Building Climates Zones of California Climate Zone Descriptions for New Buildings - California is divided into 16 climatic boundaries or climate zones, which is incorporated into the Energy Efficiency Standards (Energy Code). Each Climate zone has a unique climatic condition that dictates which minimum efficiency requirements are needed for that specific climate zone. The numbers used in the climate zone map don't have a title or legend. The California climate zones shown in this map are not the same as what we commonly call climate areas such as "desert" or "alpine" climates. The climate zones are based on energy use, temperature, weather and other factors.This is explained in the Title 24 energy efficiency standards glossary section:"The Energy Commission established 16 climate zones that represent a geographic area for which an energy budget is established. These energy budgets are the basis for the standards...." "(An) energy budget is the maximum amount of energy that a building, or portion of a building...can be designed to consume per year.""The Energy Commission originally developed weather data for each climate zone by using unmodified (but error-screened) data for a representative city and weather year (representative months from various years). The Energy Commission analyzed weather data from weather stations selected for (1) reliability of data, (2) currency of data, (3) proximity to population centers, and (4) non-duplication of stations within a climate zone."Using this information, they created representative temperature data for each zone. The remainder of the weather data for each zone is still that of the representative city." The representative city for each climate zone (CZ) is:CZ 1: ArcataCZ 2: Santa RosaCZ 3: OaklandCZ 4: San Jose-ReidCZ 5: Santa MariaCZ 6: TorranceCZ 7: San Diego-LindberghCZ 8: FullertonCZ 9: Burbank-GlendaleCZ10: RiversideCZ11: Red BluffCZ12: SacramentoCZ13: FresnoCZ14: PalmdaleCZ15: Palm Spring-IntlCZ16: Blue Canyon

The Energy Commission has developed this app to quickly and accurately show addresses and locations to determine California’s climate regions. We invite builders and building officials to use this app to determine the climate zones applicable to building projects.Please note:Building Climates Zones of California Climate Zone Descriptions for New Buildings - California is divided into 16 climatic boundaries or climate zones, which is incorporated into the Energy Efficiency Standards (Energy Code). Each Climate zone has a unique climatic condition that dictates which minimum efficiency requirements are needed for that specific climate zone. The California climate zones shown in this map are not the same as what we commonly call climate areas such as "desert" or "alpine" climates. The climate zones are based on energy use, temperature, weather and other factors.This is explained in the Title 24 energy efficiency standards glossary section:"The Energy Commission established 16 climate zones that represent a geographic area for which an energy budget is established. These energy budgets are the basis for the standards...." "(An) energy budget is the maximum amount of energy that a building, or portion of a building...can be designed to consume per year.""The Energy Commission originally developed weather data for each climate zone by using unmodified (but error-screened) data for a representative city and weather year (representative months from various years). The Energy Commission analyzed weather data from weather stations selected for (1) reliability of data, (2) currency of data, (3) proximity to population centers, and (4) non-duplication of stations within a climate zone."Using this information, they created representative temperature data for each zone. The remainder of the weather data for each zone is still that of the representative city." The representative city for each climate zone (CZ) is:CZ 1: ArcataCZ 2: Santa RosaCZ 3: OaklandCZ 4: San Jose-ReidCZ 5: Santa MariaCZ 6: TorranceCZ 7: San Diego-LindberghCZ 8: FullertonCZ 9: Burbank-GlendaleCZ10: RiversideCZ11: Red BluffCZ12: SacramentoCZ13: FresnoCZ14: PalmdaleCZ15: Palm Spring-IntlCZ16: Blue CanyonThe original detailed survey definitions of the 16 Climate Zones are found in the 1995 publication, "California Climate Zone Descriptions for New Buildings."

