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Geology topics

Wolf M. Mooij

Publications and source records attributed to Wolf M. Mooij.

18 recordsLinked to original sources
USGS2023

Enhancing the predictability of ecology in a changing world: A call for an organism-based approach

Ecology is usually very good in making descriptive explanations of what is observed, but is often unable to make predictions of the response of ecosystems to change. This has implications in a human-dominated world where a suite of anthropogenic stresses are threatening the resilience and functioning of ecosystems that sustain mankind through a range of critical regulating and supporting services. In ecosystems, cause-and-effect relationships are difficult to elucidate because of complex networks of negative and positive feedbacks. Therefore, being able to effectively predict when and where ecosystems could pass into different (and potentially unstable) new states is vitally important under rapid global change. Here, we argue that such better predictions may be reached if we focus on organisms instead of species, because organisms are the principal biotic agents in ecosystems that react directly on changes in their environment. Several studies show that changes in ecosystems may be accurately described as the result of changes in organisms and their interactions. Organism-based theories are available that are simple and derived from first principles, but allow many predictions. Of these we discuss Trait-based Ecology, Agent Based Models, and Maximum Entropy Theory of Ecology and show that together they form a logical sequence of approaches that allow organism-based studies of ecological communities. Combining and extending them makes it possible to predict the spatiotemporal distribution of groups of organisms in terms of how metabolic energy is distributed over areas, time, and resources. We expect that this “Organism-based Ecology” (OE) ultimately will improve our ability to predict ecosystem dynamics.

Frontiers in Applied Mathematics and Statistics↗
USGS2022

A generically parameterized model of Lake eutrophication: The impact of Stoichiometric ratios and constraints on the abundance of natural phytoplankton communities (GPLake-S)

Water quality improvement to avoid excessive phytoplankton blooms often requires eutrophication management where both phosphorus (P) and nitrogen (N) play a role. While empirical eutrophication studies and ecological resource competition theory both provide insight into phytoplankton abundance in response to nutrient loading, they are not seamlessly linked in the current state of eutrophication research. We argue that understanding species competition for multiple nutrients and light in natural phytoplankton communities is key to assessing phytoplankton abundance under changing nutrient supply. Here we present GPLake-S, a mechanistic model rooted in ecological resource competition theory, which has only eight parameters and can predict chlorophyll- a to nutrient relationships for phytoplankton communities under N, P, N+P colimitation and light limitation. GPLake-S offers a simple mechanistic tool to make first estimates of chlorophyll-a levels and nutrient thresholds for generic lake properties, accounting for variation in N:P ratio preferences of phytoplankton species. This makes the model supportive of water management and policy.

Ecological Modelling↗
USGS2019

Success of lake restoration depends on spatial aspects of nutrient loading and hydrology

Many aquatic ecosystems have deteriorated due to human activities and their restoration is often troublesome. It is proposed here that the restoration success of deteriorated lakes critically depends on hitherto largely neglected spatial heterogeneity in nutrient loading and hydrology. A modelling approach is used to study this hypothesis by considering four lake types with contrasting nutrient loading (point versus diffuse) and hydrology (seepage versus drainage). By comparing the longterm effect of common restoration measures (nutrient load reduction, lake flushing or biomanipulation) in these four lake types, we found that restoration through reduction of nutrient loading is effective in all cases. In contrast, biomanipulation only works in seepage lakes with diffuse nutrient inputs, while lake flushing will even be counterproductive in lakes with nutrient point sources. The main conclusion of the presented analysis is that a priori assessment of spatial heterogeneity caused by nutrient loading and hydrology is essential for successful restoration of lake ecosystems.

