My first stop in working this out was 'Free Geography Tools' and their series of posts about exporting shapefiles to Google Earth. From their list of free programs, first I tried Shp2KML by Jacob Reimers. Unfortunately this program resulted in some security conflicts with our network so I couldn't use it. Next I tried a second program, also called shp2kml, from Zonum Solutions and that worked a treat. Zonum have several other Google Earth tools that I'll have to try out sometime.
You can download the kml file it produced for the boundary of our study area here (right click, 'save as' or whatever). If you have Google Earth installed you can then just double click that file (once downloaded) and Google Earth will take you right there. When I first created the link above, I hoped that when you clicked on it the file would open automatically in Google Earth - it didn't. But after a little playing I found that kmz files will open automatically in Google Earth. kmz files are simply zipped (compressed) kml files - I used WinRar to zip the kml file and then changed the file suffix from zip to kmz. Click here - the study area file will open automatically in Google Earth (from Firefox at least - see note below). Sweet.
I also exported shapefiles for DNR and private industrial stand boundaries which match up nicely with spatial patterns of vegetation observed in the landscape. Obviously, I can't post these shapefiles online, but you can see evidence of land ownership boundaries in our study area right here. The light green rectangular area is non-DNR land and has been clear cut. The surrounding area is managed by the DNR (possibly selective timber harvest) - the resulting land cover from different management approaches is stark. These are the sorts of patterns and issues we will be able to examine using our ecological-economic landscape model.
[Note - When posting the presentation to our web server I also learned about MS Internet Explorer .png issues. They say they've fixed them, but there still seem to be some problems - try viewing this page in both IE and Firefox and note the difference (hover your cursor over the words at the bottom). Viewing the presentation pages in Firefox means the links to the .kmz files are active - they are not in IE. The issue arose becasue I used OpenOffice Impress to convert my MS PowerPoint file to html files.]
I've been back from our study area in Michigan's Upper Peninsula for over a week so it's about time I posted something about what we were doing up there.
One of the main issues we will study with our integrated ecological-economic landscape model is the impact of whitetail deer (Odocoileus virginianus) herbivory on tree regeneration following cutting. Last November we spent a week planting 2 year-old seedlings in Northern Hardwood forest gaps created by selective timber harvest (like the one in the photo below).
Our plan was to return this spring to examine the impacts of deer browse on these seedlings. In particular, we wanted to examine how herbivory varies across space due to changes in deer population densities (in turn driven by factors such as snow depth).
To this end we selected almost 40 forest sites that would hopefully capture some spatial variation in snowfall and that had recently been selectively harvested. At each site we selected 10 gaps produced by timber harvest in which to plant our seedlings.
In each gap we planted six trees of each of three species: White Spruce (Picea glauca), White Pine (Pinus strobus) and Eastern Hemlock (Tsuga canadensis). We chose these coniferous species as these are examples of the mesic confer species the Michigan DNR are trying to restore across our study area, and because we expected a range of herbivory across these species.
At each site we would also undertake deer pellet counts in the spring to estimate the number of deer in the vicinity of the site during the winter (during which time the browse we were measuring would have occurred).
On returning to the study sites a couple of weeks ago we set about looking for the trees we had planted to measure herbivory and count deer pellets. In some cases, finding the trees we planted was easier said than done. We tried to get our field crews to plant the trees in straight lines with equal spacing between each tree. In general, this was done well but on occasion the line could only be described as crooked at best. Micro-topography, fallen tree trunks and limbs, and slash from previous cutting all contributed to hamper the planned planting system. However, we did pretty well and found well over 90% of the trees.
We haven't begun analyzing our data as yet, but some anecdotal observations stand out. First, the deer preferentially browsed Hemlock over the other species, often removing virtually all non-woody biomass as shown by the 'before and after' examples below (NB - these photographs are not of the same tree and this is not a true before/after comparison).
In some cases, the deer not only removed all non-woody biomass but also pulled the tree out of the ground (as shown below).
In contrast, White Pine was browsed to a much lesser extent and White Spruce was virtually untouched (as shown below).
Having a species that was unaffected by deer (i.e. spruce) often made our job of finding the other trees much easier. Finding heavily browsed Hemlock that no longer had any green vegetation was often tricky against a background of forest floor litter.
The next step now is to start looking at this variation in browse through a more quantitative lens. Then we can start examining how browse and deer densities vary across space and how these variables are related to one another and other factors (such as snow depth and distance to conifer stands).