A plant's performance is governed by the total climate: length of growing season, timing and amount of rainfall, winter lows, summer highs, wind, and humidity.Sunset's climate zone maps take all these factors into account, unlike the familiar hardiness zone maps devised by the U.S. Department of Agriculture, which divides most of North America into zones based strictly on winter lows.ZONE 2A: Cold mountain and intermountain areasAnother snowy winter climate, Zone 2A covers several regions that are considered mild compared with surrounding climates. You’ll find this zone stretched over Colorado’s northeastern plains, a bit of it along the Western Slope and Front Range of the Rockies, as well as mild parts of river drainages like those of the Snake, Okanogan, and the Columbia. It also shows up in western Montana and Nevada and in mountain areas of the Southwest. This is the coldest zone in which sweet cherries and many apples grow. Winter temperatures here usually hover between 10 and 20°F (–12 to –7°C) at night, with drops between –20 and –30°F (–29 and –34°C) every few years. When temperatures drop below that, orchardists can lose even their trees. The growing season is 100 to 150 days.ZONE 3A: Mild areas of mountain and intermountain climatesEast of the Sierra and Cascade ranges, you can hardly find a better gardening climate than Zone 3a.Winter minimum temperatures average from 15 to 25°F (–9 to –4°C), with extremes between –8 and –18°F (–22 and –28°C). Its frost-free growing season runs from 150 to 186 days. The zone tends to occur at lower elevations in the northern states (eastern Oregon and Washington as well as Idaho), but at higher elevations as you move south crossing Utah’s Great Salt Lake and into northern New Mexico and Arizona. Fruits and vegetables that thrive in long, warm summers, such as melons, gourds, and corn, tend to do well here. This is another great zone for all kinds of deciduous fruit trees and ornamental trees and shrubs. Just keep them well watered.ZONE 18: Above and below the thermal belts in Southern CaliforniaZones 18 and 19 are classified as interior climates. This means that the major influence on climate is the continental air mass; the ocean determines the climate no more than 15 percent of the time. Many of the valley floors of Zone 18 were once regions where apricot, peach, apple, and walnut orchards flourished, but the orchards have now given way to homes. Although the climate supplies enough winter chill for some plants that need it, it is not too cold (with a little protection) for many of the hardier sub-tropicals like amaryllis. It is too hot, too cold, and too dry for fuchsias but cold enough for tree peonies and many apple varieties, and mild enough for a number of avocado varieties. Zone 18 never supplied much commercial citrus, but home gardeners who can tolerate occasional minor fruit loss can grow citrus here. Over a 20-year period, winter lows averaged from 22 to 17°F (–6 to –8°F).The all-time lows recorded by different weather stations in Zone 18 ranged from 22 to 7°F (–6 to –14°C).ZONE 19: Thermal belts around Southern California's interior valleysLike that of neighboring Zone 18, the climate in Zone 19 is little influenced by the ocean. Both zones, then, have very poor climates for such plants as fuchsias, rhododendrons, and tuberous begonias. Many sections of Zone 19 have always been prime citrus-growing country—especially for those kinds that need extra summer heat in order to grow sweet fruit. Likewise, macadamia nuts and most avocados can be grown here. The Western Plant Encyclopedia cites many ornamental plants that do well in Zone 19 but are not recommended for its neighbor because of the milder winters in Zone 19. Plants that grow well here, but not in much colder zones, include bougainvillea, bouvardia, calocephalus, Cape chestnut (Calodendrum), flame pea (Chorizema), several kinds of coral tree (Erythrina), livistona palms, Mexican blue and San Jose hesper palms (Brahea armata, B. brandegeei), giant Burmese honeysuckle (Lonicera hildebrandiana), myoporum, several of the more tender pittosporums, and lady palm (Rhapis excelsa). Extreme winter lows over a 20-year period ranged from 28 to 22°F (–2 to –6°C) and the all-time lows at different weather stations range from 23 to 17°F (–5 to –8°C). These are considerably higher than the temperatures in neighboring Zone 18.ZONE 20: Cool winters in Southern CaliforniaIn Zones 20 and 21, the same relative pattern prevails as in Zones 18 and 19. The even-numbered zone is the climate made up of cold-air basins and hilltops, and the odd-numbered one comprises thermal belts. The difference is that Zones 20 and 21 get weather influenced by both maritime air and interior air. In these transitional areas, climate boundaries often move 20 miles in 24 hours with the