Given the difficulty of separating the three Picea species—P. glauca, P. mariana, and P. rubens (white, black, and red spruce)—in the pollen record, little is known about their unique histories in eastern North America following deglaciation. Here we report the first use of a classification tree analysis (CART) to distinguish pollen grains of these species. It was successfully applied to fossil pollen from eight sites in Maine and one in Massachusetts. We focused on the late glacial/early Holocene (14,000 to 8000 cal yr B.P.) and the late Holocene (1400 cal yr B.P. to present)—the two key periods since deglaciation when Picea has been abundant in the region. The result shows a shift from a Picea forest of P. glauca and P. mariana in the late glacial to a forest of P. rubens and P. mariana in the late Holocene. The small number of P. rubens grains identified from the late glacial/early Holocene samples (<5%) suggests that that species was either absent or rare at most of the sites. The occurrence and distribution of the three species do not reveal any geographic or temporal trend during late glacial time, but the data suggest that they were distributed in local patches on the landscape. The results of this study indicate that the recent population expansion of Picea (1000 to 500 cal yr B.P.) was likely the first time since deglaciation that P. rubens was abundant in the region.

Oil palm plantations are rapidly expanding in tropical areas, although the nature of the impacts on the functional roles of the different species in the ecosystem is poorly understood. The present study is the first assessment of how oil palm affects the functional diversity of birds in the Brazilian Amazon and tests the hypothesis that converting forest to oil palm decreases functional diversity of bird communities, selecting species more tolerant to environmental disturbances. We conducted point counts to survey bird communities in 16 plots in the eastern Amazon. We sampled 32 points in riparian forest, 128 in oil palm and 160 in forested habitats. To test whether the conversion of forest into oil palm plantations affects functional diversity of birds we calculated the FD (Functional Diversity) and FRic (Functional Richness) indices. To examine whether oil palm plantations select species functionally more similar than expected by chance we used a null model (SES.FD). FD was significantly higher in the forest plots in comparison with riparian forests and oil palm, and lower in oil palm when compared with riparian forests. FRic, in turn, was greater in forest plots than in oil palm and in riparian forest. These results show that the conversion of forested areas to oil palm represents a great loss of functional strategies. The SES values indicate that in forested habitats bird communities tend to be functionally clustered while in the oil palm they are functionally overdispersed. The functional traits most affected by oil palm were those associated with diet and foraging stratum. In short, oil palm plantations reduced functional diversity of birds, although the presence of riparian forests within the plantations and the fragments of forest adjacent are extremely important for the maintenance of ecosystem services.

A database of difficult-to-forecast natural persistent deep slab avalanches was analyzed to determine thresholds for parameters that contribute to their release in western Canada. The database included avalanche observations and weather station data. The avalanches were grouped based on their primary cause-of-release, either precipitation loading, wind loading, solar warming or air temperature warming using a multivariate classification tree, which first split using a solar warming parameter. The precipitation group had a median 24 h snowfall of 15 cm and 3 d snowfall of 38 cm at weather stations, mostly at or below treeline. These amounts were likely closer between 20–30 and 50–80 cm at alpine start zones. The wind loading group experienced the most wind-transported snow potential. The solar warming group had predicted solar warming of 5.2°C, 10 cm into the snowpack, on the days of release. The air temperature warming group experienced the highest median maximum air temperature (5°C) on the days of release. These thresholds may be useful to forecast the likelihood of similar avalanches with experienced-based forecasting or with decision aids, although many false alarms are possible. A companion paper, Part II, relates weather model data to avalanche occurrences.

For 175 difficult-to-forecast persistent deep slab avalanches, weather data were obtained from Global Environmental Multiscale (GEM) models produced by Environment Canada. The focus was to determine critical parameters and thresholds for avalanche forecasting from GEM and compare them with weather station data analyzed in Part I (Conlan and Jamieson, this issue). The high-resolution GEM-limited-area model (2.5 km resolution) forecasted higher median precipitation amounts than both the lower-resolution GEM15 (15 km resolution) and weather stations within a small dataset. Air temperatures were lower for both weather models compared with the weather station data, likely because of elevation differences. A multivariate classification tree created with GEM15 data correctly classified 29 of 36 avalanches by their primary cause-of-release, using a primary split of modelled solar warming of 5.9°C, 10 cm into the snowpack. For all 175 avalanches, GEM15 forecasted significantly less precipitation than observed at the weather stations, particularly with multi-day cumulative amounts. The majority of GEM15 surface wind speeds were between 0 and 10 km h−1, producing negligible wind loading amounts. The parameter values may be helpful for predicting future persistent deep slab avalanches. However, GEM output is not always representative of field conditions and should be used in conjunction with other sources.

Comparing q-ary relations on a set $\cal O$ of elementary objects is one of the most fundamental problems ofclassification and combinatorial data analysis. In this paper the specific comparison task that involves classificationtree structures (binary or not) is considered in this context. Two mathematical representations are proposed. One isdefined in terms of a weighted binary relation; the second uses a 4-ary relation. The most classical approaches totree comparison are discussed in the context of a set theoretic representation of these relations. Formal andcombinatorial computing aspects of a construction method for a very general family of association coeficients betweenrelations are presented. The main purpose of this article is to specify the components of this construction, based on apermutational procedure, when the structures to be compared are classification trees.

Comparing q-ary relations on a set ${\cal O}$ ofelementary objects is one of the most fundamental problems ofclassification and combinatorial data analysis. In this paper thespecific comparison task that involvesclassification tree structures (binary or not) is considered in thiscontext. Two mathematical representationsare proposed. One is defined in terms of a weighted binary relation; the second uses a 4-ary relation.The most classical approaches to tree comparison are discussed in thecontext of a set theoretic representation of these relations. Formalandcombinatorial computing aspects of a construction method for a verygeneralfamily of association coefficients between relations are presented. The main purpose of this article is to specify the componentsof this construction, based on a permutational procedure, when thestructuresto be compared are classification trees.