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Sustainability challenges in socio-environmental systems (SES) are inherently multiscale, with global-level changes emerging from socio-environmental processes that operate across different spatial, temporal, and organisational scales. Models of SES therefore need to incorporate multiple scales, which requires sound methodologies for transferring information between scales. Due to the increasing global connectivity of SES, upscaling – increasing the extent or decreasing the resolution of a modelling study – is becoming progressively more important. However, upscaling in SES models has received less attention than in other fields (e.g., ecology or hydrology) and therefore remains a pressing challenge. To advance the understanding of upscaling in SES, we take three steps. First, we review existing upscaling approaches in SES as well as other disciplines. Second, we identify four main challenges that are particularly relevant to upscaling in SES: 1) heterogeneity, 2) interactions, 3) learning and adaptation, and 4) emergent phenomena. Third, we present an approach that facilitates the transfer of existing upscaling methods to SES, using two good practice examples from ecology. To describe and compare these methods, we propose a scheme of five general upscaling strategies. This scheme builds upon and unifies existing schemes and provides a standardised way to classify and represent existing as well as new upscaling methods. We demonstrate how the scheme can help to transparently present upscaling methods and uncover scaling assumptions, as well as to identify limits for the transfer of upscaling methods. We finish by pointing out research avenues on upscaling in SES to address the identified upscaling challenges.

Large areas of tropical forests have been lost through deforestation, resulting in fragmented forest landscapes. However, the dynamics of forest fragmentation are still unknown, especially the critical forest edge areas, which are sources of carbon emissions due to increased tree mortality. We analyzed the changes in forest fragmentation for the entire tropics using high-resolution forest cover maps. We found that forest edge area increased from 27 to 31% of the total forest area in just 10 years, with the largest increase in Africa. The number of forest fragments increased by 20 million with consequences for connectivity of tropical landscapes. Simulations suggest that ongoing deforestation will further accelerate forest fragmentation. By 2100, 50% of tropical forest area will be at the forest edge, causing additional carbon emissions of up to 500 million MT carbon per year. Thus, efforts to limit fragmentation in the world’s tropical forests are important for climate change mitigation.

Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi-faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time-horizons: i) reactive, when there is an imminent threat to ES resilience and a high pressure to act, ii) adjustive, when the threat is known in general but there is still time to adapt management, and iii) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology, and engineering are often implicitly focussing on provident, adjustive, or reactive resilience, respectively, but these different notions and of resilience and their corresponding social, ecological, and economic trade-offs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer-term management actions are not missed while urgent threats to ES are given priority.

Increasingly frequent and severe droughts pose one of the greatest challenges for dryland pastoralists in the Horn of Africa. Livestock drought insurance (LDI) has been proposed as a means to manage these risks. However, LDI may have unintended side effects, such as inducing unsustainable herd sizes leading to long-term pasture degradation. These issues are infeasible to study empirically given that none of the emerging LDI programs has existed at scale for any extended period of time. Thus, we study the potential long-term effects of LDI on pasture conditions at scale with the help of an agent-based model. We particularly consider the possibility that if insurance is taken up at scale, the quick herd size recovery that insurance enables after droughts can disrupt natural pasture recovery dynamics, with the potential to degrade the long-run carrying capacity of the vegetation. Our results show that, especially if pastures are very sensitive to grazing, insurance can indeed cause and/or intensify ecological instability. Furthermore, unfortunately, these unintended ecological consequences are most likely where insurance is needed the most. Designing the insurance product in the light of these insights may dampen these effects.

The Southern Ocean near the Western Antarctic Peninsula (WAP) is strongly affected by climate change resulting in warmer air temperature, accompanied with reduced sea ice coverage, increased sea water temperature and potential changes in the abundances of two key grazer species Salpa thompsoni (salp) and Euphausia superba (Antarctic krill). While salp abundance is hypothesized to increase, krill abundance is hypothesized to decline with dramatic consequences for the entire food web of the Southern Ocean. A better understanding of the biotic interaction between krill and salps and their population dynamics is thus crucial. However, the life cycle of salps is complicated and barely understood. Therefore, we have developed an individual-based model describing the whole life cycle to better understand the population dynamics of salps and the conditions for blooms. The model has been used to explore if and under what conditions the empirical pattern of large variability in observed salp abundances at the WAP, generated by the long-term data of the US Antarctic Marine Living Resources Program (AMLR) can emerge from a small seeding population. The model reproduced this empirical pattern if daily growth rates of oozoids were higher than previously reported for the WAP (mean growth rate for oozoids ~ 1 mm d−1) and if growth rates of blastozooids were lower (mean growth rate ~ 0.2 mm d−1). The model suggests that a prerequisite for local salp blooms requires a small founding population in early spring. With climate change it has been suggested that more frequent and earlier transport of salps into the WAP or winter survival will occur. Hence, the risk of salp blooms in the WAP is likely to substantially increase. These findings highlight the importance for an improved quantitative understanding of how primary production and the southward advection of salps will be impacted by climate change.