All-in-all the two weeks of work went pretty well. There were some issues with water-logged roads (due to snow melt) meaning we couldn't get to one or two of the sites we planted at, but generally the weather was pretty good (it only rained heavily one day). I'll write more once we have done more analysis and stop here with a shot I took at sunrise as I left for home.
So I'm back from fieldwork in the UP (via upstate New York). Megan (the Masters student working on our project) is still up there working hard for another week or two though. I'll write more about what we were doing (with some pictures) when I have time later this week.
I'm back in the UP for more fieldwork. Last time I was up here was right before the start of hunting season last year. Since then a hard winter has passed and is now just being replaced by spring. There's still snow on the ground in the northern areas of our study area, but it's melting fast. Over the next couple of weeks we'll be doing deer pellet counts (as a proxy for numbers of deer) to supplement previous data and to try to get a better gauge on how snowfall affects the spatial distribution of deer during the winter. We need to do these as soon after the snow melts before ground level vegetation re-grows and obscures the pellets. We're also going to count pellets in the stands where we planted tree seedlings last fall. Then we'll compare the estimated deer numbers in the stands with the browse on the seedlings we planted (if there's anything left of them at all!) to try to get a more precise handle on how deer density relates to browse impact of different species.
So that's my next few weeks - counting deer poo in the UP forests. I doubt I'll be online much so this might be the last blog for a week or two. I'll take some photos and maybe post them when I'm back in Lansing.
The theme of the meeting was the understanding of patterns, causes, and consequences of spatial heterogeneity for ecosystem function. The three keynote lectures were given by Gary Lovett, Kimberly With and John Foley. I found John Foley's lecture the most interesting and enjoyable of the three - he's a great speaker and spoke on a broader topic than the the others; Agriculture, Land Use and the Changing Biosphere. Real wide-ranging, global sustainability stuff. He highlighted the difficulties of studying agricultural landscapes because of the human cultural and institutional factors, but also stressed the importance of tackling these tricky issues because 'agriculture is the largest disturbance the biosphere has ever seen' and because of its large contribution to greenhouse gas emissions.
Presentations I was particularly interested in were mainly in the 'Landscape Patterns and Ecosystem Processes: The Role of Human Societies', 'Challenges in Modeling Forest Landscapes under Climate Change' and 'Cross-boundary Challenges to the Creation of Multifunctional Agricultural Landscapes' sessions.
In the 'human societies' session, Richard Aspinall discussed the importance of considering human decision-making at a range of scales and Dan Brown again highlighted the importance of human agency in spatial landscape process models. In particular, with regards modelling these systems using agent-based approaches he discussed the difficulty of model calibration at the agent level and stressed that work is still needed on the justification and evaluation phases of agent-based modelling.
The 'modeling forest landscapes' session was focused largely around use of the LANDIS and HARVEST models that were developed in and around Wisconsin. In fact, I don't think I saw any mention of the USFS FVS at the meeting whilst I was there, largely because (I think) FVS has large data demands and is not inherently spatial. LANDIS and HARVEST work at more coarse levels of forest representation (grid cell compared to FVS' individual tree) allowing them to be spatially explicit and to run over large time and space extents. We're confident we'll be able to use FVS in a spatially explicit manner for our study area though, capitalising on the ability of FVS to directly simulate specific timber harvest and economic scenarios.
The 'multifunctional agricultural landscapes' session had an interesting talk by Joan Nassauer on stakeholder science and the challenges it presents. Specific issues she highlighted were: 1. the need for a precise, operational definition of 'stakeholder' 2. ambiguous goals for the use of stakeholders 3. the lack of a canon of replicable methods 4. ambivalence toward the quantification of stakeholder results
Other interesting presentations were given by Richards Hobbs and Carys Swanwick. Richard spoke about the difficulties of 'integrated research' and the importance of science and policy in natural resource management. He suggested that policy-makers 'don't get' systems thinking or modelling, and that some of this may be down to the psychological profiles of the types of people that go into policy making. Such a conclusion suggests scientists need to work harder to bridge the gap to policy makers and do a better job of explaining the emergent properties of the complex systems they study. Carys Swanwick talked about the landscape character assessment, which was interesting for me having moved from the UK to the US about a year ago. Whilst 'wilderness' is an almost alien concept in the UK (and Europe as a whole), landscape character is something that is distinctly absent in the new world agricultural landscapes. Carys talked about the use of landscape character as a tool for conservation and management (in Europe) and the European Landscape Convention. It was a refreshing change from many of the other presentations about agricultural landscape (possibly just because I enjoyed seeing a few pictures of Blighty!).