movements of these air masses. Because of the greater ocean influence, this climate supports a wide variety of plants. You can see the range of them at the Los Angeles County Arboretum in Arcadia. Typical winter lows are 37° to 43°F (3 to 6°C); extreme 20-year lows average from 25 to 22°F (–4 to –6°C).All-time record lows range from 21 to 14°F (–6 to –10°C).ZONE 21: Thermal belts in Southern CaliforniaThe combination of weather influences described for Zone 20 applies to Zone 21 as well. Your garden can be in ocean air or a high fog one day and in a mass of interior air (perhaps a drying Santa Ana wind from the desert) the next day. Because temperatures rarely drop very far below 30°F (–1°C), this is fine citrus growing country. At the same time, Zone 21 is also the mildest zone that gets sufficient winter chilling for most forms of lilacs and certain other chill-loving plants. Extreme lows—the kind you see once every 10 or 20 years—in Zone 21 average 28 to 25°F (–2 to –4°C).All-time record lows in the zone were 27 to 17°F (–3 to –8°C).ZONE 22: Cold-winter portions of Southern CaliforniaAreas falling in Zone 22 have a coastal climate (they are influenced by the ocean approximately 85 percent of the time).When temperatures drop in winter, these cold-air basins or hilltops above the air-drained slopes have lower winter temperatures than those in neighboring Zone 23. Actually, the winters are so mild here that lows seldom fall below freezing. Extreme winter lows (the coldest temperature you can expect in 20 years) average 28 to 25°F (–2 to –4°C). Gardeners who plant under overhangs or tree canopies can grow subtropical plants that would otherwise be burned by a rare frost. Such plants include bananas, tree ferns, and the like. The lack of a pronounced chilling period during the winter limits the use of such deciduous woody plants as flowering cherry and lilac. Many herbaceous perennials from colder regions fail here because the winters are too warm for them to go dormant.ZONE 23: Thermal belts of Southern CaliforniaOne of the most favored areas in North America for growing subtropical plants, Zone 23 has always been Southern California’s best zone for avocados. Frosts don’t amount to much here, because 85 percent of the time, Pacific Ocean weather dominates; interior air rules only 15 percent of the time. A notorious portion of this 15 percent consists of those days when hot, dry Santa Ana winds blow. Zone 23 lacks either the summer heat or the winter cold necessary to grow pears, most apples, and most peaches. But it enjoys considerably more heat than Zone 24—enough to put the sweetness in ‘Valencia’ oranges, for example—but not enough for ‘Washington’ naval oranges, which are grown farther inland. Temperatures are mild here, but severe winters descend at times. Average lows range from 43 to 48°F (6 to 9°C), while extreme lows average from 34 to 27°F (1 to –3°C).ZONE 24: Marine influence along the Southern California coastStretched along Southern California’s beaches, this climate zone is almost completely dominated by the ocean. Where the beach runs along high cliffs or palisades, Zone 24 extends only to that barrier. But where hills are low or nonexistent, it runs inland several miles.This zone has a mild marine climate (milder than Northern California’s maritime Zone 17) because south of Point Conception, the Pacific is comparatively warm. The winters are mild, the summers cool, and the air seldom really dry. On many days in spring and early summer, the sun doesn’t break through the high overcast until afternoon. Tender perennials like geraniums and impatiens rarely go out of bloom here; spathiphyllums and pothos become outdoor plants; and tender palms are safe from killing frosts. In this climate, gardens that include such plants as ornamental figs, rubber trees, and scheffleras can become jungles.Zone 24 is coldest at the mouths of canyons that channel cold air down from the mountains on clear winter nights. Several such canyons between Laguna Beach and San Clemente are visible on the map. Numerous others touch the coast between San Clemente and the Mexican border. Partly because of the unusually low temperatures created by this canyon action, there is a broad range of winter lows in Zone 24. Winter lows average from 42°F (5°C) in Santa Barbara to 48°F (9°C) in San Diego. Extreme cold averages from 35° to 28°F (2 to –2°C), with all-time lows in the coldest stations at about 20°F (–6°C).The all-time high temperatures aren’t greatly significant in terms of plant growth. The average all-time high of weather stations in Zone 24 is 105°F (41°C). Record heat usually comes in early October, carried to the coast by Santa Ana winds. The wind’s power and dryness usually causes more problems than the heat itself—but you can ameliorate scorching with frequent sprinkling.