Success of forest restoration at farm level depends on the farmer´s decision-making and the constraints to farmers’ actions. There is a gap between the intentions and the actual behavior towards restoration in Sub-Saharan Africa and the Global South. To understand this discrepancy, our study uses empirical household survey data to design and parameterize an agent-based model. WEEM (Woodlot Establishment and Expansion Model) has been designed based on household socio-demographics and projects the temporal dynamics of woodlot numbers in Uganda. The study contributes to a mechanistic understanding of what determines the current gap between farmer’s intention and actual behavior. Results reveal that an increase in knowledge of the current forest policies laws and regulations (PLRs) from 18% to 50% and to 100% reduces the average number of woodlots by 18% and 79% respectively. Lack of labor reduces the number of woodlots by 80%. Increased labor requirement from 4 to 8 and to 12 man-days, reduces the number of woodlots by 26% and 61% respectively. WEEM indicates that absence of household labor and de facto misconception of PLRs “perceived tenure insecurity” constrains the actual behavior of farmers. We recommend forest PLRs to provide full rights of use and ownership of trees established on private farmland. Tree fund in the case of Uganda should be operationalized to address the transaction costs and to achieve the long-term targets of forest land restoration.

Deforestation in the tropics is not only responsible for direct carbon emissions but also extends the forest edge wherein trees suffer increased mortality. Here we combine high-resolution (30 m) satellite maps of forest cover with estimates of the edge effect and show that 19% of the remaining area of tropical forests lies within 100 m of a forest edge. The tropics house around 50 million forest fragments and the length of the world's tropical forest edges sums to nearly 50 million km. Edge effects in tropical forests have caused an additional 10.3 Gt (2.1–14.4 Gt) of carbon emissions, which translates into 0.34 Gt per year and represents 31% of the currently estimated annual carbon releases due to tropical deforestation. Fragmentation substantially augments carbon emissions from tropical forests and must be taken into account when analysing the role of vegetation in the global carbon cycle., Vast quantities of carbon stored in tropical forests are threatened by deforestation. Here, using high resolution satellite data, Brinck et al. examine how edge effects influence carbon emissions and they find an additional 10.3 Gt of carbon are released by deforestation when including fragmentation effects.

Land use transformation at the farm level is attributed to household decision-making, reflected by the behavior and activities of smallholder farmers. Unfortunately, household decision-making in local communities and its determinants are site-specific and hardly understood. This study uses multistage purposive selection of households as a unit for the analysis to investigate the transformation from pure agriculture to farm forest mosaics, especially through woodlot establishment. We use key informants, household surveys, and observations to obtain data on decision-making amongst 84 farm households in Nyantonzi parish, Masindi district, Uganda, as an example. Specifically, the study addresses four research questions. Firstly, what is the current status of gender-based decision-making at the household level? Secondly, is decision making within farm households individualistic or collective? Thirdly, which factors are considered to select annual, perennial and tree-crop farm management regimes? Fourthly, what determinants influence the decision-making process and the likelihood of woodlot establishment? A multilevel analysis comprising parametric statistical models and binary logistic regression is applied to assess difference in household natural, physical, human, and social capital, highlight gender roles, and obtain factors associated to selection of crops and determinants of woodlot establishment at the farm level, respectively. Results reveal that gender based decision-making is clearly disaggregated on the basis of husbands and wives and it is individualistic, mostly dominated by husbands with lower participation by wives and other family members. Households consider various factors before making any decisions, e.g., market prices for both annual and perennial crops, food consumption for annual crops, ease of management, and yields from the previous season for the tree-crop management regimes. The likelihood for woodlot establishment is positively influenced by the willingness and intention of households to establish woodlots and relative age of household head. However, knowledge of land use Policies, Laws, and Regulations (PLRs) in relation to tree planting and harvesting and access to non-farm income reduce the likelihood of woodlot establishment. Here, we recommend that current and future forest land restoration initiatives focus on reducing the gender gap and increase women&rsquo, s participation in decision making, provide market information platforms on wood products, and include woodlot farmers in social organization. Current PLRs on tree tenure should be improved and clearly communicated by using the existing communication assets and social gatherings as channels of change and influence for decision-making.

Ensuring ecosystem resilience is an intuitive approach to safeguard future provisioning of ecosystem services (ES). However, resilience is an ambiguous concept and difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough because the usefulness of a mechanism is context-dependent. We suggest a conceptual framework, resilience trinity, to facilitate management of resilience mechanisms in three distinctive decision contexts and time-horizons. i) reactive, when there is an imminent threat to ES resilience and a high pressure to act, ii) adjustive, when the threat is known in general but there is still time to adapt management, and iii) provident when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. This emphasizes that resilience has different interpretations and implications at different time horizons which however need to be reconciled. The inclusion of time into resilience thinking ensures that longer-term management actions are not missed while urgent threats to ES are given priority.

