Tag: Ecological

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Modeling Disturbance Spatially using the FVS

We plan to use the Forest Vegetation Simulator (FVS), developed by the USFS over the previous couple of decades, in our ecological-economic model of a managed forest landscape. This week I’ve been thinking a lot about how best to link a representation of white-tailed deer browse with the FVS.

Two good examples I’ve found of the modelling of forest disturbance using FVS are the Fire and Fuels Extension (FFE) developed at the USFS Rocky Mountain Research Station in collaboration with other parties, and the Westwide Pine Beetle Model developed by the Forest Health Technology Enterprise Team (FHTET).

The Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS) links the existing FVS, models that represent fire and fire-effects, and fuel dynamics and crowning submodels. The overall model is currently calibrated for northern Idaho, western Montana, and northeastern Washington. More details on the FFE-FVS can be found here, where you can also download this video about the extension:


The Westwide Pine Beetle Model simulates impacts of mountain beetle (Dendroctonus ponderosae Hokpins), western pine beetle (D. brevicomis Leconte), and Ips species for which western pines are a host. The model simulates the movement of beetles between the forest stands in the landscape using the Parallel Processor Extension (PPE) to represent multiple forest stands in FVS.

A recent paper by Ager and colleagues in Landscape and Urban Planning presents work that links both the FFE and the WPBM to FVS using the PPE:

We simulated management scenarios with and without thinning over 60 years, coupled with a mountain pine beetle outbreak (at 30 years) to examine how thinning might affect bark beetle impacts, potential fire behavior, and their interactions on a 16,000-ha landscape in northeastern Oregon. We employed the Forest Vegetation Simulator, along with sub-models including the Parallel Processing Extension, Fire and Fuels Extension, and Westwide Pine Beetle Model (WPBM). We also compared responses to treatment scenarios of two bark beetle-caused tree mortality susceptibility rating systems. As hypothesized, thinning treatments led to substantial reduction in potential wildfire severity over time. However, contrary to expectations, the WPBM predicted higher bark beetle-caused mortality from an outbreak in thinned versus unthinned scenarios. Likewise, susceptibility ratings were also higher for thinned stands. Thinning treatments favored retention of early seral species such as ponderosa pine, leading to increases in proportion and average diameter of host trees. Increased surface fuel loadings and incidence of potential crown fire behavior were predicted post-outbreak; however, these effects on potential wildfire behavior were minor relative to effects of thinning. We discuss apparent inconsistencies between simulation outputs and literature, and identify improvements needed in the modeling framework to better address bark beetle-wildfire interactions.

Whilst I’m still in the early stages of working out how our model will all fit together, it seems like an approach that takes a similar approach will be suitable for our purposes. We’ll need to develop a model that is able to represent the spatial distribution of the deer population across the landscape and that can specify the impact of those deer densities on the vegetation for given age-height classes (for each veg species). This model would likely then be linked with FVS via the the PPE. So concurrently over the next few months I’m going to be working on developing a model of deer density and browse impacts, coding this model into a structure that will link with FVS-PPE, and acquiring and developing data for model initialization.

Reference
Ager, A.A., McMahan, A., Hayes, J.L. and Smith, E.L. (2007) Modeling the effects of thinning on bark beetle impacts and wildfire potential in the Blue Mountains of eastern Oregon Landscape and Urban Planning 80:3 p.301-311

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Homogenization of the northern U.S. Great Lakes Forests

An email sitting in my inbox this morning directed me toward an article in the latest issue of Landscape Ecology that directly addresses one of the issues I touched on in Saturday’s post; the ‘Maple-ization’ of the western UP Northern Hardwood forests via selective forest harvest and the resulting feedbacks with whitetailed deer populations.

Lisa Schulte and colleagues examined the regional-scale impacts of human land use in the northern U.S. Great Lakes region. They found an overall loss of forestland, lower forest species diversity, functional diversity, and structural complexity compared to pre-Euro-American settlement forests.