Unfortunately the weather during the conference was wet which meant that I didn't get out to see as much of Madison as I would have liked. Despite the rain we did go on the Biking Fieldtrip. And yes, we did get soaked. It was also pretty miserable weather for the other fieldtrip to and International Crane Foundation center and the Aldo Leopold Foundation (more on that in a future blog), but interesting nevertheless.
Other highlights of the conference for me were meeting the former members of CSIS and eating dinner one night with Monica Turner. I also got to meet up with Don McKenzie and some of the other 'fire guys', and a couple of people from the Great Basin Landscape Ecology lab where I visited previously. And now I'm already looking forward to the meeting next year in Snowbird, Utah (where I enjoyed the snow this winter).
Final preparations are underway for the US-IALE Symposium in Madison, WI, next week. I've finished the poster that we'll be presenting there on the progress we're making withour ecological-economic forest landscape model. We've also been putting the finishing touches on our posters for the wildfire session at EGU in Vienna (which Raul will be attending and presenting our posters at). Links to .pdf versions of the posters are below. Thoughts and photos from Madison and Chicago (where I'll be stopping off for a couple of days on the way home) on my return.
US-IALE 2008 - Landscape Change and other CSIS involvement
Today I started thinking in earnest about the 2008 US-IALE Symposium to be held in Madison, Wisconsin early next month.
I'll be presenting a poster on our early model development work on the USDA deer/timber regeneration project at CSIS. I will also be chairing the Landscape Change session which has presentations discussing change within and across a diverse range of landscapes including, the Great Plains of the US, the Bolivian Andes and Ukrainian Carpathian mountain ranges, Boreal and Tropical forests, and the Congo Basin.
Whilst in Madison I also plan on attending sessions, symposia, workshops and field-trips devoted to Landscape Patterns and Ecosystem Processes, Modeling Forest Landscapes under Climate Change, Multifunctional Agricultural Landscapes, Forest Landscapes, and Fire. At this last session I'm particularly looking forward to the presentation entitled "Ecological complexity produces simple structure: Power laws in low-severity fire regimes" by Don McKenzie, co-convener of the wildfires session at EGU 2008 the following week (but which I will not be attending).
There will be plenty of other activity by members of CSIS. Jack Liu, president-elect of US-IALE, and CSIS PhD student Vanessa Hull are co-organising the H. Ronald Pulliam Symposium: Sources, Sinks, and Sustainability. Mao-Ning Tuanmu (PhD student) will be making a presentation entitled "Detecting understory vegetation using MODIS data: Implications for giant panda habitat evaluations" in the Remote Sensing session, and Wei Liu (also CSIS PhD student) will present "Conservation success leads to human-wildlife conflicts: Spatial patterns of crop damages and livestock depredation in Wolong Nature Reserve for Giant Pandas, China" in the Social Issues session.
And there's loads more going on so it promises to be an interesting and busy week! If I get online during a spare 5 minutes I'll see if I can blog an update on how it's all going...
Seeing the Wood for the Trees: Pattern-Oriented Modelling
A while back I wrote about the potentially misplaced preoccupation with statistical power in species distribution models. Our attempts at drawing out some relationships between our deer distribution data and descriptors of land cover is proving taxing - the relationships evident at a more coarse spatial resolution (e.g. county level) than we are considering aren't found in our stand-level data. As a result we moving toward taking a modelling approach that is driven less by our empirical data and more by inferences based on multiple information sources. Particularly I'm drawn toward emphasising an approach I first encountered in my undergraduate landscape ecology class taught by George Perry - 'Pattern-Oriented Modelling'.
A prime example of the POM approach is its use to model the spread of rabies through central Europe. The rabies virus has been observed to spread in a wave-like manner, carried by foxes. Grimm et al. (1996) describe how they developed a cellular automate-type model that considers cells (of fox territory) to be in either a healthy, infected or empty state. Through an iterative model development process, their model was gradually refined (i.e. its assumptions and parameters modified) by comparing model results with empirical patterns.