Due to deforestation, intact tropical forest areas are increasingly transformed into a mixture of remaining forest patches and human modified areas. These forest fragments suffer from edge effects, which cause changes in ecological and ecosystem processes, undermining habitat quality and the offer of ecosystem services. Even though detailed and long term studies were developed on the topic of edge effects at local scale, understanding edge effect characteristics in fragmented forests on larger scales and finding indicators for its impact is crucial for predicting habitat loss and developing management options. Here we evaluate the spatial and temporal dimensions of edge effects in large areas using remote sensing. First we executed a neighborhood pixel analysis in 11 LANDSAT Tree Cover (LTC) scenes (180 × 185 km each, 8 in the tropics and 3 in temperate forested areas) using tree cover as an indicator of habitat quality and in relation to edge distance. Second, we executed a temporal analysis of LTC in a smaller area in the Brazilian Amazon forest where one larger forest fragment (25,890 ha) became completely fragmented in 5 years. Our results show that for all 11 scenes pixel neighborhood variation of LTC is much higher in the vicinity of forest edges, becoming lower towards the forest interior. This analysis suggests a maximum distance for edge effects and can indicate the location of unaffected core areas. However, LTC patterns in relation to fragment edge distance vary according to the analyzed region, and maximum edge distance may differ according to local conditions. Our temporal analysis illustrates the change in tree cover patterns after 5 years of fragmentation, becoming on average lower close to the edge (between 50 and 100 m). Although it is still unclear which are the main causes of LTC edge variability within and between regions, LANDSAT Tree Cover could be used as an accessible and efficient discriminator of edge and interior forest habitats in fragmented landscapes, and become invaluable for deriving qualitative spatial and temporal information of ecological and ecosystem processes.

Incorporating representations of human decision-making that are based on social science theories into social-ecological models is considered increasingly important – yet choosing and formalising a theory for a particular modelling context remains challenging. Here, we reflect on our experiences of selecting, formalising and documenting psychological and economic theories of human decision-making for inclusion in different agent-based models (ABMs) of natural resource use. We discuss the challenges related to four critical tasks: How to select a theory? How to formalise a theory and how to translate it into code? How to document the formalisation? In this way, we present a systematic overview of the choices researchers face when including theories of human decision-making in their ABMs, reflect on the choices we made in our own modelling projects and provide guidance for those new to the field. Also, we highlight further challenges regarding the parameterisation and analysis of such ABMs and suggest that a systematic overview of how to tackle these challenges contributes to an effective collaboration in interdisciplinary teams addressing socio-ecological dynamics using models.

Agent-based modelling (ABM) and social network analysis (SNA) are both valuable tools for exploring the impact of human interactions on a broad range of social and ecological patterns. Integrating these approaches offers unique opportunities to gain insights into human behaviour that neither the evaluation of social networks nor agent-based models alone can provide. There are many intriguing examples that demonstrate this potential, for instance in epidemiology, marketing or social dynamics. Based on an extensive literature review, we provide an overview on coupling ABM with SNA and evaluating the integrated approach. Building on this, we identify current shortcomings in the combination of the two methods. The greatest room for improvement is found with regard to (i) the consideration of the concept of social integration through networks, (ii) an increased use of the co-evolutionary character of social networks and embedded agents, and (iii) a systematic and quantitative model analysis focusing on the causal relationship between the agents and the network. Furthermore, we highlight the importance of a comprehensive and clearly structured model conceptualization and documentation. We synthesize our findings in guidelines that contain the main aspects to consider when integrating social networks into agent-based models.

Salpa thompsoni is an important grazer in the Southern Ocean. It is found from the Subtropical Convergence southward to the coastal Antarctic Seas but being most abundant in the Antarctic Polar Frontal Zone. Low temperatures appear to negatively affect their development, limiting their ability to occur in the krill dominated high Antarctic ecosystems. Yet reports indicate that with ocean warming S. thompsoni have experienced a southward shift in their distribution. As they are efficient filter feeders, this shift can result in large-scale changes in the Southern Ocean ecosystem by increasing competitive or predatory interactions with Antarctic krill. To explore salp bloom dynamics in the Southern Ocean a size-structured S. thompsoni population model was developed with growth, consumption, reproduction and mortality rates dependent on temperature and chlorophyll a conditions. The largest uncertainties in S. thompsoni population ecology are individual and population growth rates, with a recent study identifying the possibility that the life cycle could be much shorter than previously considered. Here we run a suite of hypothesis scenarios under various environmental conditions to determine the most appropriate growth rate. Temperature and chlorophyll a were sufficient drivers to recreate seasonal and interannual dynamics of salp populations at two locations. The most suitable growth model suggests that mean S. thompsoni growth rates are likely to be ∼1 mm body length d−1, 2-fold higher than previous calculations. S. thompsoni biomass was dependent on bud release time, with larger biomass years corresponding to bud release occurring during favorable environmental conditions; increasing the survival and growth of blastozooids and resulting in higher embryo release. This model confirms that it is necessary for growth and reproductive rates to be flexible in order for the salp population to adapt to varying environmental conditions and provides a framework that can examine how future salp populations might respond to climate change.