Generally, they found evidence of shifts from evergreen conifer (-27.0%) to deciduous hardwood (+22.8%) species between pre-Euro-American settlement and the present time. Specifically, they found marked increases in Aspen (+12.8%) and Maple (+10.1%) and decreases in Pine (-17.5%) and Hemlock (-11.3%) across the area as a whole. However, increases in northern hardwood species were not uniform, and Beech and Birch have decreased (~4% each).


A figure from their paper (above) maps the change in ecoregion characteristics for (A) the extent of open vegetation, (B) dominance of conifers, (C) dominance of aspen (combined Populus tremuloides and P. grandidentata), and (D) dominance of maple (combined Acer saccharum and A. rubrum).

In their discussion the authors (p.1100-01) go on to describe the issues present in our study area;

“Although forests have largely been reestablished across northern portions of the region [following destructive logging in the late 19th century], these forests are on a new trajectory of change rather than recovery toward pre-Euro-American conditions . We attribute lack of recovery to legacies associated with the initial, severe land use conversion, the persistent over-abundance of a keystone herbivore (white-tailed deer), and related management practices that are inattentive to processes that historically promoted vegetation diversity within the region.
…
The excessive deer abundance at present is a feedback of regional forest management; whitetailed deer at high densities are now regarded as a major threat to forest biodiversity and regeneration in the region and elsewhere (Rooney et al. 2004). The commercial logging that is now the most frequent and widespread forest disturbance across the region largely fails to mimic either the local or landscape effects of the historically prevalent disturbances of windthrow and fire (Mladenoff et al. 1993; Scheller and Mladenoff 2002). Rather, current practices of aspen clearcutting and single-tree selection in maple stands continues to foster this divergence and simplification of the forests by largely favoring their regeneration over a greater diversity of tree species (Crow et al. 2002).”

As I discussed just the other day, we’ll be using the model we’re currently developing to examine spatial scenarios directly related to this issue. For example one aim is to examine scenarios of forest management that allow the recreation of historical herbivore disturbance via spatial patterns of vegetation whilst ensuring the future economic sustainability of the forests.

Reference
Schulte, L.A., Mladenoff, D.J., Crow, T.R., Merrick, L.C., and Cleland, D.T. (2007) Homogenization of northern U.S. Great Lakes forests due to land use Landscape Ecology 22:7 1089-1103

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Usefulness of Spatial Landscape Models

Turner et al.’s discussion about the usefulness of spatial models in land management is now a bit of a classic (written in 1995) but it had also been a while since I read it. Re-reading it after coming back from a trip to our study area, many of the paper’s points resonated with what people (many of them natural resource managers) I met with were saying.

Turner et al. suggest that (p.13) “Models that integrate ecological and economic components so that the models can be used to explore both sets of consequences simultaneously are even more valuable [than ecological alone]”. This is the driving rationale for our research project. As it was succinctly put by one potential landowner in the study area, models of this kind will contribute to the development of plans that are based on an ecological approach but backed up with economic justification.

Given the hierarchical nature of landscape ecological processes and the importance of human activity on those processes, Turner et al. highlight (p.15) that “Land ownership has a large impact on management decisions, and a useful contribution of spatially explicit models is the ability to explore the effects of management by various owners within a mosaic of public and private lands.” With a range land owners, including the state and private industrial companies, the UP study area is in this position and the model we are developing will be able to directly consider the impacts of different land owner management strategies for the landscape as a wider region. Thus, one of the driving questions of the research is “how should timber be harvested across space and time in multiple land ownerships to ensure a sustainable landscape?”

One of the most striking things I was told on my trip was that the most useful thing our model would be able to do for land managers would be if it could get people to sit down together to come up with a coherent, sustainable management plan. Again, the links with Turner et al. are clear (p.15); “Communication between land managers and ecologists remains an important challenge, and spatially explicit models have the potential to create a common working framework.”

However, not only is the communication and collaboration side of the research a challenge, but so too is the technical side of things. Turner et al. highlight the issue of data quality; the model will only be as good as the data used and the accurate up-to-date spatial data bases required are expensive to produce. Furthermore, the quality of the data will determine the modeller’s ability to parameterizes the model at a given spatial resolution and extent. I’m currently reviewing the data that has been collected over the past few years by the research group at CSIS regarding the interactions between deer density, tree regeneration and bid habitat, but also the data managed and made available by Michigan’s Department of Natural Resources. Producing an accurate representation of deer population dynamics and movement across the landscape is certainly going to be a challenge. Next, the relationships between deer browse pressure and vegetation regeneration need to be specified and parameterized. The estimates of deer population and location can then be combined with these relationships to dynamically represent the interactions across space.

