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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
Land-use intensification is the main factor for the catastrophic decline of insect pollinators. However, land-use intensification includes multiple processes that act across various scales and should affect pollinator guilds differently depending on their ecology. We aimed to reveal how two main pollinator guilds, wild bees and hoverflies, respond to different land-use intensification measures, that is, arable field cover (AFC), landscape heterogeneity (LH), and functional flower composition of local plant communities as a measure of habitat quality. We sampled wild bees and hoverflies on 22 dry grassland sites within a highly intensified landscape (NE Germany) within three campaigns using pan traps. We estimated AFC and LH on consecutive radii (60-3000 m) around the dry grassland sites and estimated the local functional flower composition. Wild bee species richness and abundance was positively affected by LH and negatively by AFC at small scales (140-400 m). In contrast, hoverflies were positively affected by AFC and negatively by LH at larger scales (500-3000 m), where both landscape parameters were negatively correlated to each other. At small spatial scales, though, LH had a positive effect on hoverfly abundance. Functional flower diversity had no positive effect on pollinators, but conspicuous flowers seem to attract abundance of hoverflies. In conclusion, landscape parameters contrarily affect two pollinator guilds at different scales. The correlation of landscape parameters may influence the observed relationships between landscape parameters and pollinators. Hence, effects of land-use intensification seem to be highly landscape-specific.
Land-use intensification is the main factor for the catastrophic decline of insect pollinators. However, land-use intensification includes multiple processes that act across various scales and should affect pollinator guilds differently depending on their ecology. We aimed to reveal how two main pollinator guilds, wild bees and hoverflies, respond to different land-use intensification measures, that is, arable field cover (AFC), landscape heterogeneity (LH), and functional flower composition of local plant communities as a measure of habitat quality. We sampled wild bees and hoverflies on 22 dry grassland sites within a highly intensified landscape (NE Germany) within three campaigns using pan traps. We estimated AFC and LH on consecutive radii (60–3000 m) around the dry grassland sites and estimated the local functional flower composition. Wild bee species richness and abundance was positively affected by LH and negatively by AFC at small scales (140–400 m). In contrast, hoverflies were positively affected by AFC and negatively by LH at larger scales (500–3000 m), where both landscape parameters were negatively correlated to each other. At small spatial scales, though, LH had a positive effect on hoverfly abundance. Functional flower diversity had no positive effect on pollinators, but conspicuous flowers seem to attract abundance of hoverflies. In conclusion, landscape parameters contrarily affect two pollinator guilds at different scales. The correlation of landscape parameters may influence the observed relationships between landscape parameters and pollinators. Hence, effects of land-use intensification seem to be highly landscape-specific.
Land-use intensification is the main factor for the catastrophic decline of insect pollinators. However, land-use intensification includes multiple processes that act across various scales and should affect pollinator guilds differently depending on their ecology. We aimed to reveal how two main pollinator guilds, wild bees and hoverflies, respond to different land-use intensification measures, that is, arable field cover (AFC), landscape heterogeneity (LH), and functional flower composition of local plant communities as a measure of habitat quality. We sampled wild bees and hoverflies on 22 dry grassland sites within a highly intensified landscape (NE Germany) within three campaigns using pan traps. We estimated AFC and LH on consecutive radii (60–3000 m) around the dry grassland sites and estimated the local functional flower composition. Wild bee species richness and abundance was positively affected by LH and negatively by AFC at small scales (140–400 m). In contrast, hoverflies were positively affected by AFC and negatively by LH at larger scales (500–3000 m), where both landscape parameters were negatively correlated to each other. At small spatial scales, though, LH had a positive effect on hoverfly abundance. Functional flower diversity had no positive effect on pollinators, but conspicuous flowers seem to attract abundance of hoverflies. In conclusion, landscape parameters contrarily affect two pollinator guilds at different scales. The correlation of landscape parameters may influence the observed relationships between landscape parameters and pollinators. Hence, effects of land-use intensification seem to be highly landscape-specific.
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.