The Southern Ocean ecosystem is characterized by extreme seasonal changes in environmental factors such as day length, sea ice extent and food availability. The key species Antarctic krill (Euphausia superba) has evolved metabolic and behavioural seasonal rhythms to cope with these seasonal changes. We investigate the switch between a physiological less active and active period for adult krill, a rhythm which seems to be controlled by internal biological clocks. These biological clocks can be synchronized by environmental triggers such as day length and food availability. They have evolved for particular environmental regimes to synchronize predictable seasonal environmental changes with important life cycle functions of the species. In a changing environment the time when krill is metabolically active and the time of peak food availability may not overlap if krill's seasonal activity is solely determined by photoperiod (day length). This is especially true for the Atlantic sector of the Southern Ocean where the spatio-temporal ice cover dynamics are changing substantially with rising average temperatures. We developed an individual-based model for krill to explore the impact of photoperiod and food availability on the growth and demographics of krill. We simulated dynamics of local krill populations (with no movement of krill assumed) along a south-north gradient for different triggers of metabolic activity and different levels of food availability below the ice. We also observed the fate of larval krill which cannot switch to low metabolism and therefore are likely to overwinter under ice. Krill could only occupy the southern end of the gradient, where algae bloom only lasts for a short time, when alternative food supply under the ice was high and metabolic activity was triggered by photoperiod. The northern distribution was limited by lack of overwintering habitat for krill larvae due to short duration of sea ice cover even for high food content under the ice. The variability of the krill's length-frequency distributions varied for different triggers of metabolic activity, but did not depend on the sea ice extent. Our findings suggest a southward shift of krill populations due to reduction in the spatial sea ice extent, which is consistent with field observations. Overall, our results highlight the importance of the explicit consideration of spatio-temporal sea ice dynamics especially for larval krill together with temporal synchronization through internal clocks, triggered by environmental factors (photoperiod and food) in adult krill for the population modelling of krill.

Empirical studies on severely fragmented regions suggest that decades after fragmentation, forest edges located near human-modified areas exhibit the structure of early successional states, with lower biomass per area and higher mortality compared to non-edge areas. These habitat changes (edge effects) can also have a considerable impact on ecosystem processes such as carbon and water balance, which in turn have a major impact on human activities. Using field data from a long-term fragmented landscape in the Brazilian Northeastern Atlantic Forest, and the Forest Model FORMIND, we were able to visualize the time scale in which edge effects influence tropical forests by performing 500-year simulations. We observed changes in community composition, aboveground biomass, total evapotranspiration and total runoff. Averages from ten four-hectare simulations show forest biomass degradation lasting around 100 years. If edge effects cease, recovery of biomass lasts around 150 years. Carbon loss is especially intense during the first five years after fragmentation, resulting in a decline of over 5 Mg ha −1 y −1 C. Finally, edges of large fragments face an evapotranspiration loss of 43% and total runoff gains of 57% in relation to core areas of large fragments, suggesting that fragmented landscapes can be of significantly lower value in terms of ecosystem services.

Remote sensing enables the quantification of tropical deforestation with high spatial resolution. This in-depth mapping has led to substantial advances in the analysis of continent-wide fragmentation of tropical forests. Here we identified approximately 130 million forest fragments in three continents that show surprisingly similar power-law size and perimeter distributions as well as fractal dimensions. Power-law distributions have been observed in many natural phenomena such as wildfires, landslides and earthquakes. The principles of percolation theory provide one explanation for the observed patterns, and suggest that forest fragmentation is close to the critical point of percolation; simulation modelling also supports this hypothesis. The observed patterns emerge not only from random deforestation, which can be described by percolation theory, but also from a wide range of deforestation and forest-recovery regimes. Our models predict that additional forest loss will result in a large increase in the total number of forest fragments-at maximum by a factor of 33 over 50 years-as well as a decrease in their size, and that these consequences could be partly mitigated by reforestation and forest protection.

Current chemical risk assessment procedures may result in imprecise estimates of risk due to sometimes arbitrary simplifying assumptions. As a way to incorporate ecological complexity and improve risk estimates, mechanistic effect models have been recommended. However, effect modeling has not yet been extensively used for regulatory purposes, one of the main reasons being uncertainty about which model type to use to answer specific regulatory questions. We took an individual-based model (IBM), which was developed for risk assessment of soil invertebrates and includes avoidance of highly contaminated areas, and contrasted it with a simpler, more standardized model, based on the generic metapopulation matrix model RAMAS. In the latter the individuals within a sub-population are not treated as separate entities anymore and the spatial resolution is lower. We explored consequences of model aggregation in terms of assessing population-level effects for different spatial distributions of a toxic chemical. For homogeneous contamination of the soil, we found good agreement between the two models, whereas for heterogeneous contamination, at different concentrations and percentages of contaminated area, RAMAS results were alternatively similar to IBM results with and without avoidance, and different food levels. This inconsistency is explained on the basis of behavioral responses that are included in the IBM but not in RAMAS. Overall, RAMAS was less sensitive than the IBM in detecting population-level effects of different spatial patterns of exposure. We conclude that choosing the right model type for risk assessment of chemicals depends on whether or not population-level effects of small-scale heterogeneity in exposure need to be detected. We recommend that if in doubt, both model types should be used and compared. Describing both models following the same standard format, the ODD protocol, makes them equally transparent and understandable. The simpler model helps to build up trust for the more complex model and can be used for more homogeneous exposure patterns. The more complex model helps detecting and understanding the limitations of the simpler model and is needed to ensure ecological realism for more complex exposure scenarios.