Once the model is up and running we will be able to examine spatial scenarios of forest management to assess both ecological and economic sustainability. For example, with regard to the appropriate location of mesic confer regeneration “…increasing the [mesic confer] component is expected to increase the number of individuals of conifer-associated bird species. And over time reduce productivity of the summer deer range and expand areas potentially suitable for deer during winter, resulting in a smaller deer herd dispersed over a larger wintering area (Doepker et al, 2001) in turn resulting in less browsing pressure in WUP forests. The eventual size, configuration, contiguousness and/or juxtaposition of restored habitats to existing or historical mesic conifer habitats and winter deer-yards on non-MDNR lands (public and private) may affect the success of these outcomes” (DNR 2004). Right now this confer regeneration is not going well and areas of maple forest are increasing.

Economically, the model should be able to show how different harvest rotations and management plans by private industrial land owners can ensure the most productive use of their land whilst ensuring both ecological and economic sustainability of the landscape. And not only for single landowners. The model should be useful to examine how actions of neighbouring land under differing ownership can work in concert. For example, if the private industrial goal is intensive harvest, maybe the primary objective of the state should be to ensure conifer cover. But the question then is what are the spatial implications of this? Is there any point in confer regeneration (which provides thermal cover for deer in the winter) if the distance between state and corporate land is large and deer cannot move from thermal cover to find food?

These are the sorts of questions and challenges to which spatial landscape models can be applied, and which we are aiming to tackle. Right now though, it’s time to concentrate on the technical development of the model and the representation of the spatio-temporal deer-vegetation interactions.

Reference
Turner, M.G., Arthaud, G.J., Engstrom, R.T, Hejl, S.J., Liu, J., Loeb, S. & McKelvey, K. (1995) Usefulness of Spatially Explicit Population Models in Land Management Ecological Applications, 5:1 12-16.

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Call for submissions to Oekologie August 2007

I’m a little behind but there’s still no harm in advertising that Oekologie #7 is up at The Evangelical Ecologist.

Oekologie #8 will be hosted right here on Direction not Destination in mid-August. Submit your recent writings on ecology and environmental science here. Here’s the details of what we’re looking for from the Oekologie home page:

Oekologie is a blog carnival all about interactions between organisms in a system. While Circus of the Spineless might look for a post discussing the hunting techniques of a trap door spider, Oekologie is looking for posts discussing how a trap door spider’s hunting techniques affect prey populations or its surroundings. While Carnival of the Green might look for a post discussing a big oil policy decision regarding ANWR, Oekologie would accept a post describing the ecological consequences of pipeline construction in the area.

Again, we are looking for posts describing biological interactions – human or nonhuman – with the environment.

Topics may include but are not limited to posts about population genetics, niche/neutral theory, sustainabilty, pollution, climate change, disturbance, exploitation, mutualism, ecosystem structure and composition, molecular ecology, evolutionary ecology, energy usage (by humans or within biological systems, succession, landscape ecology, nutrient cycling, biodiversity, agriculture, waste management, etc. The list goes on and on; I think you get the idea.

Your blog does not have to be an ecology or environmental blog itself, but the post should present an accurate representation of the field.

The post should be spell-checked, grammatically sound, and substantial; we’re not looking for brief reviews. If you are reviewing research, please include solid commentary involving other sources.

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Ecological Approach, Economic Justification

This last week I have been touring around our study area and its wider landscape setting in Michigan’s Upper Peninsula. As well as spending a couple of days in the forest ‘helping out’ with some empirical fieldwork being done by MSc student Megan Metonis on the relationship between northern hardwood forest regeneration, timber harvest gap size, and deer browse, I’ve been talking with local managers from the Department of Natural Resources and other management stakeholders.