Aim This study aims to link demographic traits and post-glacial recolonization processes with genetic traits in Himantoglossum hircinum (L.) Spreng (Orchidaceae), and to test the implications of the central-marginal concept (CMC) in Europe. Location Twenty sites covering the entire European distribution range of this species. Methods We employed amplified fragment length polymorphism (AFLP) markers and performed a plastid microsatellite survey to assess genetic variation in 20 populations of H. hircinum located along central-marginal gradients. We measured demographic traits to assess population fitness along geographical gradients and to test for correlations between demographic traits and genetic diversity. We used genetic diversity indices and analyses of molecular variance (AMOVA) to test hypotheses of reduced genetic diversity and increased genetic differentiation and isolation from central to peripheral sites. We used Bayesian simulations to analyse genetic relationships among populations. Results Genetic diversity decreased significantly with increasing latitudinal and longitudinal distance from the distribution centre when excluding outlying populations. The AMOVA revealed significant genetic differentiation among populations (F-ST = 0.146) and an increase in genetic differentiation from the centre of the geographical range to the margins (except for the Atlantic group). Population fitness, expressed as the ratio N-R/N, decreased significantly with increasing latitudinal distance from the distribution centre. Flower production was lower in most eastern peripheral sites. The geographical distribution of microsatellite haplotypes suggests post-glacial range expansion along three major migratory pathways, as also supported by individual membership fractions in six ancestral genetic clusters (C1-C6). No correlations between genetic diversity (e.g. diversity indices, haplotype frequency) and population demographic traits were detected. Main conclusions Reduced genetic diversity and haplotype frequency in H. hircinum at marginal sites reflect historical range expansions. Spatial variation in demographic traits could not explain genetic diversity patterns. For those sites that did not fit into the CMC, the genetic pattern is probably masked by other factors directly affecting either demography or population genetic structure. These include post-glacial recolonization patterns and changes in habitat suitability due to climate change at the northern periphery. Our findings emphasize the importance of distinguishing historical effects from those caused by geographical variation in population demography of species when studying evolutionary and ecological processes at the range margins under global change.
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity
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.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
Habitat loss poses a severe threat to biodiversity. While many studies yield valuable information on how specific species cope with such environmental modification, the mechanistic understanding of how interacting species or whole communities are affected by habitat loss is still poor. Individual movement plays a crucial role for the space use characteristics of species, since it determines how individuals perceive and use their heterogeneous environment. At the community level, it is therefore essential to include individual movement and how it is influenced by resource sharing into the investigation of consequences of habitat loss. To elucidate the effects of foraging movement on communities in face of habitat loss, we here apply a recently published spatially-explicit and individual-based model of home range formation. This approach allows predicting the individual size distribution (ISD) of mammal communities in simulation landscapes that vary in the amount of suitable habitat. We apply three fundamentally different foraging movement approaches (central place forager (CPF), patrolling forager (PF) and body mass dependent nomadic forager (BNF)). Results show that the efficiency of the different foraging strategies depends on body mass, which again affects community structure in face of habitat loss. CPF is only efficient for small animals, and therefore yields steep ISD exponents on which habitat loss has little effect (due to a movement limitation of body mass). PF and particularly BNF are more efficient for larger animals, resulting in less steep ISDs with higher mass maxima, both showing a threshold behaviour with regard to loss of suitable habitat. These findings represent a new way of explaining observed extinction thresholds, and therefore indicate the importance of individual space use characterized by physiology and behaviour, i.e. foraging movement, for communities and their response to habitat loss. Findings also indicate the necessity to incorporate the crucial role of movement into future conservation efforts of terrestrial communities.
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
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.
The predicted climate change causes deep concerns on the effects of increasing temperatures and changing precipitation patterns on species viability and, in turn, on biodiversity. Models of Population Viability Analysis (PVA) provide a powerful tool to assess the risk of species extinction. However, most PVA models do not take into account the potential effects of behavioural adaptations. Organisms might adapt to new environmental situations and thereby mitigate negative effects of climate change. To demonstrate such mitigation effects, we use an existing PVA model describing a population of the tawny eagle (Aquila rapax) in the southern Kalahari. This model does not include behavioural adaptations. We develop a new model by assuming that the birds enlarge their average territory size to compensate for lower amounts of precipitation. Here, we found the predicted increase in risk of extinction due to climate change to be much lower than in the original model. However, this "buffering" of climate change by behavioural adaptation is not very effective in coping with increasing interannual variances. We refer to further examples of ecological "buffering mechanisms" from the literature and argue that possible buffering mechanisms should be given due consideration when the effects of climate change on biodiversity are to be predicted. (c) 2004 Elsevier B.V. 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
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.