Science of the Total Environment↗
USGS2019

A generically parameterized model of lake eutrophication (GPLake) that links field-, lab- and model-based knowledge

Worldwide, eutrophication is threatening lake ecosystems. To support lake management numerous eutrophication models have been developed. Diverse research questions in a wide range of lake ecosystems are addressed by these models. The established models are based on three key approaches: the empirical approach that employs field surveys, the theoretical approach in which models based on first principles are tested against lab experiments, and the process-based approach that uses parameters and functions representing detailed biogeochemical processes. These approaches have led to an accumulation of field-, lab- and model-based knowledge, respectively. Linking these sources of knowledge would benefit lake management by exploiting complementary information; however, the development of a simple tool that links these approaches was hampered by their large differences in scale and complexity. Here we propose a Generically Parameterized Lake eutrophication model (GPLake) that links field-, lab- and model-based knowledge and can be used to make a first diagnosis of lake water quality. We derived GPLake from consumer-resource theory by the principle that lacustrine phytoplankton is typically limited by two resources: nutrients and light. These limitations are captured in two generic parameters that shape the nutrient to chlorophyll- a relations. Next, we parameterized GPLake, using knowledge from empirical, theoretical, and process-based approaches. GPLake generic parameters were found to scale in a comparable manner across data sources. Finally, we show that GPLake can be applied as a simple tool that provides lake managers with a first diagnosis of the limiting factor and lake water quality, using only the parameters for lake depth, residence time and current nutrient loading. With this first-order assessment, lake managers can easily assess measures such as reducing nutrient load, decreasing residence time or changing depth before spending money on field-, lab- or model- experiments to support lake management.

Science of the Total Environment↗
USGS2018

Modeling water quality in the Anthropocene: Directions for the next-generation aquatic ecosystem models

“Everything changes and nothing stands still” (Heraclitus). Here we review three major improvements to freshwater aquatic ecosystem models — and ecological models in general — as water quality scenario analysis tools towards a sustainable future. To tackle the rapid and deeply connected dynamics characteristic of the Anthropocene, we argue for the inclusion of eco-evolutionary, novel ecosystem and social-ecological dynamics. These dynamics arise from adaptive responses in organisms and ecosystems to global environmental change and act at different integration levels and different time scales. We provide reasons and means to incorporate each improvement into aquatic ecosystem models. Throughout this study we refer to Lake Victoria as a microcosm of the evolving novel social-ecological systems of the Anthropocene. The Lake Victoria case clearly shows how interlinked eco-evolutionary, novel ecosystem and social-ecological dynamics are, and demonstrates the need for transdisciplinary research approaches towards global sustainability.

Current Opinion in Environmental Sustainability↗
USGS2010

Challenges and opportunities for integrating lake ecosystem modelling approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘ reinventing the wheel ’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘ having tunnel vision ’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

Aquatic Ecology↗
USGS2007

Exploring the temporal effects of seasonal water availability on the snail kite of Florida: Part III

The Florida snail kite ( Rostrhamus sociabilis ) is an endangered raptor that occurs as an isolated population, currently of about 2,000 birds, in the wetlands of southern and central Florida, USA. Its exclusive prey species, the apple snail ( Pomacea paludosa ) is strongly influenced by seasonal changes in water abundance. Droughts during the snail kite breeding season have a direct negative effect on snail kite survival and reproduction, but droughts are also needed to maintain aquatic vegetation types favorable to snail kite foraging for snails. We used a spatially explicit matrix model to explore the effects of temporal variation in water levels on the viability of the snail kite population under different temporal drought regimes in its wetland breeding habitat. We focused on three aspects of variations in water levels that were likely to affect kites: (1) drought frequency; (2) drought duration; and (3) drought timing within the year. We modeled a 31-year historical scenario using four different scenarios in which the average water level was maintained constant, but the amplitude of water level fluctuations was modified. Our results reveal the complexity of the effects of temporal variation in water levels on snail kite population dynamics. Management implications of these results are discussed. In particular, management decisions should not be based on annual mean water levels alone, but must consider the intra-annual variability.

