The regulation of body weight and composition involves input from genes and the environment, demonstrated, for example, by the variable susceptibility of inbred strains of mice to obesity when offered a high-fat diet. The identification of the gene responsible for obesity in the ob/ob mouse provides a new approach to defining links between diet and genetics in the regulation of body weight. The ob gene protein product, leptin, is an adipocyte-derived circulating protein. Administration of recombinant leptin reduces food intake and increases energy expenditure in ob/ob mice, suggesting that it signals to the brain the magnitude of fat stores. Information on the regulation of this protein is limited. In several rodent models of obesity including db/db, fa/fa, yellow (Ay/a) VMH-lesioned, and those induced by gold thioglucose, monosodium glutamate, and transgenic ablation of brown adipose tissue, leptin mRNA expression and the level of circulating leptin are increased, suggesting resistance to one or more of its actions. We have assessed the impact of increased dietary fat on circulating leptin levels in normal FVB mice and FVB mice with transgene-induced ablation of brown adipose tissue. We find that high-fat diet evokes a sustained increase in circulating leptin in both normal and transgenic mice, with leptin levels accurately reflecting the amount of body lipid across a broad range of body fat. However, despite increased leptin levels, animals fed a high-fat diet became obese without decreasing their caloric intake, suggesting that a high content of dietary fat changes the 'set point' for body weight, at least in part by limiting the action of leptin.

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Brown adipose tissue, because of its capacity for uncoupled mitochondrial respiration, has been implicated as an important site of facultative energy expenditure. This has led to speculation that this tissue normally functions to prevent obesity. Attempts to ablate or denervate brown adipose tissue surgically have been uninformative because it exists in diffuse depots and has substantial capacity for regeneration and hypertrophy. Here we have used a transgenic toxigene approach to create two lines of transgenic mice with primary deficiency of brown adipose tissue. At 16 days, both lines have decreased brown fat and obesity. In one line, brown fat subsequently regenerates and obesity resolves. In the other line, the deficiency persists and obesity, with its morbid complications, advances. Obesity develops in the absence of hyperphagia, indicating that brown fat deficient mice have increased metabolic efficiency. As obesity progresses, transgenic animals develop hyperphagia. This study supports a critical role for brown adipose tissue in the nutritional homeostasis of mice.

This study addresses the need to provide comprehensive historical climate data and climate change projections at a scale suitable for, and readily accessible to, researchers and resource managers. This database for western North America (WNA) includes over 20 000 surfaces of monthly, seasonal, and annual climate variables from 1901 to 2009; several climate normal periods; and multimodel climate projections for the 2020s, 2050s, and 2080s. A software package, ClimateWNA, allows users to access the database and query point locations, obtain time series, or generate custom climate surfaces at any resolution. The software uses partial derivative functions of temperature change along elevation gradients to improve medium-resolution baseline climate estimates and calculates biologically relevant climate variables such as growing degree-days, number of frost-free days, extreme temperatures, and dryness indices. Historical and projected future climates are obtained by using monthly temperature and precipitation anomalies to adjust the interpolated baseline data for the location of interest. All algorithms used in the software package are described and evaluated against observations from weather stations across WNA. The downscaling algorithms substantially improve the accuracy of temperature variables over the medium-resolution baseline climate surfaces. Climate variables that are usually calculated from daily data are estimated from monthly climate variables with high statistical accuracy.

The orphan nuclear receptor, peroxisome proliferator-activated receptor (PPAR) ␥ , is implicated in mediating expression of fat-specific genes and in activating the program of adipocyte differentiation. The potential for regulation of PPAR ␥ gene expression in vivo is unknown. We cloned a partial mouse PPAR ␥ cDNA and developed an RNase protection assay that permits simultaneous quantitation of mRNAs for both ␥ 1 and ␥ 2 isoforms encoded by the PPAR ␥ gene. Probes for detection of adipocyte P2, the obese gene product, leptin, and 18S mRNAs were also employed. Both ␥ 1 and ␥ 2 mRNAs were abundantly expressed in adipose tissue. PPAR ␥ 1 expression was also detected at lower levels in liver, spleen, and heart; whereas, ␥ 1 and ␥ 2 mRNA were expressed at low levels in skeletal muscle. Adipose tissue levels of ␥ 1 and ␥ 2 were not altered in two murine models of obesity (gold thioglucose and ob/ob), but were modestly increased in mice with toxigene-induced brown fat ablation uncoupling protein diphtheria toxin A mice. Fasting (12-48 h) was associated with an 80% fall in PPAR ␥ 2 and a 50% fall in PPAR ␥ 1 mRNA levels in adipose tissue. Western blot analysis demonstrated a marked effect of fasting to reduce PPAR ␥ protein levels in adipose tissue. Similar effects of fasting on PPAR ␥ mRNAs were noted in all three models of obesity. Insulin-deficient (streptozotocin) diabetes suppressed adipose tissue ␥ 1 and ␥ 2 expression by 75% in normal mice with partial restoration during insulin treatment. Levels of adipose tissue PPAR ␥ 2 mRNA were increased by 50% in normal mice exposed to a high fat diet. In obese uncoupling protein diphtheria toxin A mice, high fat feeding resulted in de novo induction of PPAR ␥ 2 expression in liver. We conclude (

A new ecosystem-based climate envelope modeling approach was applied to assess potential climate change impacts on forest communities and tree species. Four orthogonal canonical discriminant functions were used to describe the realized climate space for British Columbia's ecosystems and to model portions of the realized niche space for tree species under current and predicted future climates. This conceptually simple model is capable of predicting species ranges at high spatial resolutions far beyond the study area, including outlying populations and southern range limits for many species. We analyzed how the realized climate space of current ecosystems changes in extent, elevation, and spatial distribution under climate change scenarios and evaluated the implications for potential tree species habitat. Tree species with their northern range limit in British Columbia gain potential habitat at a pace of at least 100 km per decade, common hardwoods appear to be generally unaffected by climate change, and some of the most important conifer species in British Columbia are expected to lose a large portion of their suitable habitat. The extent of spatial redistribution of realized climate space for ecosystems is considerable, with currently important sub-boreal and montane climate regions rapidly disappearing. Local predictions of changes to tree species frequencies were generated as a basis for systematic surveys of biological response to climate change.

When confronted with an adaptive challenge, such as extreme temperature, closely related species frequently evolve similar phenotypes using the same genes. Although such repeated evolution is thought to be less likely in highly polygenic traits and distantly related species, this has not been tested at the genome scale. We performed a population genomic study of convergent local adaptation among two distantly related species, lodgepole pine and interior spruce. We identified a suite of 47 genes, enriched for duplicated genes, with variants associated with spatial variation in temperature or cold hardiness in both species, providing evidence of convergent local adaptation despite 140 million years of separate evolution. These results show that adaptation to climate can be genetically constrained, with certain key genes playing nonredundant roles.

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