Climate change and land use management practices are major drivers of biodiversity in terrestrial ecosystems. To understand and predict resulting changes in community structures, individual-based and spatially explicit population models are a useful tool but require detailed data sets for each species. More generic approaches are thus needed. Here we present a trait-based functional type approach to model savanna birds. The aim of our model is to explore the response of different bird functional types to modifications in habitat structure. The functional types are characterized by different traits, in particular body mass, which is related to life-history traits (reproduction and mortality) and spatial scales (home range area and dispersal ability), as well as the use of vegetation structures for foraging and nesting, which is related to habitat quality and suitability. We tested the performance of the functional types in artificial landscapes varying in shrub:grass ratio and clumping intensity of shrub patches. We found that an increase in shrub encroachment and a decrease in habitat quality caused by land use mismanagement and climate change endangered all simulated bird functional types. The strength of this effect was related to the preferred habitat. Furthermore, larger-bodied insectivores and omnivores were more prone to extinction due to shrub encroachment compared to small-bodied species. Insectivorous and omnivorous birds were more sensitive to clumping intensity of shrubs whereas herbivorous and carnivorous birds were most affected by a decreasing amount of grass cover. From an applied point of view, our findings emphasize that policies such as woody plant removal and a reduction in livestock stocking rates to prevent shrub encroachment should prioritize the enlargement of existing grassland patches. Overall, our results show that the combination of an individual-based modelling approach with carefully defined functional types can provide a powerful tool for exploring biodiversity responses to environmental changes. Furthermore, the increasing accumulation of worldwide data sets on species’ core and soft traits (surrogates to determine core traits indirectly) on one side and the refinement of conceptual frameworks for animal functional types on the other side will further improve functional type approaches which consider the sensitivities of multiple species to climate change, habitat loss, and fragmentation.
Low-dimensional trade-offs fail to explain richness and structure in species-rich plant communities
(2011)
Mathematical models and ecological theory suggest that low-dimensional life history trade-offs (i.e. negative correlation between two life history traits such as competition vs. colonisation) may potentially explain the maintenance of species diversity and community structure. In the absence of trade-offs, we would expect communities to be dominated by 'super-types' characterised by mainly positive trait expressions. However, it has proven difficult to find strong empirical evidence for such trade-offs in species-rich communities. We developed a spatially explicit, rule-based and individual-based stochastic model to explore the importance of low-dimensional trade-offs. This model simulates the community dynamics of 288 virtual plant functional types (PFTs), each of which is described by seven life history traits. We consider trait combinations that fit into the trade-off concept, as well as super-types with little or no energy constraints or resource limitations, and weak PFTs, which do not exploit resources efficiently. The model is parameterised using data from a fire-prone, species-rich Mediterranean-type shrubland in southwestern Australia. We performed an exclusion experiment, where we sequentially removed the strongest PFT in the simulation and studied the remaining communities. We analysed the impact of traits on performance of PFTs in the exclusion experiment with standard and boosted regression trees. Regression tree analysis of the simulation results showed that the trade-off concept is necessary for PFT viability in the case of weak trait expression combinations such as low seed production or small seeds. However, species richness and diversity can be high despite the presence of super-types. Furthermore, the exclusion of super-types does not necessarily lead to a large increase in PFT richness and diversity. We conclude that low-dimensional trade-offs do not provide explanations for multi-species co-existence contrary to the prediction of many conceptual models.
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.
Long-term impacts of livestock herbivory on herbaceous and woody vegetation in semiarid savannas
(2000)
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
Environmental gradients represent an ideal framework for studying adaptive variation in the life history of plant species. However, on very steep gradients, largely contrasting conditions at the two gradient ends often limit the distribution of the same species across the whole range of environmental conditions. Here, we study phenotypic variation in a winter annual crucifer Biscutella didyma persisting along a steep gradient of increasing rainfall in Israel. In particular, we explored whether the life history at the arid end of the gradient indicates adaptations to drought and unpredictable conditions, while adaptations to the highly competitive environment prevail at the mesic Mediterranean end. We examined several morphological and reproductive traits in four natural populations and in populations cultivated in standard common environment. Plants from arid environments were faster in phenological development, more branched in architecture and tended to maximize reproduction, while the Mediterranean plants invested mainly in vertical vegetative growth. Differences between cultivation and field in diaspore production were very large for arid populations as opposed to Mediterranean ones, indicating a larger potential to increase reproduction under favorable conditions. Our overall findings indicate two strongly opposing selective forces at the two extremes of the aridity gradient, which result in contrasting strategies within the studied annual plant species
The need to implement sustainable resource management regimes for semi-arid and arid rangelands is acute as non- adapted grazing strategies lead to irreversible environmental problems such as desertification and associated loss of economic support to society. In these sensitive ecosystems, traditional sectoral, disciplinary approaches will not work to attain sustainability: achieving a collective vision of how to attain sustainability requires interactive efforts among disciplines in a more integrated approach. Therefore, we developed an integrated ecological-economic approach that consists of an ecological and an economic module and combines relevant processes on either level. Parameters for both modules are adjusted for an arid dwarf shrub savannah in southern Namibia. The economic module is used to analyse decisions of different virtual farmer types on annual stocking rates depending on their knowledge how the ecosystem works and climatic conditions. We used a dynamic linear optimisation model to simulate farm economics and livestock dynamics. The ecological module is used to simulate the impact of the farmers' land-use decision, derived by the economic module, on ecosystem dynamics and resulting carrying capacity of the system for livestock. Vegetation dynamics, based on the concept of State-and-transition models, and forage productivity for both modules is derived by a small- scale and spatially explicit vegetation model. This mechanistic approach guarantees that data collected and processes estimated at smaller scales are included in our application. Simulation results of the ecological module were successfully compared to simulation results of the optimisation model for a time series of 30 years. We revealed that sustainable management of semi-arid and arid rangelands relies strongly on rangeland managers' understanding of ecological processes. Furthermore, our simulation results demonstrate that the projected lower annual rainfall due to climate change adds an additional layer of risk to these ecosystems that are already prone to land degradation.