The idea underpinning this iterative POM approach is
"... if we decide to use a pattern for model construction because we believe this pattern contains information about essential structures and processes, we have to provide a model structure which in principle allows the pattern observed to emerge Whether it does emerge depends on the hypotheses we have built into the model."
This approach has been found particularly useful for the development of 'bottom-up' agent-based models. Often understanding of the fine-scale processes driving broad-scale system dynamics and patterns is poor, making it difficult to both structure and parameterise mechanistic models. However, whilst the logical fallacy of affirming the consequent remains, if a model of low-level interactions is able to reproduce higher-level patterns, we can be confident that our model is a better representation of the system mechanics than one that doesn't. Furthermore, the more patterns at different scales that the model reproduces, the mode confident we can be in it. Thus, in POM
"multiple patterns observed in real systems at different hierarchical levels and scales are used systematically to optimize model complexity and to reduce uncertainty."Grimm et al. (2005)
Grimm and Berger outline the general protocol of a pattern-oriented modelling approach (whilst reminding us that there is no standard recipe for model development):
Formulate the question or problem
Assemble hypotheses about essential processes and structures
Assemble (observed) patterns
Choose state variables, parameters and structures
Construct the model
Analyse, test and revise the model
Use patterns for parameterisation
Search for independent predictions
Several iterations of this process will be required to refine the model. In initial iterations, steps 2 and 4 may need to be largely inferential if the state of knowledge about the system is poor. However, by moving iteratively back through these steps, and in particular exploiting steps 6 and 7 to inform us about model performance relative to system behaviour, we can improve our knowledge about the system whilst simultaneously ensuring our model recreates observed patterns. For example, during the development of the landscape fire-succession model in my PhD, I compared the landscape-level model results of different sets of (unknown) flammability probabilities (parameters) of each vegetation type required by the model with empirically observed wildfire regime behaviour. By modifying parameters for individual vegetation types I was able to reproduce the appropriate wildfire frequency-area distribution for Mediterranean-type environments that had previously been found (I'm currently writing this up for publications - more soon).
But what does this all have to do with our model of the relationship between deer browse and timber harvest in Michigan's Upper Pensinsula? Well, right now I think we're at steps 2,3 and 4 (all at the same time). As our deer and land cover relationships are weak at the stand-level (which is the level we are considering so that we can integrate the model with an economic module), I am currently developing hypotheses (i.e. assumptions) about the structure of the system from previous research on different specific aspects of similar systems. Furthermore, we're continuing to look for spatial patterns in both vegetation and deer distribution so that we can compare the results of our hypothetical model.
For example, one thing I'm struggling with right now is is how to establish the probability of which individual trees (or saplings) will be removed from a stand due to a given level of deer browse (which in turn is dependent upon a deer density). This is not something that has been explicitly studied (and would be very difficult to study at the landscape level). Therefore we need to parameterise this process in order for the model to function. We should be able to do this by comparing several different parameterisations to empirically observed patterns such as spatial configuration of forest types classified by age class or age/species distributions at the stand-level. That's the idea anyway - we'll see how it goes over the next months...
In the meantime, next week I head back to the study area for the first stage of our seedling experiment. We're planting seedlings now across a gradient of browse and site conditions with the intention of returning in the spring to see what has been browsed and count deer pellets. This should improve our understanding of the link between pellet counts and browse pressure and provide us with some more empirical patterns which we can use in our ongoing model development.
A few pictures from our trip to the UP study area this past week.
The fall was almost over. We were out on a recce to find sites for an experiment we're setting up over the next couple of weeks to examine the impact of deer browse on seedlings of various conifer species.
We want to locate our seedling planting on both state and commercial lands - cutting had recently finished at this commercial site.
We also visited a deer exclosure set up to examine tree regeneration in the absence of deer browse (similar in many ways to our experiment). It's not the best picture, but the effects of 12 years of protection can be seen - very little regeneration on the left of the fence but evidence of green juveniles on the right. These effects haven't been quantified at this site but by sight alone there's clearly difference outside s inside the exclosure.
Finally, not all the leaves had fallen. We were a couple of weeks late for the real colours, but some remained down on the Lake Michigan coastline.
The past week or two I've been wrestling with the data we have on white-tailed deer density and vegetation in Michigan's Upper Peninsula in an attempt to find some solid statistical relationships that we might use in our ecological-economic simulation model. However, I seem to be encountering similar issues to previous researchers, notably (as Weisberg and Bugmann put it) "the weak signal-to noise ratio that is characteristic of ungulate-vegetation systems", that "multiple factors need to be considered, if we are to develop a useful, predictive understanding of ungulate-vegetation relationships", and that "ungulate-vegetation interactions need to be better understood over multiple scales".
