The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling, with over 1000 published applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt typically outperforms other methods based on predictive accuracy and 2) the software is particularly easy to use. MaxEnt users must make a number of decisions about how they should select their input data and choose from a wide variety of settings in the software package to build models from these data. The underlying basis for making these decisions is unclear in many studies, and default settings are apparently chosen, even though alternative settings are often more appropriate. In this paper, we provide a detailed explanation of how MaxEnt works and a prospectus on modeling options to enable users to make informed decisions when preparing data, choosing settings and interpreting output. We explain how the choice of background samples reflects prior assumptions, how nonlinear functions of environmental variables (features) are created and selected, how to account for environmentally biased sampling, the interpretation of the various types of model output and the challenges for model evaluation. We demonstrate MaxEnt's calculations using both simplified simulated data and occurrence data from South Africa on species of the flowering plant family Proteaceae. Throughout, we show how MaxEnt's outputs vary in response to different settings to highlight the need for making biologically motivated modeling decisions.

A spatial and mechanistic model is developed for the dynamics of transition 2 STEPHEN W. PACALA ET AL. Ecological MonographsVol. 66, No. l 7) Modeling experiments that determine which aspects of individu~l perf~rma~ce a~d inter-neighbor competition are responsible for each ~f the ro~ust predictiOn~ IdentJ.fied m aspect (4) above and tested in aspect (6) above. This analysis reveals a wide vanety of causal relationships, with most parameters contributing to at least one community level phenomenon.8) An explanation of the diversity of individual level causes identified in aspect (7). The two "axes" describing most of the strategic variation among the species (see [2]), provide a simple explanation of community level pattern in terms of individual level processes.

Abstract. With a view toward understanding species-specific differences in juvenile tree mortality and the community-level implications of these differences, we characterized juvenile survivorship of 10 dominant tree species of oak transition-northern hardwood forests using species-specific mathematical models. The mortality models predict a sapling's probability of dying as a function of its recent growth history. These models and speciesspecific growth functions (published elsewhere), characterize a species' shade tolerance. Combined growth and mortality models express a sapling's probability of mortality as a function of light availability. We describe the statistica! bases and the field methods used to calibrate the mortality models.We examined inter-and intraspecific variation in juvenile mortality across three sites: Great Mountain Forest (low pH, nutrient poor soils) in northwestern Connecticut, a calcareous bedrock region (neutra! pH, nutrient rich soils) also in northwestern Connecticut, and a site in central-western Michigan (low pH, nutrient poor soils).Interspecific differences in juvenile mortality have profound effects on community dynamics and composition; the importance of these effects is demonstrated through a spatially explicit simulator of forest dynamics (SORTIE). The 1 O species we examined occupy a continuum of survivorship levels at 1% of fu li sun.There was surprisingly little intraspecific variation in mortality functions for sugar maple, American beech, eastern hemlock, and white ash between the Great Mountain and Michigan sites. However, there was a striking increase in survivorship for sugar maple in the calcareous site. Differences in survivorship among the sites are correlated with soil pH and presumably nutrient availability.Growth rates in high-light and low-light survivorship are inversely correlated across species; as level of shade tolerance increases, a species grows more slowly in high Iight and exhibits increased survivorship under low Iight. Our results indicate that interspecific differences in sapling mortality are critica! components of forest community dynamics.

Recruitment, the addition of new individuals into a community, is an important factor that can substantially affect community composition and dynamics. We present a method for calibrating spatial models of plant recruitment that does not require identifying the specific parent of each recruit. This method calibrates seedling recruitment functions by comparing tree seedling distributions with adult distributions via a maximum likelihood analysis. The models obtained from this method can then be used to predict the spatial distributions of seedlings from adult distributions.We calibrated recruitment functions for 10 tree species characteristic of transition oaknorthern hardwood forests. Significant differences were found in recruit abundances and spatial distributions. Predicted seedling recruitment limitation for test stands varied substantially between species, with little recruitment limitation for some species and strong recruitment limitation for others. Recruitment was limited due to low overall recruit production or to restricted recruit dispersion. When these seedling recruitment parameters were incorporated into a spatial, individual-based model of forest dynamics, called SOR-TIE, alterations of recruitment parameters produced substantial changes in species abundance, providing additional support for the potential importance of seedling recruitment processes in community structure and dynamics.

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