Whilst I’ll write more about my trip once I’m back at MSU, one of the key things the DNR indicated they would hope our modelling project might achieve is the improved collaboration of multiple land owners and stakeholders, each with their own priorities and expectations, to build the beginnings of a long-term forestry management plan. Such long-term planning has been virtually non-existent in the past, but it was interesting to see an article in a UP newspaper describing the meeting of corporate land owners, natural resource managers and university academics to discuss future land use, ownership and economic trends. This meeting gives me some hope that improved collaboration for forestry management in this area isn’t impossible. If this is the case, as one potential future land owner suggested, the use of the model we’re developing could help develop plans that are based on an ecological approach but backed up with economic justification.

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Call for Papers: Environmental Micro-simulation

This call for papers for a special issue of Ecological Complexity addresses some of the issues I’ve been discussing recently, and hopes to present examples of multi-model approaches to assess environmental simulation model. If I’d seen this earlier or I might have tried to put something together. As it is I’ll just have to keep my eye open for the issue when it comes out next year sometime.

Call for Papers

Ecological Complexity is pleased to announce a special issue on: Environmental micro-simulation: From data approximation to theory assessment

Spatial micro-simulation has recently become a mainstream element in environmental studies. Essentially, different models, representing the same phenomena, are being extensively published and the “next step” sought is hypothesis testing, regarding the factors that determine system dynamics. However, the problem arises that assessment of environmental theories using spatial micro-simulation lacks a leading paradigm. While the Occam’s razor of positivism, which works perfectly in physics and chemistry, demands datasets covering the entire space of model parameters, the experimental abilities of environmentalists are limited and the data collected in the field represent only a small part of the always multi-dimensional parameter space. Consequently, any given model can be considered as merely approximating the few data sets available for verification and its theoretical validity is thus brought into question.

To overcome this limitation, we propose to generate a virtual world that will allow hypothesis testing based on environmental theory. That is, we propose to implement micro-simulation models using high-resolution GIS database and use them as a surrogate for reality, instead of the limited empirical database. GIS enables a realistically looking virtual world to be generated that, unlike the real one, provides the parameters characteristic of every trajectory. The almost unlimited data that can be generated from such a virtual world can then be used to assess our ability to extract rules and dependencies, estimate parameters and, finally, make applicable forecasts.

This special issue will focus on investigating models as representations of environmental theory with the help of a combination of real data and artificial worlds. We invite innovative research papers that employ different high-resolution models for generating virtual worlds, comparing them to each other, with the aim being to develop a better understanding of environmental theory. Examples can be studies of a model’s robustness, a comparative study of dynamic models, investigation of the limitations of data fitting methods and of a model’s sensitivity to changes in spatial and temporal resolution.

Scope
All sorts of micro-simulation, including cellular automata, agent-based systems, fuzzy systems, ANN and genetic algorithms, are welcome. The environmental systems of interest include, but are not limited, to:

  • Complex ecosystems
  • Landscape ecology
  • Terrain analysis and landscape evolution
  • Agriculture and pastoralism
  • Human-environment interaction
  • Land-use and land-cover changes
  • Urban dynamics

Submission instructions
Abstracts of 2 pages in length should be submitted to the Guest Editors by July 14, 2007. The review process of those abstracts considered to be the most relevant will continue and authors will be required to upload the full manuscript to the Ecological Complexity website by November 1, 2007.

Guest Editors
Tal Svoray
Ben-Gurion University of the Negev,
tsvoray@bgu.ac.il

Itzhak Benenson
Tel Aviv University,
bennya@post.tau.ac.il

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Alternative Model Assessment Criteria

Given the discussion in the previous posts regarding the nature of socio-ecological systems, equifinality and relativism in environmental modelling, how should we go about assessing the worth and performance of our simulation models of human-environment systems?

Simulation models are tangible manifestations of a modellers’ ‘mental model’ of the structure of the system being examined. Socio-Ecological Simulation Models (SESMs) may be thought of as logical and factual arguments made by a modeller, based on their mental model. If the model assumptions hold, these arguments should provide a cogent and persuasive indication of how system states may change under different scenarios of environmental, economic and social conditions. However, the resulting simulation model, based upon a logical and factually coherent mental model, is unlikely to be validated on these two criteria (logic and fact) alone.