Studies explaining the choice of model structure for population viability analysis (PVA) are rare and no such study exists for butterfly species, a focal group for conservation. Here, we describe in detail the development of a model to predict population viability of a glacial relict butterfly species, Boloria eunomia, under climate change. We compared four alternative formulations of an individual-based model, differing in the environmental factors acting on the survival of immature life stages: temperature (only temperature impact), weather (temperature, precipitation, and sunshine), temperature and parasitism, and weather and parasitism. Following pattern-oriented modeling, four observed patterns were used to contrast these models: one qualitative (response of population size to habitat parameters) and three quantitative ones describing population dynamics during eight years (mean and variability of population size, and magnitude of the temporal autocorrelation in yearly population growth rates). The four model formulations were not equally able to depict population dynamics under current environmental conditions; the model including only temperature was selected as the most parsimonious model sufficiently well reproducing the empirical patterns. We used all four model formulations to test a range of climate change scenarios that were characterized by changes in both mean and variability of the weather variables. All models predicted adverse effects of climate change and resulted in the same ranking of mean climate change scenarios. However, models differed in their absolute values of population viability measures, underlining the need to explicitly choose the most appropriate model formulation and avoid arbitrary usage of environmental drivers in a model. We conclude that further applications of pattern-oriented modeling to butterfly and other species are likely to help in identifying the key factors impacting the viability of certain taxa, which, ultimately, will aid and speed up informed management decisions for endangered species under climate change.

A dominant Antarctic ecological paradigm suggests that winter sea ice is generally the main feeding ground for krill larvae. Observations from our winter cruise to the southwest Atlantic sector of the Southern Ocean contradict this view and present the first evidence that the pack-ice zone is a food-poor habitat for larval development. In contrast, the more open marginal ice zone provides a more favourable food environment for high larval krill growth rates. We found that complex under-ice habitats are, however, vital for larval krill when water column productivity is limited by light, by providing structures that offer protec- tion from predators and to collect organic material released from the ice. The larvae feed on this sparse ice-associated food during the day. After sunset, they migrate into the water below the ice (upper 20 m) and drift away from the ice areas where they have previously fed. Model analyses indicate that this behaviour increases both food uptake in a patchy food environment and the likelihood of overwinter transport to areas where feeding conditions are more favourable in spring.

Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social ecological systems. (C) 2016 Elsevier B.V. All rights reserved.

Agent-based models (ABMs) are increasingly used to describe, understand and predict human behaviour. The flexibility of agent-based models allows exploring mechanisms and feedback effects. However, this flexibility comes at a price, which is the problem of communicating and describing the model in a concise and transparent manner. There is no general agreement or culture yet on how agent-based models should be documented and described. Therefore, we want to contribute to the discussion on how agent-based models should be described in this position paper from a demographic perspective. Firstly we present and discuss the plethora of different ways to describe published agent-based models in population studies and demography. Subsequently, we argue that the ODD + D (Overview, Design, Details + Decisions) protocol is apt to address the specific difficulties which arise in describing demographic ABMs. We describe the main elements of the ODD + D protocol and subsequently present the results of an experiment illustrating its usefulness to describe an agent-based model of circular migration. We conclude that protocols such as the ODD + D are not only useful to compile a model description, but also serve as tool for the model developer to check if she has provided all necessary information that allows the reader to fully understand and replicate the model.

Current rates of environmental change are exceeding the capacity of many populations to adapt to new conditions and thus avoid demographic collapse and ultimate extinction. In particular, cold-water freshwater fish species are predicted to experience strong selective pressure from climate change and a wide range of interacting anthropogenic stressors in the near future. To implement effective management and conservation measures, it is crucial to quantify the maximum rate of change that cold-water freshwater fish populations can withstand. Here, we present a spatially explicit eco-genetic individual-based model, inSTREAM-Gen, to predict the eco-evolutionary dynamics of stream-dwelling trout under anthropogenic environmental change. The model builds on a well-tested demographic model, which includes submodels of river dynamics, bioenergetics, and adaptive habitat selection, with a new genetic module that allows exploration of genetic and life-history adaptations to new environments. The genetic module models the transmission of two key traits, size at emergence and maturity size threshold. We parameterized the model for a brown trout (Salmo trutta L.) population at the warmest edge of its range to validate it and analyze its sensitivity to parameters under contrasting thermal profiles. To illustrate potential applications of the model, we analyzed the population's demographic and evolutionary dynamics under scenarios of (1) climate change-induced warming, and (2) warming plus flow reduction resulting from climate and land use change, compared to (3) a baseline of no environmental change. The model predicted severe declines in density and biomass under climate warming. These declines were lower than expected at range margins because of evolution towards smaller size at both emergence and maturation compared to the natural evolution under the baseline conditions. Despite stronger evolutionary responses, declining rates were substantially larger under the combined warming and flow reduction scenario, leading to a high probability of population extinction over contemporary time frames. Therefore, adaptive responses could not prevent extinction under high rates of environmental change. Our model demonstrates critical elements of next generation ecological modelling aiming at predictions in a changing world as it accounts for spatial and temporal resource heterogeneity, while merging individual behaviour and bioenergetics with microevolutionary adaptations.

