude of the response peak. These metrics are then used to complement long-term SDM projections with dynamic short-term responses to disturbance. To illustrate our framework, we investigate the effect of abrupt short-term groundwater level and salinity changes on coastal vegetation at the German Baltic Sea. We found two example species to be largely resilient, and, consequently, modifications of SDM predictions consisted mostly of smoothing out peaks in the occurrence probability that were not confirmed by the PBM. Discrepancies between SDM- and PBM-predicted species responses were caused by community dynamics simulated in the PBM and absent from the SDM. Although demonstrated with boosted regression trees (SDM) and an existing individual-based model, IBC-grass (PBM), our flexible framework can easily be applied to other PBM and SDM types, as well as other definitions of short-term disturbances or long-term trends of environmental change. Thus, our framework allows accounting for biological feedbacks in the response to short- and long-term environmental changes as a major advancement in predictive vegetation modeling.
Germination marks a critical transition in plant life that is prone to high mortality. Strong selection pressure is therefore expected to finely tune it to environmental conditions. Our study on the common Mediterranean grass Brachypodium hybridum assessed whether germination behavior changes systematically along a steep natural rainfall gradient ranging from harsh desert to rather mild mesic-Mediterranean conditions, We specifically tested hypotheses that germination behavior confers greater risk-spreading in populations from drier, unpredictable environments, and that seeds from wetter populations are better competitors. In 14 populations (spanning 114-954 mm annual rainfall) we assessed three alternative key parameters of germination in a greenhouse experiment: between-year dormancy, days to emergence within a season, and temporal spread. Addition of neighbor seeds accounted for competition as another crucial environmental factor. In six of the 14 populations, we also compared seeds originating from corresponding north (more mesic) and south (more arid) exposed hill slopes to test whether germination patterns along the large-scale rainfall gradient are paralleled at this smaller scale. B. hybridum exhibited generally high germination fractions and rapid emergence with very little temporal spread, indicating overall little risk-spreading germination. Surprisingly, none of the three parameters changed systematically with increasing aridity, neither at large scale along the rainfall gradient nor at small scale between north and south exposures. Neighbor seeds, however, mildly suppressed germination. Germination of neighbor seeds, in turn, was more strongly suppressed by B. hybridum seeds from drier populations, and this effect was stronger for forb than for grass neighbor species. Our results provide strong evidence that increased risk-spreading germination is not a universal, essential strategy to persist in increasingly dry, unpredictable environments. They also highlight that competition with neighbors occurs even at the earliest plant life stage. Since neighbor effects were species-specific, competition among seeds can affect community composition at later plant stages.
A challenge for eco-evolutionary research is to better understand the effect of climate and landscape changes on species and their distribution. Populations of species can respond to changes in their environment through local genetic adaptation or plasticity, dispersal, or local extinction. The individual-based modeling (IBM) approach has been repeatedly applied to assess organismic responses to environmental changes. IBMs simulate emerging adaptive behaviors from the basic entities upon which both ecological and evolutionary mechanisms act. The objective of this review is to summarize the state of the art of eco-evolutionary IBMs and to explore to what degree they already address the key responses of organisms to environmental change. In this, we identify promising approaches and potential knowledge gaps in the implementation of eco-evolutionary mechanisms to motivate future research. Using mainly the ISI Web of Science, we reveal that most of the progress in eco-evolutionary IBMs in the last decades was achieved for genetic adaptation to novel local environmental conditions. There is, however, not a single eco-evolutionary IBM addressing the three potential adaptive responses simultaneously. Additionally, IBMs implementing adaptive phenotypic plasticity are rare. Most commonly, plasticity was implemented as random noise or reaction norms. Our review further identifies a current lack of models where plasticity is an evolving trait. Future eco-evolutionary models should consider dispersal and plasticity as evolving traits with their associated costs and benefits. Such an integrated approach could help to identify conditions promoting population persistence depending on the life history strategy of organisms and the environment they experience.
Background
Organisms are expected to respond to changing environmental conditions through local adaptation, range shift or local extinction. The process of local adaptation can occur by genetic changes or phenotypic plasticity, and becomes especially relevant when dispersal abilities or possibilities are somehow constrained. For genetic changes to occur, mutations are the ultimate source of variation and the mutation rate in terms of a mutator locus can be subject to evolutionary change. Recent findings suggest that the evolution of the mutation rate in a sexual species can advance invasion speed and promote adaptation to novel environmental conditions. Following this idea, this work uses an individual-based model approach to investigate if the mutation rate can also evolve in a sexual species experiencing different conditions of directional climate change, under different scenarios of colored stochastic environmental noise, probability of recombination and of beneficial mutations. The color of the noise mimicked investigating the evolutionary dynamics of the mutation rate in different habitats.