First, the problems of equifinality suggest that there are multiple logical model structures that could be implemented for any particular system. Second, accurate mimetic reproduction of an empirical system state by a model may be the most persuasive form of the factual proof of a model in many eyes, but the dangers of affirming the consequent make it impossible to prove temporal predictions in models of open systems are truly accurate. Simulation models may be based on facts about empirical systems, but their results cannot be taken as facts about the modelled empirical system.

Thus, some other criteria alongside the logical and factual criteria will be useful to evaluate or validate a SESM. A third and fourth criteria, for environmental simulation models that consider the interaction of social and ecological systems at least, are available by specifically considering the user(s) of a model and its output. These criteria are closely linked.

My third proposed criterion is the establishment of user trust in the model. Trust is used here in the sense of ‘confidence in the model’. If a person using a model or its results does not trust the model it will likely not be deemed fit for its intended purpose. If confidence is lacking in the model or its results, confidence will consequently be lacking in any knowledge derived, decision made, or policy recommended based upon the model. Thus, the use of trust as a criterion for validation is a form of ‘social validation’, ensuring that user(s) agree the model is a legitimate representation of the system.

The fourth criteria by which a model might achieve legitimacy and receive a favourable evaluation (i.e. be validated), is the provision of some form of utility to the user. This utility will be termed ‘practical adequacy’. If a model is not trusted then it will not be practically adequate for its purpose. However, regardless of trust, if the model is not able to address the problems or questions set by the user then the model is equally practically inadequate.

The addition of these two criteria, centred on the model user rather than the model itself, suggests a shift away from falsification and deduction as model validation techniques, toward more reflexive approaches. The shift in emphasis is away from establishing the truth and mimetic accuracy of a model and toward ensuring trust and practical adequacy. By considering trust and practical adequacy, validation becomes an exercise in model evaluation and reclaims its more appropriate meaning of ‘establising a model’s legitimacy’.

From his observation of experimental physicists and work on the ‘experimenter’s regress’, Collins has arrived at the view that there is no distinction between epistemological criteria and social forces to resolve a scientific dispute. The position outlined previously seems to imply a similar situation for models of open, middle-numbered systems where modellers are required to resort to social criteria to justify their models due the inability to do so convincingly epistemologically. This is not necessarily an idea that many natural scientists will sit comfortably with. However, the shift away from truth and mimetic accuracy should not necessarily be something modellers would object to.

First, all modellers know that their models are not true, exact replications of reality. A model is an approximation of reality – there is no need to create a model system if experimentation on the existing empirical system is possible. Furthermore, accepting the results of a model are not ‘true’ (i.e. in the sense that they are perfect predictions of the future) in no way requires the model be built on incorrect logic or facts. As Hesse notes in criticism of Collins, whilst the resolution of scientific disputes might result from a social decision that is not forced by the facts, “it does not follow that social decision has nothing to do with objective fact”.

Second, regardless of truth and mimetic accuracy, modellers have several options to build trust and ensure practical adequacy scientifically. Ensuring models are logically coherent and not factually invalid (i.e. criteria one and two) will already have come some way to make a scientific case. Furthermore, the traditions of scientific methodological and theoretical simplicity and elegance can be observed, and the important unifying potential across theories and between disciplines that modelling offers can be emphasised. Thus, regardless of the failures of epistemological methods for justifying them, socio-ecological and other environmental simulation models must be built upon solid logical and factual foundations;

“The postmodern world may be a nightmare for … normal science (Kuhn 1962), but science still deserves to be privileged, because it is still the best game in town. … [Scientists] need to continue to be meticulous and quantitative. But more than this, we need scientific models that can inform policy and action at the larger scales that matter. Simple questions with one right answer cannot deliver on that front. The myth of science approaching singular truth is no longer tenable, if science is to be useful in the coming age.”
(Allen et al. p.484)

Post-normal science highlights the importance of finding alternative ways for science to engage with both the problems faced in the contemporary world and the people living in that world. As they have been defined here, SESMs will inherently address questions that will be of concern to more than just scientists, including problems of the ‘risk society’. From a modelling perspective, a post-normal science approach highlights the need to build trust in the eyes of non-scientists such that understanding is fostered.