Hobbs suggests that one of the problems slowing species distribution research is a preoccupation with statistical power that he calls "the tyranny of power". This tyranny arises, he suggests, because traditional statistical methods that are powerful at smaller scales become less useful at larger extents. There are at least three reasons for this including,
small things are more amenable to study by traditional methods than large things
variability increases with scale (extent)
potential for bias increases with scale (extent)
"The implication of the tyranny of power is that many of the traditionally sanctioned techniques for ecological investigation are simply not appropriate at large-scales... This means that inferences at large-scales are likely to require research designs that bear little resemblance to the approaches many of us learned in graduate school."Hobbs p.230
However, this tyranny may simply be because, as Fortin and Dale point out, "most study areas contain more than one ecological process that can act at different spatial and temporal scales". That is, the processes are non-stationary in time and space. Leaving time aside for now, spatial non-stationarity has already been found to be present in our study area with regards the processes we're considering. For example, Shi and colleagues found that Geographically Weighted Regression (GWR) models are better at predicting white-tailed deer densities than an ordinary least-squares regression model for the entirety of our study area.
Hobbs' argument suggests that it's often useful analyse ecological data from large regions by partitioning them into smaller, more spatially homogenous areas. The idea is that these smaller patches are more likely to be governed by the same ecological process. But how should these smaller regions be selected? A commonly used geographical division is the ecoregion. Ecoregions divide land into areas of similar characteristics such as climate, soils, vegetation and topography. For our study area we've found that relationships between deer densities and predictor variables do indeed vary by Albert's ecoregions. But we think that there might be more useful ways to divide our study area that take into account variables that are commonly believed to strongly influence spatial deer distributions. In Michigan's UP the prime example is the large snow fall is received each winter and which hinders deer movement and foraging.
We're beginning to examine how GWR and spatial boundary analysis might be used to delineate these areas (at different scales) in the hope of refining our understanding about the interaction of deer and vegetation across our large (400,000 ha) landscape. In turn we should be able to better quantify some of these relationships for use in our model.
"Increasing drought conditions across Michigan have increased the fire danger to very high. Department of Natural Resources wildfire officials are asking outdoor enthusiasts to use caution with outdoor fires."
Over the weekend erratic winds have fanned a fire to greater than 12,000 acres in the UP, just north of Tahquamenon Falls State Park. More here.
Update - 4th January 2008 On 29th August 2007 Michigan DNR reported the Sleeper Lake fire was 95% contained and at ~18,000 acres was the third largest fire in Michigan history.
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.
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.
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 Planning80:3 p.301-311
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 Ecology22:7 1089-1103
Some of the State natural resource manager I met with spoke about the 'Maple-ization' of the forests in the western UP - whilst a native of these forests, the economic value of Maple wood is leading to the removal of other Northern Hardwood species and an (over) dominance of Maple.
The Mackinac Bridge, linking the Upper and Lower peninsulas of Michigan, celebrates its 50th birthday this year. Currently the third-longest Suspension Bridge in the world (at 1.7 miles of suspended roadway) it was originally dubbed the 'Bridge to Nowhere'. Now however, it provides a vital (though recently decreasing) influx of tourist dollars to the UP. Whilst impressive, IMHO the Mackinac Bridge doesn't have a patch on the Bristolian's beloved Clifton Suspension Bridge.
Many of those tourists crossing the Mackinac Bridge head to Tahquamenon Falls. The second largest waterfalls east of the Mississippi (after Niagra), at peak flow more than 50,000 gallons of water per second flow over the edge.
Checkout the location of these pics, and others I took on my trip, at the photos page.
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.
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.
I'm heading off to the UP later today to visit our study area for the first time. I'm looking forward to actually seeing place we're going to be modelling and to get a better intuitive understanding about how the system works and what the issues are. Whilst I'm up there I plan on helping out with some ongoing MSU Northern Hardwood seedling experiments and meeting with people involved in the use and management of the region at organisations such as Michigan's Department of Natural Resources, the Hiawatha National Forest, The Nature Conservancy, and the Hannahville Indian Community. I'll be offline whilst I'm away - I'll let you know how it went when I'm back.
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 d