Local climate zones have been developed in the climatology field to characterize the landscape surrounding climate monitoring stations, toward adjusting for local landscape influences on measured temperature trends. For example, a station surrounded by tall buildings may be influenced by the urban heat island effect compared to a station in an agricultural area. The local climate zone classification system was developed by Iain Stewart and Tim Oke at the University of British Columbia. The classification scheme has been adopted by the World Urban Database Access and Tools Portal (WUDAPT) project, which aims to produce local climate zone maps for the entire world at a scale of ~ 100m. Local climate zones take building and vegetation type and height into account, and therefore serve as indicators of urban form, from dense urban (high building with little vegetation) to industrial/commercial (large lowrise buildings with paved areas) and natural (dense trees, low plants, water). How local climate zones are related to human health is a new area of research.CANUE staff and students worked in collaboratation with WUDAPT researchers to map local climate zones for Canada, using scripts developed in Google Earth Engine and applied to LandSat imagery for key time periods. Each postal code has been assigned to one of 14 local climate zone classes. In adition, seven groups have been created by aggregating similar local climate zones, and the percentage of group in the neighbourhood (1km2) around each postal code has been calculated.

Regional boundaries for use by CA Nature to support activities related to Executive Order N-82-20. These include California's 30x30 effort, Climate Smart Land Strategies, and equitable access to open space. This layer is derived from the 4th California Climate Assessment regions, and enhanced using the California County Boundaries dataset (version 19.1) maintained by the California Department of Forestry and Fire Protection's Fire Resource Assessment Program, and the 3 Nautical Mile marine boundary for California sourced from the California Department of Fish and Wildlife.

The North American Climate Zones map shows the distribution of climate types across Canada, Mexico, and the United States based on the Köppen-Geiger climate classification. This map is derived from the global climate zones presented by Beck et al. (2018), “Present and future Köppen-Geiger climate classification maps at 1-km resolution,” and represents the spatial distribution in vector format of 29 climate zones (out of 30 global climate zones) present in North America. This map was produced by resampling the original input data spatial resolution of 0.0083 degrees to 0.016 degrees and cropping the global data to the North American region. The map was used to meet the needs of the CEC project “Improving the effectiveness of early warning systems for drought” in assessing the effectiveness of available drought indicators and indices in climate zones of North America. Reference: Beck, H., Zimmermann, N., McVicar, T. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci Data 5, 180214 (2018). https://doi.org/10.1038/sdata.2018.214 Files Download

Contained within 3rd Edition (1957) of the Atlas of Canada is a map that shows the division of Canada into climatic regions according to the classification of the climates of the world developed by W. Koppen. Koppen first divided the world into five major divisions to which he assigned the letters A, B, C, D, and E. The letters represent the range of divisions from tropical climate (A) to polar climate (E). There are no A climates in Canada. The descriptions of the four remaining major divisions are given in the map legend. Koppen then divided the large divisions into a number of climatic types in accordance with temperature differences and variations in the amounts and distribution of precipitation, on the basis of which he added certain letters to the initial letter denoting the major division. The definitions of the additional letters which apply in Canada are also given when they first appear in the map legend. Thus b is defined under Csb and the definition is, therefore, not repeated under Cfb, Dfb or Dsb. For this map, the temperature and precipitation criteria established by Koppen have been applied to Canadian data for a standard thirty year period (1921 to 1950 inclusive).

Local climate zones have been developed in the climatology field to characterize the landscape surrounding climate monitoring stations, toward adjusting for local landscape influences on measured temperature trends. For example, a station surrounded by tall buildings may be influenced by the urban heat island effect compared to a station in an agricultural area. The local climate zone classification system was developed by Iain Stewart and Tim Oke at the University of British Columbia. The classification scheme has been adopted by the World Urban Database Access and Tools Portal (WUDAPT) project, which aims to produce local climate zone maps for the entire world at a scale of ~ 100m. Local climate zones take building and vegetation type and height into account, and therefore serve as indicators of urban form, from dense urban (high building with little vegetation) to industrial/commercial (large lowrise buildings with paved areas) and natural (dense trees, low plants, water). How local climate zones are related to human health is a new area of research.CANUE staff and students worked in collaboratation with WUDAPT researchers to map local climate zones for Canada, using scripts developed in Google Earth Engine and applied to LandSat imagery for key time periods. Each postal code has been assigned to one of 14 local climate zone classes. In adition, seven groups have been created by aggregating similar local climate zones, and the percentage of group in the neighbourhood (1km2) around each postal code has been calculated.