Further, it emphasises the need for SESMs to be practically adequate such that good decisions can be made promptly. It also implies that the manner in which a ‘normal’ scientist will go about assessing the trustworthiness or practical adequacy of a model (such as the methods described above) will differ markedly from that of a non-scientist. For example, scientific model users will often, but not always, have also been the person to develop and construct the model. In such a case the model will be constructed to ensure the model is practically adequate to address their particular scientific problems and questions.

When the model is to be used by other parties the issue of ensuring practical adequacy will not be so straight-forward, and particularly so when the user is a non-scientist. In such situations, the modeller needs to ask the question ‘practically adequate for what’? The inhabitants of the study areas investigated will have a vested interest in the processes being examined and will themselves have questions that could be addressed by the model. In all probability many of these questions will be ones that the modeller themselves has not considered or, if they have, may not have considered relevant. Further, the questions asked by local stakeholders may be non-scientific – or at least may be questions that environmental scientists are not used to attempting to answer.

The use and improvements in technical approaches (such a spatial error matrices from pixel-by-pixel model assessment) will remain useful and necessary in the future. Here however, I have emphasised potential alternative methods for model validation (assessment) might be useful to utilise the additional information and knowledge which is available from those actors driving change in a socio-ecological system. In other words, there is information within the system of study that is not utilised for model assessment by simply comparing observed and predicted system states. This information is present in the form of local stakeholders’ knowledge and experience.

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Daniel Botkin’s Renegade Blog

Daniel Botkin, eminent Ecologist and author of Discordant Harmonies, has recently started a blog called Reflections of a renegade naturalist. Two recent posts caught my eye.

The days of Smokey Bear, an enduring American icon of wildland management and its efforts to communicate with the public, are apparently numbered. Whilst his message about taking precautions against starting wildfires remains necessary, the underlying ethos of forest (and environmental) management has changed. Once, ecologists’ theoretical foundation was the ‘balance of nature’ and the presence of equilibrium and stability within ecosystems. But over the past three decades this perception has dramatically shifted and now ‘change is natural’ would be a more apt motto. Ecosystems are dynamic. Disturbance, such a wildfire, is now seen as an inherent and necessary component of many landscapes to ensure ecosystem health. This shift in thinking is evident on the Smokey website, with sections discussing the use of prescribed fire, fire’s role in ecosystem function, and the potential pitfalls of excluding fire entirely. George Perry has written an excellent review of these shifts in ecological understanding.


So what about Smokey Bear? His message about taking precautions in wilderness areas still remain of course. But with this new ecological ethos in mind, Botkin was asked for suggestions for a new management mascot. He came up with Morph the Moose. I haven’t seen anything about Morph previously, and a quick Google search currently only throws up 7 hits, so we’ll have to watch out for Morph wandering around with his new message soon.

The second post that got my eye is related to the evaluation of the forest growth model JABOWA that Botkin developed. JABOWA is an individual-based model that considers the establishment, growth and senescence of individual trees. In 1991 JABOWA was used to forecast how potential global warming would influence the Kirtland’s warbler, an endangered species that nests only in Michigan. Botkin and his colleagues forecast that by 2015 the Jack pine habitat of the warbler would decline significantly with detrimental consequences for the warbler. On his blog he suggests that matching this prediction with contemporary observations will be an ideal test to validate the predictions of the JABOWA model. Given my previous discussion about ‘affirming the consequent’ (i.e. deeming a model a true representation of reality if its predictions match observed reality, and false if it does not) it’s good to see Botkin does not suggest a valid prediction indicates the validity of the model itself. We’re advised us to stay tuned for the results. Given the subject matter and quality of the articles on the new renegade blog I certainly will.

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Initial Michigan UP Ecological Economic Modelling Webpage


We now have a very basic webpage online, (very) briefly outlining the Michigan UP Ecological-Economic Modeling project. This is just so that we have an online presence for now – in time we will develop this into a much more comprehensive document detailing the model, its construction and use. Hopefully, at some point in the future we’ll also mount a version of the model online. I’ll keep you posted on the online development of the project.