Florida↗
USGS2006

A standard protocol for describing individual-based and agent-based models

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

Ecological Modelling↗
USGS2005

Inducible defenses in food webs: Chapter 3.4

This chapter reviews the predicted effects of induced defenses on trophic structure and two aspects of stability, “local” stability and persistence, as well as presenting novel results on a third, resilience. Food webs are structures of populations in a given location organized according to their predator–prey interactions. Interaction strengths and, therefore, prey defenses are generally recognized as important ecological factors affecting food webs. Despite this, surprisingly, little light has been shed on the food web-level consequences of inducible defenses. Inducible defenses occur in many taxa in both terrestrial and aquatic food webs. They include refuge use, reduced activity, adaptive life history changes, the production of toxins, synomones and extrafloral nectar, and the formation of colonies, helmets, thorns, or spines. In the chapter, theoretical results for the effects of inducible defenses on trophic structure and the three aspects of stability are reviewed. This is done, in part, using bifurcation analysis—a type of analysis that is applied to nonlinear dynamic systems described by a set of ordinary differential or difference equations. The work presented in the chapter suggests that heterogeneity, as caused by induced defenses in prey species, has major effects on the functioning of food webs. Inducible defenses occur in many species in both aquatic and terrestrial systems, and theoretical work indicates they have major effects on important food web properties such as trophic structure, local stability, persistence, and resilience.

Book chapter↗
USGS2005

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

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.

Science↗
USGS2005

Individual-based modeling of ecological and evolutionary processes

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

Annual Review of Ecology, Evolution, and Systemati↗
USGS2004

Evaluating the effect of salinity on a simulated American Crocodile ( Crocodylus acutus ) population with applications to conservation and Everglades restoration

Everglades restoration will alter the hydrology of South Florida, affecting both water depth and salinity levels in the southern fringes of the Everglades, the habitat of the endangered American crocodile ( Crocodylus acutus ). A key question is what the effects of these hydrologic changes will be on the crocodile population. Reliable predictions of the viability of endangered species under a variety of management scenarios are of vital importance in conservation ecology. Juvenile American crocodiles are thought to be sensitive to high salinity levels, suffering reduced mass, and potentially reduced survivorship and recruitment. This could negatively impact the population recovery. We addressed the management issue of how the crocodile population will respond to alterations in hydrology with a spatially explicit individual-based model. The model is designed to relate water levels, salinities, and dominant vegetation to crocodile distribution, abundance, population growth, individual growth, survival, nesting effort, and nesting success. Our analysis shows that Everglades restoration, through its effects on water flow to estuaries, may benefit crocodile populations if increased freshwater flow reduces the chance that regional salinity levels exceed levels where small individuals lose mass. In addition, we conclude that conservation priority should be placed on reducing anthropogenic sources of mortality on large individuals, such as road mortality. Finally, research should focus on estimates of annual survivorship for large individuals.

Florida↗
USGS2003

Uncertainty in spatially explicit animal dispersal models

Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

Ecological Applications↗
USGS2002

Exploring the effect of drought extent and interval on the Florida snail kite: Interplay between spatial and temporal scales

The paper aims at exploring the viability of the Florida snail kite population under various drought regimes in its wetland habitat. The population dynamics of snail kites are strongly linked with the hydrology of the system due to the dependence of this bird species on one exclusive prey species, the apple snail, which is negatively affected by a drying out of habitat. Based on empirical evidence, it has been hypothesised that the viability of the snail kite population critically depends not only on the time interval between droughts, but also on the spatial extent of these droughts. A system wide drought is likely to result in reduced reproduction and increased mortality, whereas the birds can respond to local droughts by moving to sites where conditions are still favourable. This paper explores the implications of this hypothesis by means of a spatially-explicit individual-based model. The specific aim of the model is to study in a factorial design the dynamics of the kite population in relation to two scale parameters, the temporal interval between droughts and the spatial correlation between droughts. In the model high drought frequencies led to reduced numbers of kites. Also, habitat degradation due to prolonged periods of inundation led to lower predicted numbers of kites. Another main result was that when the spatial correlation between droughts was low, the model showed little variability in the predicted numbers of kites. But when droughts occurred mostly on a system wide level, environmental stochasticity strongly increased the stochasticity in kite numbers and in the worst case the viability of the kite population was seriously threatened.

Ecological Modelling↗