The United States Geological Survey has published "An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems" in Global Ecology and Conservation Journal. This work was produced by a team led by Roger Sayre, Ph.D., Senior Scientist for Ecosytems at the USGS Land Change Science Program with the support from The Nature Conservancy and Esri. We described this work using two introduction story maps, Introduction to World Ecosystems Map and Introduction to World Climate Regions Map. This story map is an introduction for World Climate Regions Map. You can have more information by accessing the published paper and you can access the dataset by downloading the pro package.

Machine-readable summary of key horticultural traits extracted from the page.

The California State Energy Commission established climate zones that represent an area for which an energy budget is established. An energy budget is the maximum amount of energy that a building, or portion of a building can be designed to consume per year.

"Vegetation Zones of Canada: a Biogeoclimatic Perspective" maps Canadian geography in relation to gradients of regional climate, as expressed by potential vegetation on zonal sites. Compared to previous similar national-scale products, "Vegetation Zones of Canada" benefits from the work of provincial and territorial ecological classification programs over the last 30+ years, incorporating this regional knowledge of ecologically significant climatic gradients into a harmonized national map. This new map, reflecting vegetation and soils adapted to climates prior to approximately 1960, can serve as a broad-scale (approximately 1:5 M to 1:10 M) geospatial reference for monitoring and modeling effects of climate changes on Canadian ecosystems. "Vegetation Zones of Canada: a Biogeoclimatic Perspective" employs a two-level hierarchical legend. Level 1 vegetation zones reflect the global-scale latitudinal gradient of annual net radiation, as well as the effects of high elevation and west to east climatic and biogeographic variation across Canada. Within the level 1 vegetation zones, level 2 zones distinguish finer scale variation in zonal vegetation, especially in response to elevational and arctic climatic gradients, climate-related floristics and physiognomic diversity in the Great Plains, and maritime climatic influences on the east and west coasts. Thirty-three level 2 vegetation zones are recognized: High Arctic Sparse Tundra Mid-Arctic Dwarf Shrub Tundra Low Arctic Shrub Tundra Subarctic Alpine Tundra Western Boreal Alpine Tundra Cordilleran Alpine Tundra Pacific Alpine Tundra Eastern Alpine Tundra Subarctic Woodland-Tundra Northern Boreal Woodland Northwestern Boreal Forest West-Central Boreal Forest Eastern Boreal Forest Atlantic Maritime Heathland Pacific Maritime Rainforest Pacific Dry Forest Pacific Montane Forest Cordilleran Subboreal Forest Cordilleran Montane Forest Cordilleran Rainforest Cordilleran Dry Forest Eastern Temperate Mixed Forest Eastern Temperate Deciduous Forest Acadian Temperate Forest Rocky Mountains Foothills Parkland Great Plains Parkland Intermontane Shrub-Steppe Rocky Mountains Foothills Fescue Grassland Great Plains Fescue Grassland Great Plains Mixedgrass Grassland Central Tallgrass Grassland Cypress Hills Glaciers Please cite this dataset as: Baldwin, K.; Allen, L.; Basquill, S.; Chapman, K.; Downing, D.; Flynn, N.; MacKenzie, W.; Major, M.; Meades, W.; Meidinger, D.; Morneau, C.; Saucier, J-P.; Thorpe, J.; Uhlig, P. 2019. Vegetation Zones of Canada: a Biogeoclimatic Perspective. [Map] Scale 1:5,000,000. Natural Resources Canada, Canadian Forest Service. Great Lake Forestry Center, Sault Ste. Marie, ON, Canada.

