Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use.” Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty.

/pdf/species-distribution-models-ecological-explanation-and-1szux2yl31.pdf

Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

Multivariate analysis provides statistical methods for study of the joint rela­ tionships of variables in data that contain intercorrelations. Because several variables can be considered simultaneously, interpretations can be made that are not possible with univariate statistics. Applications are now common in medicine (117), agriculture (218), geology (50), the social sciences (7, 178, 193), and other disciplines. The opportunity for succinct summaries of large data sets, especially in the exploratory stages of an investigation, has contrib­ uted to an increasing interest in multivariate methods. The first applications of multivariate analysis in ecology and systematics were in plant ecology (54, 222) and numerical taxonomy (187) more than 30 years ago. In our survey of the literature, we found 20 major summaries of recent applications. Between 1978 and 1988, books, proceedings of sym­ posia, and reviews treated applications in ecology (73, 126, 155, 156), ordination and classification (13, 53, 67, 78,81,83,90,113,121,122,159), wildlife biology (33, 213), systematics (148), and morphometries (45, 164,

/pdf/multivariate-analysis-in-ecology-and-systematics-panacea-or-1y5ebeycpq.pdf

Multivariate analysis in ecology and systematics: panacea or pandora's box?

/pdf/handbook-of-field-methods-for-monitoring-landbirds-3mxtt71f7n.pdf

Handbook of Field Methods for Monitoring Landbirds

http://rbasicsworkshop.weebly.com/uploads/1/8/6/0/18603232/peres-neto_etal_2005.pdf

How many principal components? stopping rules for determining the number of non-trivial axes revisited

– Habitat is important in determining stream carrying capacity and population density in young Atlantic salmon and brown trout. We review stream habitat selection studies and relate results to variable and interacting abiotic and biotic factors. The importance of spatial and temporal scales are often overlooked. Different physical variables may influence fish position choice at different spatial scales. Temporally variable water flows and temperatures are pervasive environmental factors in streams that affect behavior and habitat selection. The more frequently measured abiotic variables are water depth, water velocity (or stream gradient), substrate particle size, and cover. Summer daytime, feeding habitats of Atlantic salmon are size structured. Larger parr (>7 cm) have a wider spatial niche than small parr. Selected snout water velocities are consistently low (3–25 cm. s−1). Mean (or surface) water velocities are in the preferred range of 30–50 cm. s−1, and usually in combination with coarse substratum (16–256 mm). However, salmon parr demonstrate flexibility with respect to preferred water velocity, depending on fish size, intra- and interspecific competition, and predation risk. Water depth is less important, except in small streams. In large rivers and lakes a variety of water depths are used by salmon parr. Summer daytime, feeding habitat of brown trout is also characterized by a narrow selection of low snout water velocities. Habitat use is size-structured, which appears to be mainly a result of intraspecific competition. The small trout parr (<7 cm) are abundant in the shallow swift stream areas (<20–30 cm depths, 10–50 cm. s−1 water velocities) with cobble substrates. The larger trout have increasingly strong preferences for deep-slow stream areas, in particular pools. Water depth is considered the most important habitat variable for brown trout. Spatial niche overlap is considerable where the two species are sympatric, although young Atlantic salmon tend to be distributed more in the faster flowing and shallow habitats compared with trout. Habitat use by salmon is restricted through interspecific competition with the more aggressive brown trout (interactive segregation). However, subtle innate differences in behavior at an early stage also indicate selective segregation. Seasonal changes in habitat use related to water temperatures occur in both species. In winter, they have a stronger preference for cover and shelter, and may seek shelter in the streambed and/or deeper water. At low temperatures (higher latitudes), there are also marked shifts in habitat use during day and night as the fish become nocturnal. Passive sheltering in the substrate or aggregating in deep-slow stream areas is the typical daytime behavior. While active at night, the fish move to more exposed holding positions primarily on but also above the substrate. Diurnal changes in habitat use take place also in summer; brown trout may utilize a wider spatial niche at night with more fish occupying the shallow-slow stream areas. Brown trout and young Atlantic salmon also exhibit a flexible response to variability in streamflows, wherein habitat selection may change considerably. Important topics in need of further research include: influence of spatial measurement scale, effects of temporal and spatial variability in habitat conditions on habitat selection, effects of interactive competition and trophic interactions (predation risk) on habitat selection, influence of extreme natural events on habitat selection use or suitability (floods, ice formation and jams, droughts), and individual variation in habitat use or behavior.

Spatial niche variability for young Atlantic salmon (Salmo salar) and brown trout (S. trutta) in heterogeneous streams

The use of multivariate statistics in studies of wildlife habitat

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The use of multivariate statistics in studies of wildlife habitat