Köderauslageintervalle und Dauer der Bekämpfung des Kleinen Fuchsbandwurms : eine Modellierstudie
(2003)
Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.
Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.
Density regulation influences population dynamics through its effects on demographic rates and consequently constitutes a key mechanism explaining the response of organisms to environmental changes. Yet, it is difficult to establish the exact form of density dependence from empirical data. Here, we developed an individual-based model to explore how resource limitation and behavioural processes determine the spatial structure of white stork Ciconia ciconia populations and regulate reproductive rates. We found that the form of density dependence differed considerably between landscapes with the same overall resource availability and between home range selection strategies, highlighting the importance of fine-scale resource distribution in interaction with behaviour. In accordance with theories of density dependence, breeding output generally decreased with density but this effect was highly variable and strongly affected by optimal foraging strategy, resource detection probability and colonial behaviour. Moreover, our results uncovered an overlooked consequence of density dependence by showing that high early nestling mortality in storks, assumed to be the outcome of harsh weather, may actually result from density dependent effects on food provision. Our findings emphasize that accounting for interactive effects of individual behaviour and local environmental factors is crucial for understanding density-dependent processes within spatially structured populations. Enhanced understanding of the ways animal populations are regulated in general, and how habitat conditions and behaviour may dictate spatial population structure and demographic rates is critically needed for predicting the dynamics of populations, communities and ecosystems under changing environmental conditions.
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.
Aim To assess how habitat loss and climate change interact in affecting the range dynamics of species and to quantify how predicted range dynamics depend on demographic properties of species and the severity of environmental change. Location South African Cape Floristic Region. Methods We use data-driven demographic models to assess the impacts of past habitat loss and future climate change on range size, range filing and abundances of eight species of woody plants (Proteaceae). The species-specific models employ a hybrid approach that simulates population dynamics and long-distance dispersal on top of expected spatio-temporal dynamics of suitable habitat. Results Climate change was mainly predicted to reduce range size and range filling (because of a combination of strong habitat shifts with low migration ability). In contrast, habitat loss mostly decreased mean local abundance. For most species and response measures, the combination of habitat loss and climate change had the most severe effect. Yet, this combined effect was mostly smaller than expected from adding or multiplying effects of the individual environmental drivers. This seems to be because climate change shifts suitable habitats to regions less affected by habitat loss. Interspecific variation in range size responses depended mostly on the severity of environmental change, whereas responses in range filling and local abundance depended mostly on demographic properties of species. While most surviving populations concentrated in areas that remain climatically suitable, refugia for multiple species were overestimated by simply overlying habitat models and ignoring demography. Main conclusions Demographic models of range dynamics can simultaneously predict the response of range size, abundance and range filling to multiple drivers of environmental change. Demographic knowledge is particularly needed to predict abundance responses and to identify areas that can serve as biodiversity refugia under climate change. These findings highlight the need for data-driven, demographic assessments in conservation biogeography.
Understanding mechanisms to predict changes in plant and animal communities is a key challenge in ecology. The need to transfer knowledge gained from single species to a more generalized approach has led to the development of categorization systems where species' similarities in life strategies and traits are classified into ecological groups (EGs) like functional groups/types or guilds. While approaches in plant ecology undergo a steady improvement and refinement of methodologies, progression in animal ecology is lagging behind. With this review, we aim to initiate a further development of functional classification systems in animal ecology, comparable to recent developments in plant ecology. We here (i) give an overview of terms and definitions of EGs in animal ecology, (ii) discuss existing classification systems, methods and application areas of EGs (focusing on terrestrial vertebrates), and (iii) provide a "roadmap towards an animal functional type approach" for improving the application of EGs and classifications in animal ecology. We found that an animal functional type approach requires: (i) the identification of core traits describing species' dependency on their habitat and life history traits, (ii) an optimization of trait selection by clustering traits into hierarchies, (iii) the assessment of "soft traits" as substitute for hardly measurable traits, e.g. body size for dispersal ability, and (iv) testing of delineated groups for validation including experiments.