Results
The results suggest that the mutation rate in a sexual species experiencing directional climate change scenarios can evolve and reach relatively high values mainly under conditions of complete linkage of the mutator locus and the adaptation locus. In contrast, when they are unlinked, the mutation rate can slightly increase only under scenarios where at least 50% of arising mutations are beneficial and the rate of environmental change is relatively fast. This result is robust under different scenarios of stochastic environmental noise, which supports the observation of no systematic variation in the mutation rate among organisms experiencing different habitats.
Conclusions
Given that 50% beneficial mutations may be an unrealistic assumption, and that recombination is ubiquitous in sexual species, the evolution of an elevated mutation rate in a sexual species experiencing directional climate change might be rather unlikely. Furthermore, when the percentage of beneficial mutations and the population size are small, sexual species (especially multicellular ones) producing few offspring may be expected to react to changing environments not by adaptive genetic change, but mainly through plasticity. Without the ability for a plastic response, such species may become – at least locally – extinct.
Background
Organisms are expected to respond to changing environmental conditions through local adaptation, range shift or local extinction. The process of local adaptation can occur by genetic changes or phenotypic plasticity, and becomes especially relevant when dispersal abilities or possibilities are somehow constrained. For genetic changes to occur, mutations are the ultimate source of variation and the mutation rate in terms of a mutator locus can be subject to evolutionary change. Recent findings suggest that the evolution of the mutation rate in a sexual species can advance invasion speed and promote adaptation to novel environmental conditions. Following this idea, this work uses an individual-based model approach to investigate if the mutation rate can also evolve in a sexual species experiencing different conditions of directional climate change, under different scenarios of colored stochastic environmental noise, probability of recombination and of beneficial mutations. The color of the noise mimicked investigating the evolutionary dynamics of the mutation rate in different habitats.
Results
The results suggest that the mutation rate in a sexual species experiencing directional climate change scenarios can evolve and reach relatively high values mainly under conditions of complete linkage of the mutator locus and the adaptation locus. In contrast, when they are unlinked, the mutation rate can slightly increase only under scenarios where at least 50% of arising mutations are beneficial and the rate of environmental change is relatively fast. This result is robust under different scenarios of stochastic environmental noise, which supports the observation of no systematic variation in the mutation rate among organisms experiencing different habitats.
Conclusions
Given that 50% beneficial mutations may be an unrealistic assumption, and that recombination is ubiquitous in sexual species, the evolution of an elevated mutation rate in a sexual species experiencing directional climate change might be rather unlikely. Furthermore, when the percentage of beneficial mutations and the population size are small, sexual species (especially multicellular ones) producing few offspring may be expected to react to changing environments not by adaptive genetic change, but mainly through plasticity. Without the ability for a plastic response, such species may become – at least locally – extinct.
Small livestock is an important resource for rural human populations in dry climates. How strongly will climate change affect the capacity of the rangeland? We used hierarchical modelling to scale quantitatively the growth of shrubs and annual plants, the main food of sheep and goats, to the landscape extent in the eastern Mediterranean region. Without grazing, productivity increased in a sigmoid way with mean annual precipitation. Grazing reduced productivity more strongly the drier the landscape. At a point just under the stocking capacity of the vegetation, productivity declined precipitously with more intense grazing due to a lack of seed production of annuals. We repeated simulations with precipitation patterns projected by two contrasting IPCC scenarios. Compared to results based on historic patterns, productivity and stocking capacity did not differ in most cases. Thus, grazing intensity remains the stronger impact on landscape productivity in this dry region even in the future.
Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations ( red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated ( white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme ( catastrophic) events can occur ( strong noise) or sensitivity is high ( overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk
In tropical West Africa, distribution patterns of forest islands in savannas are influenced by fires which occur regularly in the grass stratum. Along continuous forest-savanna transects in the Comoe National Park, the change in the amount and composition of non-woody phytomass was investigated from savanna to forest interior. This was correlated with the cover of vegetation strata above, soil depth, and the occurrence of seasonal surface fires. Phytomass mainly consisted of leaf litter in the forests (about 400 g m(-2) at the end of the rainy season, and about 600 g m(-2) at the end of the dry season) and of grasses in the savanna (about 900 g m(-2)). Low grass biomass appeared to be primarily the result of suppression by competing woody species and not of shallow soil. The occurrence of early dry-season fires seemed to be determined mainly by the amount of grass biomass as fuel because fires occurred in almost all savanna plots while forest sites remained unaffected. However, late dry-season fires will encounter higher amounts of leaf litter raising fire probability in forests. Due to the importance of the amount of combustible phytomass, fire probability and intensity might increase with annual precipitation in both savanna and forest
In semiarid savannas of Southern Africa current land use practices and climate change may lead to substantial changes of vegetation structure in the near future, however uncertainty remains about the potential consequences and the magnitude of change. In this paper we study the impact of climate change, cattle grazing, and wood cutting on shrub cover dynamics in savannas of the southern Kalahari. We use an established savanna ecosystem model to simulate landscape dynamics in terms of rainfall, fire and distribution of the dominant tree Acacia erioloba. We then incorporate these data into a spatial population model of the common, fleshy-fruited shrub Grewia flava and investigate shrub cover dynamics for a period of 100 years. Depending on the intensity of commercial wood cutting practices tree removal of A. erioloba led to a strong decline of the G. flava population, as shrub recruitment is concentrated in tree sub-canopies due to bird-mediated seed dispersal. Under climate change shrub cover slightly decreased with decreasing precipitation and was unchanged with increase in precipitation variability. Contrarily, grazing by cattle strongly increased shrub cover and facilitated shrub encroachment because of cattle-induced distribution of G. flava seeds into the matrix vegetation. Knowledge of the latter process is particularly important because shrub invasion is a major concern for conservation and savanna rangeland management as a result of its adverse effects on livestock carrying capacity and biodiversity
The impact of temporally correlated fluctuating environments (coloured noise) on the extinction risk of populations has become a main focus in theoretical population ecology. In this study we particularly focus on the extinction risk in strongly autocorrelated environments. Here, in contrast to moderate autocorrelation, we found the extinction risk to be highly dependent on the process of noise generation, in particular on the method of variance scaling. Such variance scaling is commonly applied to avoid variance-driven biases when comparing the extinction risk for white and coloured noise. In this study we found an often-used scaling technique to lead to high variability in the resulting variances of different time series for strong auto-correlation eventually leading to deviations in the projected extinction risk. Therefore, we present an alternative method that always delivers the target variance, even in the case of strong temporal correlation. Furthermore, in contrast to the earlier method, our very intuitive method is not bound to auto-regressive processes but can be applied to all types of coloured noises. We recommend the method introduced here to be used when the target of interest is the effect of noise colour on extinction risk not obscured by any variance effects.
Environmental heterogeneity is a major determinant of plant population dynamics. In semi-arid Kalahari savannas, heterogeneity is created by savanna structure, i.e. by the spatial arrangement and temporal dynamics of woody plant and open grassland microsites. We formulate a conceptual model describing the effects of savanna dynamics on the population dynamics of the animal-dispersed shrub Grewia flava. From empirical results we derive model rules describing effects of savanna structure on several processes in Grewia's life cycle. By formulating the model, we summarise existing information on Grewia demography and identify gaps in this knowledge. Despite a number of such gaps, the model can be used to make certain quantitative predictions. As an example, we apply the model to investigate the role of seed dispersal in Grewia encroachment on rangelands. Model results show that cattle promote encroachment by depositing substantial numbers of seeds in open areas, where Grewia is otherwise dispersal-limited. Finally, we draw some general conclusions about Grewia's life history and population dynamics. Under natural conditions, concentrated seed deposition under woody plants appears to be a key process causing the observed association between Grewia and other woody plants. Furthermore, low rates of recruitment and high adult survival result in slow-motion dynamics of Grewia populations. As a consequence, Grewia populations interact with savanna dynamics on long temporal and short to intermediate spatial scales.