Data Sources:CanCoast 2.0 Arctic Shoreline, Backshore Slope, Coastal Materials, Tidal Range, and 12 NM Coastal ZoneManson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669Esri World Topographic Basemap:

https://basemaps.arcgis.com/arcgis/rest/services/World_Basemap_v2/VectorTileServerEsri World Imagery Basemap:

https://services.arcgisonline.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0/WMTSCapabilities.xmlthumbnail:https://deeply.thenewhumanitarian.org/arctic/articles/2017/01/25/going-going-gone-canadian-arctic-faces-threat-of-coastal-erosion

The Open Geospatial Consortium (OGC) Federated Marine Spatial Data Infrastructure (FMSDI) Pilot 2023 project is important to Esri Canada as it will help show leadership in the use of modern geospatial technology, standards, and approaches to finding and combining land and marine spatial data across the Canadian Arctic regions. The goal of this work was to demonstrate how spatial data could be used to analyze and visualize the impacts of climate change on the environment, infrastructure, and inhabitants of Arctic coastal regions. Glaciers in the Canadian Arctic region(Unsplash.com)

Aim: Effective management decisions depend on knowledge of species distribution and habitat use. Maps generated from species distribution models are important in predicting previously unknown occurrences of protected species. However, if populations are seasonally dynamic or locally adapted, failing to consider population level differences could lead to erroneous determinations of occurrence probability and ineffective management. The study goal was to model the distribution of a species of special concern, Townsend’s big-eared bats (Corynorhinus townsendii), in California. We incorporate seasonal and spatial differences to estimate the distribution under current and future climate conditions. Methods: We built species distribution models using all records from statewide roost surveys and by subsetting data to seasonal colonies, representing different phenological stages, and to Environmental Protection Agency Level III Ecoregions to understand how environmental needs vary based on these factors. We projected species’ distribution for 2061-2080 in response to low and high emissions scenarios and calculated the expected range shifts. Results: The estimated distribution differed between the combined (full dataset) and phenologically-explicit models, while ecoregion-specific models were largely congruent with the combined model. Across the majority of models, precipitation was the most important variable predicting the presence of C. townsendii roosts. Under future climate scnearios, distribution of C. townsendii is expected to contract throughout the state, however suitable areas will expand within some ecoregions. Main conclusion: Comparison of phenologically-explicit models with combined models indicate the combined models better predict the extent of the known range of C. townsendii in California. However, life history-explicit models aid in understanding of different environmental needs and distribution of their major phenological stages. Differences between ecoregion-specific and statewide predictions of habitat contractions highlight the need to consider regional variation when forecasting species’ responses to climate change. These models can aid in directing seasonally explicit surveys and predicting regions most vulnerable under future climate conditions. Methods Study area and survey data The study area covers the U.S. state of California, which has steep environmental gradients that support an array of species (Dobrowski et al. 2011). Because California is ecologically diverse, with regions ranging from forested mountain ranges to deserts, we examined local environmental needs by modeling at both the state-wide and ecoregion scale, using U.S. Environmental Protection Agency (EPA) Level III ecoregion designations and there are thirteen Level III ecoregions in California (Table S1.1) (Griffith et al. 2016). Species occurrence data used in this study were from a statewide survey of C. townsendii in California conducted by Harris et al. (2019). Briefly, methods included field surveys from 2014-2017 following a modified bat survey protocol to create a stratified random sampling scheme. Corynorhinus townsendii presence at roost sites was based on visual bat sightings. From these survey efforts, we have visual occurrence data for 65 maternity roosts, 82 hibernation roosts (hibernacula), and 91 active-season non-maternity roosts (transition roosts) for a total of 238 occurrence records (Figure 1, Table S1.1). Ecogeographical factors We downloaded climatic variables from WorldClim 2.0 bioclimatic variables (Fick & Hijmans, 2017) at a resolution of 5 arcmin for broad-scale analysis and 30 arcsec for our ecoregion-specific analyses. To calculate elevation and slope, we used a digital elevation model (USGS 2022) in ArcGIS 10.8.1 (ESRI, 2006). The chosen set of environmental variables reflects knowledge on climatic conditions and habitat relevant to bat physiology, phenology, and life history (Rebelo et al. 2010, Razgour et al. 2011, Loeb and Winters 2013, Razgour 2015, Ancillotto et al. 2016). To trim the global environmental variables to the same extent (the state of California), we used the R package “raster” (Hijmans et al. 2022). We performed a correlation analysis on the raster layers using