Tropical forests are highly diverse ecosystems, but within such forests there can be large patches dominated by a single tree species. The myriad presumed mechanisms that lead to the emergence of such monodominant areas is currently the subject of intensive research. We used the most generic of these mechanisms, large seed mass and low dispersal ability of the monodominant species, in a spatially explicit model. The model represents seven identical species with long-distance dispersal of small seeds, competing with one potentially monodominant species with short-distance dispersal of large seeds. Monodominant patches emerged and persisted only for a narrow range of species traits; these results have the characteristic features of phase transitions. Additional mechanisms may explain monodominance in different ecological contexts, but our results suggest that percolation-like phenomena and phase transitions might be pervasive in this type of system., M.K. was supported by ERC advanced grant no. 233066. P.B. gratefully acknowledges the support of the German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig supported by the German Research Foundation (FZT 118).

The distribution of surface water affects herbivore–vegetation interactions in arid and semi-arid regions. Limited access to surface water typically results in the emergence of vegetation gradients around natural and artificial water sources. In particular, African elephants can create large-scale gradients of woody vegetation. Understanding the dynamics of these gradients is of particular importance for the conservation of other, less mobile herbivores that depend on woody vegetation in areas close to water. While rainfall is known to be a key determinant of herbivore–vegetation interactions in dry areas, we only have limited understanding on how it impacts woody vegetation gradients around waterholes. To address this problem, we developed a deterministic simulation model that describes the interplay of rainfall, elephants and woody vegetation in the vicinity of waterholes. The model is based on elephant telemetry data and the ecological conditions in Etosha National Park (ENP), Namibia. We found that decreasing amounts of rainfall led to an increased degradation of woody vegetation, which was particularly severe in areas close to water. Based on this result we conclude that low rainfall was an important driver of recently observed patterns of vegetation degradation in ENP. More generally, rainfall appears to be a key factor that determines elephant–vegetation interactions and thus dynamics of woody vegetation gradients around waterholes. Using long-term rainfall data from ENP, we also demonstrate that an increase in the number of water sources during periods of low rainfall can mitigate the destructive impact of elephants in areas close to water. However, more research is required to assess the sustainability and effectiveness of rainfall-adapted strategies of artificial water provisioning in more detail. In particular it is important to investigate potential effects on elephant population dynamics.

Classical ecological theory predicts that ecological communities should only contain as many species as there are resources. Many ecosystems, however, seem to contain many more species than classical theory allows. Understanding this paradox is central to community ecology and biogeography. Niche-based models consider that differences and trade-offs between species’ life history traits stabilise species interactions and so allow coexistence. In stark contrast, neutral models assume that individuals at the same trophic level interact identically with conspecifics and heterospecifics (i.e. all species are equivalent), and this equivalence allows coexistence. Despite it seeming unlikely that species are equivalent, neutral models do predict some of the macroscopic properties of ecological communities surprisingly well. Although there are many neutral models, the best-known neutral model in the context of community ecology is that described by Hubbell (2001) in the Unified Neutral Theory of Biodiversity. We review the development of neutral theory in ecology and biogeography, consider its predictions and how they can be evaluated, and look at how neutral theory may develop in the future. This article focuses on species-rich plant communities, as they are, for the most part, the test-bed for the recent development and application of neutral models, but we also consider the application of neutral approaches to other taxonomic groups and ecosystem types.

Question: The majority of studies investigating the impact of climate change on local plant communities ignores changes in regional processes, such as immigration from the regional seed pool. Here we explore: (i) the potential impact of climate change on composition of the regional seed pool, (ii) the influence of changes in climate and in the regional seed pool on local community structure, and (iii) the combinations of life history traits, i.e. plant functional types (PFTs), that are most affected by environmental changes. Location: Fire-prone, Mediterranean-type shrublands in southwestern Australia. Methods: Spatially explicit simulation experiments were conducted at the population level under different rainfall and fire regime scenarios to determine the effect of environmental change on the regional seed pool for 38 PFTs. The effects of environmental and seed immigration changes on local community dynamics were then derived from community-level experiments. Classification tree analyses were used to investigate PFT-specific vulnerabilities to climate change. Results: The classification tree analyses revealed that responses of PFTs to climate change are determined by specific trait characteristics. PFT-specific seed production and community patterns responded in a complex manner to climate change. For example, an increase in annual rainfall caused an increase in numbers of dispersed seeds for some PFTs, but decreased PFT diversity in the community. Conversely, a simulated decrease in rainfall reduced the number of dispersed seeds and diversity of PFTs. Conclusions: PFT interactions and regional processes must be considered when assessing how local community structure will be affected by environmental change.