Predicting the breeding success of large raptors in arid southern Africa : a first assessment
(2006)
Raptors are often priorities for conservation efforts and breeding success is a target measure for assessing their conservation status. The breeding success of large raptors in and southern Africa is thought to be higher in years of high rainfall. While this correlation has been found in several studies, it has not yet been shown for data from a wider geographical area. In conservation research, it is important to explore the differences between spatially- separated populations to estimate and to compare their conservation status, and to deduce specific management strategies. Using a theoretical approach, we develop a simplistic model to explain the breeding success-rainfall relationship in large African raptors at larger spatial scales. Secondly, we validate this model and we show that the inclusion of field data leads to consistent predictions. In particular, we recommend that the average size of the 'effective territory' should be included in the relationship between annual rainfall and breeding success of raptors in and southern Africa. Accordingly, we suggest that breeding success is a function of precipitation and inter- nest distance. We present a new measure of territory quality depending on rainfall and territory size. We suggest that our model provides a useful first approach to assess breeding success in large raptors of and southern Africa. However, we strongly emphasise the need to gather more data to further verify our model. A general problem in conservation research is to compare the status of populations assessed in different study areas under changing environmental conditions. Our simplistic approach indicates that this problem can be overcome by using a weighted evaluation of a target measure (i.e. breeding success), taking regional differences into account
The small fox tapeworm (Echinococcus multilocularis) shows a heterogeneous spatial distribution in the intermediate host (Microtus arvalis). To identify the ecological processes responsible for this heterogeneity, we developed a spatially explicit simulation model. The model combines individual-based (foxes, Vulpes vulpes) and grid- based (voles) techniques to simulate the infections in both intermediate and definite host. If host populations are homogeneously mixed, the model reproduces field data for parasite prevalence only for a limited number of parameter combinations. As ecological parameters inevitably vary to a certain degree, we discarded the homogeneous mixing model as insufficient to gain insight into the ecology of the fox tapeworm cycle. We analysed five different model scenarios, each focussing on an ecological process that might be responsible for the heterogeneous spatial distribution of E multilocularis in the intermediate host. Field studies revealed that the prevalence ratio between intermediate and definite host remains stable over a wide range of ecological conditions. Thus, by varying the parameters in simulation experiments, we used the robustness of the agreement between field data and model output as quality criterion for the five scenarios. Only one of the five scenarios was found to reproduce the prevalence ratio over a sufficient range of parameter combinations. In the accentuated scenario most tapeworm eggs die due to bad environmental conditions before they cause infections in the intermediate host. This scenario is supported by the known sensitivity of tapeworm eggs to high temperatures and dry conditions. The identified process is likely to lead to a heterogeneous availability of infective eggs and thus to a clumped distribution of infected intermediate hosts. In conclusion, areas with humid conditions and low temperatures must be pointed out as high risk areas for human exposure to E. multilocularis eggs as well. (C) 2004 on behalf of Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved
There is concern about the lack of recruitment of Acacia trees in the Negev desert of Israel. We have developed three models to estimate the frequency of recruitment necessary for long-term population survival (i.e. positive average population growth for 1,000 years and <10% probability of extinction). Two models assume purely episodic recruitment based on the general notion that recruitment in and environments is highly episodic. They differ in that the deterministic model investigates average dynamics while the stochastic model does not. Studies indicating that recruitment episodes in and environments have been overemphasized motivated the development of the third model. This semi-stochastic model simulates a mixture of continuous and episodic recruitment. Model analysis was done analytically for the deterministic model and via running model simulations for the stochastic and semi-stochastic models. The deterministic and stochastic models predict that, on average, 2.2 and 3.7 recruitment events per century, respectively, are necessary to sustain the population. According to the semi-stochastic model, 1.6 large recruitment events per century and an annual probability of 50% that a small recruitment event occurs are needed. A consequence of purely episodic recruitment is that all recruitment episodes produce extremely large numbers of recruits (i.e. at odds with field observations), an evaluation that holds even when considering that rare events must be large. Thus, the semi- stochastic model appears to be the most realistic model. Comparing the prediction of the semi-stochastic model to field observations in the Negev desert shows that the absence of observations of extremely large recruitment events is no reason for concern. However, the almost complete absence of small recruitment events is a serious reason for concern. The lack of recruitment may be due to decreased densities of large mammalian herbivores and might be further exacerbated by possible changes in climate, both in terms of average precipitation and the temporal distribution of rain