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.
East Africa hosts a striking diversity of terrestrial ecosystems, which vary both in space and time due to complex regional topography and a dynamic climate. The structure and functioning of these ecosystems under this environmental setting can be studied with dynamic vegetation models (DVMs) in a spatially explicit way. Yet, regional applications of DVMs to East Africa are rare and a comprehensive validation of such applications is missing. Here, we simulated the present-day and mid-Holocene vegetation of East Africa with the DVM, LPJ-GUESS and we conducted an exhaustive comparison of model outputs with maps of potential modern vegetation distribution, and with pollen records of local change through time. Overall, the model was able to reproduce the observed spatial patterns of East African vegetation. To see whether running the model at higher spatial resolutions (10′ × 10′) contribute to resolve the vegetation distribution better and have a better comparison scale with the observational data (i.e. pollen data), we run the model with coarser spatial resolution (0.5° × 0.5°) for the present-day as well. Both the area- and point-wise comparison showed that a higher spatial resolution allows to better describe spatial vegetation changes induced by the complex topography of East Africa. Our analysis of the difference between modelled mid-Holocene and modern-day vegetation showed that whether a biome shifts to another is best explained by both the amount of change in precipitation it experiences and the amount of precipitation it received originally. We also confirmed that tropical forest biomes were more sensitive to a decrease in precipitation compared to woodland and savanna biomes and that Holocene vegetation changes in East Africa were driven not only by changes in annual precipitation but also by changes in its seasonality.
Seed dispersal plays an important role in population dynamics in agricultural ecosystems, but the effects of surrounding vegetation height on seed dispersal and population connectivity on the landscape scale have rarely been studied. Understanding the effects of surrounding vegetation height on seed dispersal will provide important information for land-use management in agricultural landscapes to prevent the spread of undesired weeds or enhance functional connectivity. We used two model species, Phragmites australis and Typha latifolia, growing in small natural ponds known as kettle holes, in an agricultural landscape to evaluate the effects of surrounding vegetation height on wind dispersal and population connectivity between kettle holes. Seed dispersal distance and the probability of long-distance dispersal (LDD) were simulated with the mechanistic WALD model under three scenarios of "low", "dynamic" and "high" surrounding vegetation height. Connectivity between the origin and target kettle holes was quantified with a connectivity index adapted from Hanski and Thomas (1994). Our results show that mean seed dispersal distance decreases with the height of surrounding matrix vegetation, but the probability of long-distance dispersal (LDD) increases with vegetation height. This indicates an important vegetation-based trade-off between mean dispersal distance and LDD, which has an impact on connectivity. Matrix vegetation height has a negative effect on mean seed dispersal distance but a positive effect on the probability of LDD. This positive effect and its impact on connectivity provide novel insights into landscape level (meta-)population and community dynamics - a change in matrix vegetation height by land-use or climatic changes could strongly affect the spread and connectivity of wind-dispersed plants. The opposite effect of vegetation height on mean seed dispersal distance and the probability of LDD should therefore be considered in management and analyses of future land-use and climate change effects.
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.
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.
Identifying drivers of species diversity is a major challenge in understanding and predicting the dynamics of species-rich semi-natural grasslands. In particular in temperate grasslands changes in land use and its consequences, i.e. increasing fragmentation, the on-going loss of habitat and the declining importance of regional processes such as seed dispersal by livestock, are considered key drivers of the diversity loss witnessed within the last decades.
Give chance a chance
(2019)
A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
Give chance a chance
(2019)
A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
Decisions for the conservation of biodiversity and sustainable management of natural resources are typically related to large scales, i.e. the landscape level. However, understanding and predicting the effects of land use and climate change on scales relevant for decision-making requires to include both, large scale vegetation dynamics and small scale processes, such as soil-plant interactions. Integrating the results of multiple BIOTA subprojects enabled us to include necessary data of soil science, botany, socio-economics and remote sensing into a high resolution, process-based and spatially-explicit model. Using an example from a sustainably-used research farm and a communally used and degraded farming area in semiarid southern Namibia we show the power of simulation models as a tool to integrate processes across disciplines and scales.