The Atlantic Rain Forest, an important biodiversity hot spot, has faced severe habitat loss since the last century which has resulted in a highly fragmented landscape with a large number of small forest patches (

1. Spatio-temporal fire regimes are likely to shift with changes in land use and climate. Such a shift in the disturbance regime has been proposed from recent reconstructions of the regional fire history in the Mediterranean-type woodlands and shrublands of Western Australia which suggest that fire was much more frequent before 1930 (local fire intervals of 3-5 years) than it is today (local fire intervals of 8-15 years). 2. To investigate the potential biodiversity consequences of such changes in fire regime for fire-killed woody species, we developed a spatial model for the serotinous shrub Banksia hookeriana that grows on sand dunes of the Eneabba Plain, Western Australia. We sought to identify the envelope of fire regimes under which the spatially separated populations in this species are able to persist, and whether this encompasses the fire regimes proposed by recent fire-history reconstructions. 3. We tested two fire frequency-size distribution scenarios: (1) a scenario where fire size depends on the spatial patch configuration; and (2) a scenario depending also on available fuel (time since last fire), which reduces fire size at short inter-fire intervals. 4. In scenario 1, metapopulation persistence was only likely for mean ignition intervals at the landscape scale of > 6 years. In scenario 2, persistence was likely for the whole range of fire interval distributions at the landscape scale suggested by the empirical data. However, persistence was almost impossible if the mean return fire interval at the local scale (i.e. for individual dunes) is < 8 years. 5. Synthesis and applications. We have demonstrated that this plant metapopulation can potentially persist over a wide range of temporal fire regimes at the landscape scale, so long as there are buffering mechanisms at work (e.g. feedback between fire spread and vegetation age) which reduces the probability of large fires at short intervals. Our findings demonstrate that at least some parts of the landscape must burn substantially less frequently on average than suggested by the empirical fire reconstructions for the early and pre-European period if populations of fire-killed woody species such as B. hookeriana are to be conserved.

Modelling and empirical studies have shown that input from the regional seed pool is essential to maintain local species diversity. However, most of these studies have concentrated on simplified, if not neutral, model systems, and focus on a limited subset of species or on aggregated measures of diversity only (e.g., species richness or Shannon diversity). Thus they ignore more complex species interactions and important differences between species. To gain a better understanding of how seed immigration affects community structure at the local scale in real communities we conducted computer simulation experiments based on plant functional types (PFTs) for a species-rich, fire-prone Mediterranean-type shrubland in Western Australia. We developed a spatially explicit simulation model to explore the community dynamics of 38 PFTs, defined by seven traits - regeneration mode, seed production, seed size, maximum crown diameter, drought tolerance, dispersal mode and seed bank type - representing 78 woody species. Model parameterisation is based on published and unpublished data on the population dynamics of shrub species collected over 18 years. Simulation experiments are based on two contrasting seed immigration scenarios: (1) the 'equal seed input number' scenario, where the number of immigrant seeds is the same for all PFTs, and (2) the 'equal seed input mass' scenario, where the cumulative mass of migrating seeds is the same for all PFTs. Both scenarios were systematically tested and compared for different overall seed input values. Without immigration the local community drifts towards a state with only 13 coexisting PFTs. With increasing immigration rates in terms of overall mass of seeds the simulated number of coexisting PFTs and Shannon diversity quickly approaches values observed in the field. The equal seed mass scenario resulted in a more diverse community than did the seed number scenario. The model successfully approximates the frequency distributions (relative densities) of all individual plant traits except seed size for scenarios associated with equal seed input mass and high immigration rate. However, no scenario satisfactorily approximated the frequency distribution for all traits in combination. Our results show that regional seed input can explain the more aggregated measures of local community structure, and some, but not all, aspects of community composition. This points to the possible importance of other (untested) processes and traits (e.g., dispersal vectors) operating at the local scale. Our modelling framework can readily allow new factors to be systematically investigated, which is a major advantage compared to previous simulation studies, as it allows us to find structurally realistic models, which can address questions pertinent to ecological theory and to conservation management.

Forests worldwide are threatened by various environmental and anthropogenic hazards, especially tropical forests. Knowledge on the impacts of these hazards on forest structure and dynamics has been compiled in empirical studies. However, the results of these studies are often not sufficient for long-term projections and extrapolations to large spatial scales especially for unprecedented environmental conditions, which require both the identification and understanding of key underlying processes. Forest models bridge this gap by incorporating multiple ecological processes in a dynamic framework (i.e. including a realistic model structure) and addressing the complexity of forest ecosystems. Here, we describe the evolution of the individual-based and process-based forest gap model FORMIND and its application to tropical forests. At its core, the model includes physiological processes on tree level (photosynthesis, respiration, tree growth, mortality, regeneration, competition). During the past two decades, FORMIND has been used to address various scientific questions arising from different forest types by continuously extending the model structure. The model applications thus provided understanding in three main aspects: (1) the grouping of single tree species into plant functional types is a successful approach to reduce complexity in vegetation models, (2) structural realism was necessary to analyze impacts of natural and anthropogenic disturbances such as logging, fragmentation, or drought, and (3) complex ecological processes such as carbon fluxes in tropical forests – starting from the individual tree level up to the entire forest ecosystem – can be explored as a function of forest structure, species composition and disturbance regime. Overall, this review shows how the evolution of long-term modelling projects not only provides scientific understanding of forest ecosystems, but also provides benefits for ecological theory and empirical study design. peerReviewed