In ecology much attention has been paid towards seed dispersal of fleshy-fruited plants, however, knowledge is lacking about the Iona-term demographic consequences of variation in dispersal distance and fruit removal rate, particularly given the natural variability of the environment the organism lives in. In this study we used a spatially explicit, two-level stochastic computer model to simulate population dynamics of a fleshy-fruited shrub living in the sub-canopy of solitary savanna trees. On the landscape level we implemented three realistic scenarios of savanna landscape dynamics for a period of 500 years with equal inter-annual mean of environmental variables. The first scenario is representative of a relatively constant environment with normal variability in precipitation, constant tree density and random tree recruitment pattern. The second and third scenarios represent positive auto-correlated, cyclic patterns with alternating phases of tree cover increase and decrease corresponding with favorable and unfavorable rain phases. Our simulation experiments show that when fruit removal rate is extremely low, population persistence is enhanced under relatively constant rain conditions, while alternating rain phases of the cyclic scenarios lead to a significant population decrease. This result confirms previous findings that periodically fluctuating environments may increase local extinction risk. However, when dispersal distance is a limiting factor (whilst removal rate was sufficiently high), tree clumps typically forming in wet phases of both cyclic scenarios compensated for the negative effect of low dispersal distances, while the constant scenario with random tree pattern and larger inter-tree distances resulted in a significant population decline. (C) 2003 Elsevier B.V. All rights reserved
Shrub encroachment, i.e. the increase in woody plant cover, is a major concern for livestock farming in southern Kalahari savannas. We developed a grid-based computer model simulating the population dynamics of Grewia flava, a common, fleshy-fruited encroaching shrub. In the absence of large herbivores, seeds of Grewia are largely deposited in the sub-canopy of Acacia erioloba. Cattle negate this dispersal limitation by browsing on the foliage of Grewia and dispersing seeds into the grassland matrix. In this study we first show that model predictions of Grewia cover dynamics are realistic by comparing model output with shrub cover estimates obtained from a time series of aerial photographs. Subsequently, we apply a realistic range of intensity of cattle-induced seed dispersal combined with potential precipitation and fire scenarios. Based on the simulation results we suggest that cattle may facilitate shrub encroachment of Grewia. The results show that the severity of shrub encroachment is governed by the intensity of seed dispersal. For a high seed dispersal intensity without fire (equivalent to a high stocking rate) the model predicts 56% shrub cover and 85% cell cover after 100 yr. With fire both recruitment and shrub cover are reduced, which may, under moderate intensities, prevent shrub encroachment. Climate change scenarios with two-fold higher frequencies of drought and wet years intensified shrub encroachment rates, although long-term mean of precipitation remained constant. As a management recommendation we suggest that shrub encroachment on rangelands may be counteracted by frequent fires and controlling cattle movements to areas with a high proportion of fruiting Grewia shrubs
Köderauslageintervalle und Dauer der Bekämpfung des Kleinen Fuchsbandwurms : eine Modellierstudie
(2003)
Plants located adjacent to agricultural fields are important for maintaining biodiversity in semi-natural landscapes. To avoid undesired impacts on these plants due to herbicide application on the arable fields, regulatory risk assessments are conducted prior to registration to ensure proposed uses of plant protection products do not present an unacceptable risk. The current risk assessment approach for these non-target terrestrial plants (NTTPs) examines impacts at the individual-level as a surrogate approach for protecting the plant community due to the inherent difficulties of directly assessing population or community level impacts. However, modelling approaches are suitable higher tier tools to upscale individual-level effects to community level. IBC-grass is a sophisticated plant community model, which has already been applied in several studies. However, as it is a console application software, it was not deemed sufficiently user-friendly for risk managers and assessors to be conveniently operated without prior expertise in ecological models. Here, we present a user-friendly and open source graphical user interface (GUI) for the application of IBC-grass in regulatory herbicide risk assessment. It facilitates the use of the plant community model for predicting long-term impacts of herbicide applications on NTTP communities. The GUI offers two options to integrate herbicide impacts: (1) dose responses based on current standard experiments (acc. to testing guidelines) and (2) based on specific effect intensities. Both options represent suitable higher tier options for future risk assessments of NTTPs as well as for research on the ecological relevance of effects.
Natural grassland communities are threatened by a variety of factors, such as climate change and increasing land use by mankind. The use of plant protection products (synthetic or organic) is mandatory in agricultural food production. To avoid adverse effects on natural grasslands within agricultural areas, synthetic plant protection products are strictly regulated in Europe. However, effects of herbicides on non-target terrestrial plants are primarily studied on the level of individual plants neglecting interactions between species. In our study, we aim to extrapolate individual-level effects to the population and community level by adapting an existing spatio-temporal, individual-based plant community model (IBC-grass). We analyse the effects of herbicide exposure for three different grassland communities: 1) representative field boundary community, 2) Calthion grassland community, and 3) Arrhenatheretalia grassland community. Our simulations show that herbicide depositions can have effects on non-target plant communities resulting from direct and indirect effects on population level. The effect extent depends not only on the distance to the field, but also on the specific plant community, its disturbance regime (cutting frequency, trampling and grazing intensity) and resource level. Mechanistic modelling approaches such as IBC-grass present a promising novel approach in transferring and extrapolating standardized pot experiments to community level and thereby bridging the gap between ecotoxicological testing (e.g. in the greenhouse) and protection goals referring to real world conditions.
