Wildfire ignition-distribution modelling: a comparative study in the Huron–Manistee National Forest, Michigan, USA

Wildfire ignition distribution models are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar species-distribution models exhibit pronounced differences among model types. Therefore, our goal was to compare the predictive performance, variable importance and the spatial patterns of predicted ignition-probabilities of three ignition-distribution model types: one parametric, statistical model (Generalised Linear Models, GLM) and two machine-learning algorithms (Random Forests and Maximum Entropy, Maxent). We parameterised the models using 16 years of ignitions data and environmental data for the Huron–Manistee National Forest in Michigan, USA. Random Forests and Maxent had slightly better prediction accuracies than did GLM, but model fit was similar for all three. Variables related to human population and development were the best predictors of wildfire ignition locations in all models (although variable rankings differed slightly), along with elevation. However, despite similar model performance and variables, the map of ignition probabilities generated by Maxent was markedly different from those of the two other models. We thus suggest that when accurate predictions are desired, the outcomes of different model types should be compared, or alternatively combined, to produce ensemble predictions.

Bat activity is low in thinned and unthinned stands of red pine

We investigated the use of red pine (Pinus resinosa Ait.) plantations by bats in the Manistee National Forest of Michigan. Using ultrasonic detectors, we compared the activity of bats in the interior of stands of red pine and in openings within the stands, both before and after thinning (mean time after thinning = 7 years). Bat activity was more than 20 times greater in small openings within thinned and unthinned stands than within the stands themselves, and bat activity was associated with greater insect abundance in openings. Thinning lead to a significant change in structural complexity, as shown by a 39% decrease in basal area and a 45% decline in tree density, although these changes did not lead to an increase in use of red pine stands by bats. Red pine plantations, even after thinning, most likely are too structurally complex and have low insect abundance, making them a largely unsuitable habitat for bats.

Landscape ecosystem diversity of river floodplains in northwestern Lower Michigan, U.S.A.

We present a classification and comparison of river floodplains using an ecological, multifactor approach integrating physiography, hydrology, soil, and vegetation within a relatively homogenous macroclimate. Aerial photographs and field reconnaissance were used to locate 22 river valley transects along nine major rivers in the Manistee National Forest, northwestern Lower Michigan. Distinct ecosystems along each transect were sampled extensively. Twenty-three floodplain ecosystem types were identified and classified primarily on the basis of physiographic systems and fluvial landforms within a regional context. Physiographic systems are broad-scale, surficial landforms characterized by distinctive form, parent material, soil, hydrologic regimes, and vegetation. We examined landscape ecosystem differences between different physiographic systems, within a physiographic system, and on a single fluvial landform. Different physiographic systems have different kinds and patterns of floodplain ecosystems in successive valley segments along a river. Within a physiographic system, the physiographic position of different fluvial landforms and ecosystem types within a single fluvial landform leads to marked ecosystem diversity laterally away from the river. The results indicate that physiography is an important determinant of floodplain ecosystem diversity and that an ecological, multifactor approach is useful in distinguishing floodplain ecosystems at multiple scales within a regional context.