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

1. A spatially explicit, rule-based model for three co-occurring Banksia species was developed to investigate coexistence mediating processes in a fire-prone shrubland in western Australia. Fecundity, recruitment, mortality and other biological data for two non-sprouting (B. hookeriana, B. prionotes) and one resprouting (B. attenuata) species were available from 15 years of empirical field studies. 2. Without interspecific competition, each species could persist for a wide range of fire intervals (10 to > 20 years). The resprouting species performed better under shorter fire intervals (10-13 years), while both non-sprouting species were favoured by longer (15 to > 20 years) fire intervals. These results conform with those obtained from single-species, non-spatial population models. 3. When interspecific competition for space was included in the model, all three species exhibited optima at shorter fire intervals and with a narrower range than in isolation. The three species did not co-occur under any fire regime. At intermediate fire frequencies (11-13 years), B. hookeriana excluded the other species, while for longer intervals between fires B. prionotes became dominant. 4. The introduction of temporal (stochastic) variability in fire intervals (drawn from a normal distribution) failed to produce coexistence, unless spatial variability as a spatial ignition gradient was also included. The spatial arrangement of the non-sprouters observed in the field was then reproduced. 5. Observed patterns of coexistence and spatial distributions of all species occurred when a spatial establishment gradient for the resprouter species was included in the model (individuals of B. attenuata are known to produce more seeds in swales than on dune crests and recruit seedlings here more frequently). 6. Coexistence appears to be highly dependent upon the mean interfire period in combination with subtle gradients associated with fire propagation and recruitment conditions. Variation around the mean fire interval is less critical. When the system is modelled over a long time period (1500 years) coexistence is most strongly favoured for a narrow window of mean fire intervals (12-14 years).

In times of global change and intensified resource exploitation, advanced knowledge of ecophysiological processes in natural and engineered systems driven by complex microbial communities is crucial for both, safeguarding environmental processes and optimising rational control of biotechnological processes. To gain such knowledge, high-throughput molecular techniques are routinely employed to investigate microbial community composition and dynamics within a wide range of natural or engineered environments. However, for molecular dataset analyses no consensus about a generally applicable alpha diversity concept and no appropriate benchmarking of corresponding statistical indices exist yet. To overcome this, we listed criteria for the appropriateness of an index for such analyses and systematically scrutinised commonly employed ecological indices describing diversity, evenness, and richness based on artificial and real molecular datasets. We identified appropriate indices warranting inter-study comparability and intuitive interpretability. The unified diversity concept based on ‘effective numbers of types’ provides the mathematical framework for describing community composition. Additionally, the Bray-Curtis dissimilarity as a beta-diversity index was found to reflect compositional changes. The employed statistical procedure is presented comprising commented R-scripts and example datasets for user-friendly trial application.

Coexistence in fire-prone Mediterranean-type shrublands has been explored in the past using both neutral and niche-based models. However, distinct differences between plant functional types (PFTs), such as fire-killed vs resprouting responses to fire, and the relative similarity of species within a PFT, suggest that coexistence models might benefit from combining both neutral and niche-based (stabilizing) approaches. We developed a multispecies metacommunity model where species are grouped into two PFTs (fire-killed vs resprouting) to investigate the roles of neutral and stabilizing processes on species richness and rank-abundance distributions. Our results show that species richness can be maintained in two ways: i) strictly neutral species within each PFT, or ii) species within PFTs differing in key demographic properties, provided that additional stabilizing processes, such as negative density regulation, also operate. However, only simulations including stabilizing processes resulted in structurally realistic rank-abundance distributions over plausible time scales. This result underscores the importance of including both key species traits and stabilizing (niche) processes in explaining species coexistence and community structure.

Multiple agent-based models (ABM) on social-ecological systems exist in parallel investigating similar research questions. However, the choice of a particular human decision model is often not sufficiently empirically or theoretically substantiated in the model documentation. Furthermore, model comparison is difficult because model descriptions are often incomplete, intransparent and difficult to understand. Therefore we expand and refine the ‘ODD’ (Overview, Design Concepts, and Details) protocol to establish a standard to describe ABMs which includes human decision making (ODD+D). Since the original ODD is mainly from an ecological perspective, some adaptations are necessary for the social-ecological context. We extended and rearranged the design concepts and related guiding questions to differentiate and describe decision making, adaptation and learning of the agents in a comprehensive and clearly structured way. Furthermore, ODD+D encompasses a section on ‘Theoretical and empirical background’ to encourage that model design and model assumptions are related more closely to theory. The application of ODD+D is illustrated with a description of a social-ecological ABM on water use. We believe that our expansions help to make the ODD protocol a most suitable protocol to describe social-ecological ABMs and may support the review process of related manuscripts. The ODD+D protocol does not only improve the quality of model descriptions but also improves our understanding of models and is an important necessary step forward developing theory respectively frameworks for social-ecological ABMs.