Potential impact of effects on reproductive attributes induced by herbicides on a plant community
(2018)
Current herbicide risk assessment guidelines for nontarget terrestrial plants require testing effects on young, vulnerable life stages (i.e., seedling emergence [and subsequent growth] and vegetative vigor [growth and dry wt]) but not directly on the reproduction of plants. However, the European Food Safety Authority (EFSA) has proposed that effects on reproduction might be considered when evaluating the potential effects on plants. We adapted the plant community model for grassland (IBC-grass) to give insight into the current debate on the sensitivity of reproductive versus vegetative endpoints in ecological risk assessment. In an extensive sensitivity analysis of this model, we compared plant attributes potentially affected by herbicides and the consequences for long-term plant population dynamics and plant diversity. This evaluation was implemented by reducing reproductive as well as vegetative endpoints by certain percentages (e.g., 10-90%) as a theoretical assumption. Plant mortality and seed sterility (i.e., inability of seeds to germinate) were the most sensitive attributes. Our results indicated that effects on seed production at off-field exposure rates must be very strong to have an impact on the risk assessment. Otherwise, effects on seed production are compensated for by the soil seed bank. The present study highlights the usefulness of community level modeling studies to support regulators in their decisions on the appropriate risk assessment endpoints and provides confidence in their assessments. Environ Toxicol Chem 2018;37:1707-1722. (c) 2018 SETAC
GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.
Aim Patterns that relate species richness with fragment area (the species-area relationship, SAR) and with isolation (the species-isolation relationship, SIR) are well documented. However, those that relate species density - the number of species within a standardized area - with fragment area (D-SAR) or isolation (D-SIR) have not been sufficiently explored, despite the potential for such an analysis to disentangle the underlying mechanisms of SARs and SIRs. Previous spatial theory predicts that a significant D-SAR or D-SIR is unlikely to emerge in taxa with high dispersal limitation, such as plants. Furthermore, a recent model predicts that the detection and the significance of D-SARs or D-SIRs may decrease with grain size. We combined a literature review with grain size-dependent sampling in a fragmented landscape to evaluate the prevalence and grain size-dependent nature of D-SARs and D-SIRs in plants. Location Worldwide (review) and a semi-arid agro-ecosystem in Israel (case study). Methods We combined an extensive literature review of 31 D-SAR studies of plants in fragmented landscapes with an empirical study in which we analysed grain size-dependent D-SARs and D-SIRs using a grain size-dependent hierarchical sampling of species density and species richness in a fragmented, semi-arid agro-ecosystem. Results We found that significantly increasing D-SARs are rare in plant studies. Furthermore, we found that the detection of a significant D-SAR is often possible only after the data have been stratified by species, habitat or landscape characteristics. The results from our case study indicated that the significance and the slopes of both D-SARs and D-SIRs increase as grain size decreases. Main conclusions These results call for a careful consideration of scale while analysing and interpreting the responses of species richness and species density to fragmentation. Our results suggest that grain size-dependent analyses of D-SARs and D-SIRs may help to disentangle the mechanisms that generate SARs and SIRs and may enable early detection of the effects of fragmentation on plant biodiversity.
Understanding the regional dynamics of plant communities is crucial for predicting the response of plant diversity to habitat fragmentation. However, for fragmented landscapes the importance of regional processes, such as seed dispersal among isolated habitat patches, has been controversially debated. Due to the stochasticity and rarity of among-patch dispersal and colonization events, we still lack a quantitative understanding of the consequences of these processes at the landscape-scale. In this study, we used extensive field data from a fragmented, semi-arid landscape in Israel to parameterize a multi-species incidence-function model. This model simulates species occupancy pattern based on patch areas and habitat configuration and explicitly considers the locations and the shapes of habitat patches for the derivation of patch connectivity. We implemented an approximate Bayesian computation approach for parameter inference and uncertainty assessment. We tested which of the three types of regional dynamics - the metacommunity, the mainland-island, or the island communities type - best represents the community dynamics in the study area and applied the simulation model to estimate the extinction debt in the investigated landscape. We found that the regional dynamics in the patch-matrix study landscape is best represented as a system of highly isolated island' communities with low rates of propagule exchange among habitat patches and consequently low colonization rates in local communities. Accordingly, the extinction rates in the local communities are the main drivers of community dynamics. Our findings indicate that the landscape carries a significant extinction debt and in model projections 33-60% of all species went extinct within 1000 yr. Our study demonstrates that the combination of dynamic simulation models with field data provides a promising approach for understanding regional community dynamics and for projecting community responses to habitat fragmentation. The approach bears the potential for efficient tests of conservation activities aimed at mitigating future losses of biodiversity.