the “layerStats” function and removed variables with a Pearson’s coefficient > 0.7 (see Table 1 for final model variables). For future climate conditions, we selected three general circulation models (GCMs) based on previous species distribution models of temperate bat species (Razgour et al. 2019) [Hadley Centre Global Environment Model version 2 Earth Systems model (HadGEM3-GC31_LL; Webb, 2019), Institut Pierre-Simon Laplace Coupled Model 6th Assessment Low Resolution (IPSL-CM6A-LR; Boucher et al., 2018), and Max Planck Institute for Meteorology Earth System Model Low Resolution (MPI-ESM1-2-LR; Brovkin et al., 2019)] and two contrasting greenhouse concentration trajectories (Shared Socio-economic Pathways (SSPs): a steady decline pathway with CO2 concentrations of 360 ppmv (SSP1-2.6) and an increasing pathway with CO2 reaching around 2,000 ppmv (SSP5-8.5) (IPCC6). We modeled distribution for present conditions future (2061-2080) time periods. Because one aim of our study was to determine the consequences of changing climate, we changed only the climatic data when projecting future distributions, while keeping the other variables constant over time (elevation, slope). Species distribution modeling We generated distribution maps for total occurrences (maternity + hibernacula + transition, hereafter defined as “combined models”), maternity colonies , hibernacula, and transition roosts. To estimate the present and future habitat suitability for C. townsendii in California, we used the maximum entropy (MaxEnt) algorithm in the “dismo” R package (Hijmans et al. 2021) through the advanced computing resources provided by Texas A&M High Performance Research Computing. We chose MaxEnt to aid in the comparisons of state-wide and ecoregion-specific models as MaxEnt outperforms other approaches when using small datasets (as is the case in our ecoregion-specific models). We created 1,000 background points from random points in the environmental layers and performed a 5-fold cross validation approach, which divided the occurrence records into training (80%) and testing (20%) datasets. We assessed the performance of our models by measuring the area under the receiver operating characteristic curve (AUC; Hanley & McNeil, 1982), where values >0.5 indicate that the model is performing better than random, values 0.5-0.7 indicating poor performance, 0.7-0.9 moderate performance and values of 0.9-1 excellent performance (BCCVL, Hallgren et al., 2016). We also measured the maximum true skill statistic (TSS; Allouche, Tsoar, & Kadmon, 2006) to assess model performance. The maxTSS ranges from -1 to +1:values <0.4 indicate a model that performs no better than random, 0.4-0.55 indicates poor performance, (0.55-0.7) moderate performance, (0.7-0.85) good performance, and values >0.80 indicate excellent performance (Samadi et al. 2022). Final distribution maps were generated using all occurrence records for each region (rather than the training/testing subset), and the models were projected onto present and future climate conditions. Additionally, because the climatic conditions of the different ecoregions of California vary widely, we generated separate models for each ecoregion in an attempt to capture potential local effects of climate change. A general rule in species distribution modeling is that the occurrence points should be 10 times the number of predictors included in the model, meaning that we would need 50 occurrences in each ecoregion. One common way to overcome this limitation is through the ensemble of small models (ESMs) (Breiner et al. 2015., 2018; Virtanen et al. 2018; Scherrer et al. 2019; Song et al. 2019) included in ecospat R package (references). For our ESMs we implemented MaxEnt modeling, and the final ensemble model was created by averaging individual bivariate models by weighted performance (AUC > 0.5). We also used null model significance testing with to evaluate the performance of our ESMs (Raes and Ter Steege 2007). To perform null model testing we compared AUC scores from 100 null models using randomly generated presence locations equal to the number used in the developed distribution model. All ecoregion models outperformed the null expectation (p<0.002). Estimating range shifts For each of the three GCMs and each RCP scenario, we converted the probability distribution map into a binary map (0=unsuitable, 1=suitable) using the threshold that maximizes sensitivity and specificity (Liu et al. 2016). To create the final maps for each SSP scenario, we summed the three binary GCM layers and took a consensus approach, meaning climatically suitable areas were pixels where at least two of the three models predicted species presence (Araújo and New 2007, Piccioli Cappelli et al. 2021). We combined the future binary maps (fmap) and the present binary maps (pmap) following the formula fmap x 2 + pmap (from Huang et al., 2017) to produce maps with values of 0 (areas not suitable), 1 (areas that are suitable in the present but not the future), 2 (areas that are not suitable in the present but suitable in the future), and 3 (areas currently suitable that will remain suitable) using the raster calculator function in QGIS. We then calculated the total area of suitability, area of maintenance, area of expansion, and area of contraction for each binary model using the “BIOMOD_RangeSize” function in R package “biomod2” (Thuiller et al. 2021).