Quantifying the association of plant functional traits to environmental gradients is a promising approach for understanding and projecting community responses to land use and climatic changes. Although habitat fragmentation and climate are expected to affect plant communities interactively, there is a lack of empirical studies addressing trait associations to fragmentation in different climatic regimes.
In this study, we analyse data on the key functional traits: specific leaf area (SLA), plant height, seed mass and seed number. First, we assess the evidence for the community assembly mechanisms habitat filtering and competition at different spatial scales, using several null-models and a comprehensive set of community-level trait convergence and divergence indices. Second, we analyse the association of community-mean traits with patch area and connectivity along a south-north productivity gradient.
We found clear evidence for trait convergence due to habitat filtering. In contrast, the evidence for trait divergence due to competition fundamentally depended on the null-model used. When the null-model controlled for habitat filtering, there was only evidence for trait divergence at the smallest sampling scale (0.25 m x 0.25 m). All traits varied significantly along the S-N productivity gradient. While plant height and SLA were consistently associated with fragmentation, the association of seed mass and seed number with fragmentation changed along the S-N gradient.
Our findings indicate trait convergence due to drought stress in the arid sites and due to higher productivity in the mesic sites. The association of plant traits to fragmentation is likely driven by increased colonization ability in small and/or isolated patches (plant height, seed number) or increased persistence ability in isolated patches (seed mass).
Our study provides the first empirical test of trait associations with fragmentation along a productivity gradient. We conclude that it is crucial to study the interactive effects of different ecological drivers on plant functional traits.
In European dry grasslands land-use changes affect plant species performance and frequency. Potential driving forces are eutrophication and habitat fragmentation. The importance of these factors is presumably scale dependent. We used a functional trait approach to detect processes that influence species frequency and endangerment on different spatial scales. We tested for associations between functional traits and (1) frequency and (2) degree of endangerment on local, regional and national scales. We focussed on five selected traits that describe the life-history of plant species and that are related to competition, dispersal ability and habitat specificity. Trait data on plant height, SLA, plant coverage, peak of flowering and diaspore mass were measured for 28 perennials from common to rare and endangered to non-endangered on 59 dry grassland sites in north-eastern Germany. Multiple regression models revealed that species frequency is positively and species endangerment negatively related to plant height, plant coverage and SLA on more than one spatial scale. On the local scale, diaspore mass has a negative effect on species frequency. More frequent and less endangered species show a later peak of flowering on nationwide and regional scales. We concluded that competition traits are more important on larger scales, whereas dispersal traits are more important for species frequency on the smaller scale. On national and regional scales, eutrophication and habitat loss may be the main drivers of species threat, whereas on the local scale fragmentation plays a crucial role for the performance of dry grassland species.
Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.
Home range size and resource use of breeding and non-breeding white storks along a land use gradient
(2018)
Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.
Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user-friendly implementation of the well-established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species’ response to global environmental change.
Small livestock is an important resource for rural human populations in dry climates. How strongly will climate change affect the capacity of the rangeland? We used hierarchical modelling to scale quantitatively the growth of shrubs and annual plants, the main food of sheep and goats, to the landscape extent in the eastern Mediterranean region. Without grazing, productivity increased in a sigmoid way with mean annual precipitation. Grazing reduced productivity more strongly the drier the landscape. At a point just under the stocking capacity of the vegetation, productivity declined precipitously with more intense grazing due to a lack of seed production of annuals. We repeated simulations with precipitation patterns projected by two contrasting IPCC scenarios. Compared to results based on historic patterns, productivity and stocking capacity did not differ in most cases. Thus, grazing intensity remains the stronger impact on landscape productivity in this dry region even in the future.
1. Migration conveys an immense challenge, especially for juvenile birds coping with enduring and risky journeys shortly after fledging. Accordingly, juveniles exhibit considerably lower survival rates compared to adults, particularly during migration. Juvenile white storks (Ciconia ciconia), which are known to rely on adults during their first fall migration presumably for navigational purposes, also display much lower annual survival than adults.
2. Using detailed GPS and body acceleration data, we examined the patterns and potential causes of age-related differences in fall migration properties of white storks by comparing first-year juveniles and adults. We compared juvenile and adult parameters of movement, behaviour and energy expenditure (estimated from overall dynamic body acceleration) and placed this in the context of the juveniles’ lower survival rate.
3. Juveniles used flapping flight vs. soaring flight 23% more than adults and were estimated to expend 14% more energy during flight. Juveniles did not compensate for their higher flight costs by increased refuelling or resting during migration. When juveniles and adults migrated together in the same flock, the juvenile flew mostly behind the adult and was left behind when they separated. Juveniles showed greater improvement in flight efficiency throughout migration compared to adults which appears crucial because juveniles exhibiting higher flight costs suffered increased mortality.
4. Our findings demonstrate the conflict between the juveniles’ inferior flight skills and their urge to keep up with mixed adult–juvenile flocks. We suggest that increased flight costs are an important proximate cause of juvenile mortality in white storks and likely in other soaring migrants and that natural selection is operating on juvenile variation in flight efficiency.
The cover of large trees in African savannahs is rapidly declining, mainly due to human land-use practices. Trees improve grass nutrient quality and contribute to species and structural diversity of savannah vegetation. However, the response of herbivores to trees as habitat features is unknown We quantified the habitat use of wild and domestic ungulates in two eastern and southern African savannahs. We assessed grazing intensities and quantified dung depositions beneath and around canopies of different sized trees. Grasses were eaten and dung was deposited twice as frequently beneath large (ca. 5 m in height) and very large trees (7-10 m) than in open grasslands. Small trees (<2.5 m) did not show this trend. Grazing intensity and dung deposition decreased with distance away from trees at both study sites. These results suggest that large trees represent essential habitat features for domestic and wild herbivores. Increased dung depositions beneath large trees may further promote the maintenance of a patchy nutrient distribution in savannahs. Small trees cannot provide the same structural and functional advantages as large trees do. We recommend that land-use practices be promoted which conserve large single-standing trees to benefit the flora and fauna of African savannahs.
Drylands worldwide are exposed to a highly variable environment and face a high risk of degradation. The effects of global climate change such as altered precipitation patterns and increased temperature leading to reduced water availability will likely increase this risk. At the same time, an elevated atmospheric CO2 level could mitigate the effects of reduced water availability by increasing the water use efficiency of plants. To prevent degradation of drylands, it is essential to understand the underlying processes that affect water availability and vegetation cover. Since water and vegetation are strongly interdependent in water-limited ecosystems, changes can lead to highly non- linear effects. We assess these effects by developing an ecohydrological model of soil moisture and vegetation cover. The water component of the model simulates the daily dynamics of surface water and water contents in two soil layers. Vegetation is represented by two functional types: shrubs and grasses. These compete for soil water and strongly influence hydrological processes. We apply the model to a Namibian thornbush savanna and evaluate the separate and combined effects of decreased annual precipitation, increased temperature, more variable precipitation and elevated atmospheric CO2 on soil moisture and on vegetation cover. The results show that two main factors control the response of plant types towards climate change, namely a change in water availability and a change in water allocation to a specific plant type. Especially, reduced competitiveness of grasses can lead to a higher risk of shrub encroachment in these systems.
Fragmentation and loss of habitat are major threats to animal communities and are therefore important to conservation. Due to the complexity of the interplay of spatial effects and community processes, our mechanistic understanding of how communities respond to such landscape changes is still poor. Modelling studies have mostly focused on elucidating the principles of community response to fragmentation and habitat loss at relatively large spatial and temporal scales relevant to metacommunity dynamics. Yet, it has been shown that also small scale processes, like foraging behaviour, space use by individuals and local resource competition are also important factors. However, most studies that consider these smaller scales are designed for single species and are characterized by high model complexity. Hence, they are not easily applicable to ecological communities of interacting individuals. To fill this gap, we apply an allometric model of individual home range formation to investigate the effects of habitat loss and fragmentation on mammal and bird communities, and, in this context, to investigate the role of interspecific competition and individual space use. Results show a similar response of both taxa to habitat loss. Community composition is shifted towards higher frequency of relatively small animals. The exponent and the 95%-quantile of the individual size distribution (ISD, described as a power law distribution) of the emerging communities show threshold behaviour with decreasing habitat area. Fragmentation per se has a similar and strong effect on mammals, but not on birds. The ISDs of bird communities were insensitive to fragmentation at the small scales considered here. These patterns can be explained by competitive release taking place in interacting animal communities, with the exception of bird's buffering response to fragmentation, presumably by adjusting the size of their home ranges. These results reflect consequences of higher mobility of birds compared to mammals of the same size and the importance of considering competitive interaction, particularly for mammal communities, in response to landscape fragmentation. Our allometric approach enables scaling up from individual physiology and foraging behaviour to terrestrial communities, and disentangling the role of individual space use and interspecific competition in controlling the response of mammal and bird communities to landscape changes.