This highly specialized publication (Ontario Tree Seed Transfer Policy data) is available in English only in accordance with Regulation 671/92, which exempts it from translation under the French Language Services Act. To obtain information in French, please contact the Ministry of Natural Resources and Forestry at (1-800-667-1940).

The Ontario Tree Seed Transfer Policy ensures that seed used to regenerate forests has a good chance of producing trees that are adapted to their growing environment. It specifies where seed can be collected and used and the conditions under which seed may be transferred.

The data is provided as part of Appendix 1 of the Ontario Tree Seed Transfer Policy. It is available in both table and map formats , and also includes CSV and shape files.

Tabular display

This dataset includes three tables that show the spatial direction of the seed transfer policy based on the climate similarity analysis (refer to Appendix 1 of the policy for information on the climate similarity analysis):

• Table 1. For transitional period: Acceptable seed transfer from the 2010 Seed Zones of Ontario to current seed zones
• Table 2. Acceptable seed transfer from the 2010 Seed Zones of Ontario to ecodistricts
• Table 3. Acceptable seed transfer among ecodistricts

Within the tables, you can click and sort by your location of interest to understand the best seed sources to collect from or deploy to. You can sort by either seed zone or ecodistrict.

The policy recommends a climate similarity of 0.9 or greater to the targeted collection or deployment site.

Visual display

The climate similarity analysis used in developing this policy is also available as an interactive map.

Maps are available to help you make seed collection and deployment decisions, including:

• collecting seed by ecodistrict or county
• deploying seed by ecodistrict
• deploying seed by seed zone

You can also view:

• a detailed map of management unit by seed zone or by ecodistrict
• maps to help you make seed transfer decisions related to growing season, precipitation and temperature

These boundaries define the regions used in by CA Nature to support activities related to Executive Order N-82-20. These include California's 30x30 effort, Climate Smart Land Strategies, and equitable access to open space. This layer is derived from the 4th California Climate Assessment regions, and enhanced using the California County Boundaries dataset (version 19.1) maintained by the California Department of Forestry and Fire Protection's Fire Resource Assessment Program, and the 3 Nautical Mile marine boundary for California sourced from the National Oceanographic and Atmospheric Administration.

This dataset represents future climate change projections for Durham Region developed as part of the Guide to Conducting a Climate Change Analysis: Lessons Learned in Durham Region (2020). The dataset includes summary information for 52 climate parameters under the RCP8.5 (business-as-usual or high emissions) and RCP4.5 (moderate) emissions scenario for the short (2011-2040), medium (2041-2070) and long-term (2071-2100) future using an ensemble of climate models. For more information, visit https://www.durham.ca/en/living-here/climateenergyandresilience.aspx?_mid_=32210. A copy of the Guide can be made available upon request.

Wind erosion risk for unprotected soils in areas sensitive to climatic change is shown on this map. The regions that would have the highest sensitivity to a warming climate are likely to occur in the southern and central Prairies and in the southernmost part of Ontario. This risk of wind erosion is based on the nature of local climate and vegetation. Areas with dryer, warmer climates and with sparse vegetation cover are more vulnerable to wind erosion. The levels of climate sensitivity were derived by comparing present and future ecoclimatic regions of Canada, based on the assumption of a doubling of atmospheric carbon dioxide concentrations over pre-industrial levels.