This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic location of Nunavut, Canada. The time period coverage is from 47900000 to 37800000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of paleoceanography with a geographic location of North Pacific Ocean. The time period coverage is from 4580295 to 1975132 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing (carbon dioxide) with a geographic location of Global. The time period coverage is from 65000000 to 0 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

The global paleo food market is estimated at US$ 11.2 billion in 2023. The market is expected to rise to US$ 19.4 billion by 2033, registering a CAGR of 5.6% between 2023 and 2033.

Data Points	Key Statistics
Expected Market Value in 2023	US$ 11.2 billion
Projected Market Value by 2033	US$ 19.4 billion
Growth Rate (2023 to 2033)	5.6% CAGR

How The Market Progressed till June 2022?

Market Statistics	Details
H1,2021 (A)	5.7%
H1,2022 Projected (P)	5.8%
H1,2022 Outlook (O)	6.4%
BPS Change: H1,2022 (O) - H1,2022 (P)	(+) 58 ↑
BPS Change: H1,2022 (O) - H1,2021 (A)	(+) 63.8 ↑

(2017 to 2022) Market Demand Outlook for Paleo Food Compared to Forecast (2023 to 2033)

Attribute	Valuation
2025	US$ 12.49 billion
2028	US$ 14.71 billion
2032	US$ 18.29 billion

Historical CAGR (2017 to 2022)	9.3%
Forecast CAGR (2023 to 2033)	5.6%

Category-wise Insights

Taxonomy	Product Type
Top Segment	Vegetables
Forecast CAGR	5.2%

Taxonomy	End Use
Top Segment	Cereals
Forecast CAGR	5%

Holocene climate reconstructions are useful for understanding the diverse features and spatial heterogeneity of past and future climate change. Here we present a database of western North American Holocene paleoclimate records. The database gathers paleoclimate time series from 184 terrestrial and marine sites, including 381 individual proxy records. The records span at least 4000 of the last 12 000 years (median duration of 10 725 years) and have been screened for resolution, chronologic control, and climate sensitivity. Records were included that reflect temperature, hydroclimate, or circulation features. The database is shared in the machine readable Linked Paleo Data (LiPD) format and includes geochronologic data for generating site-level time-uncertain ensembles. This publicly accessible and curated collection of proxy paleoclimate records will have wide research applications, including, for example, investigations of the primary features of ocean–atmospheric circulation along the eastern margin of the North Pacific and the latitudinal response of climate to orbital changes.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic location of United States Of America. The time period coverage is from 23000000 to 5500000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic location of Global. The time period coverage is from 415000000 to 3000000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of loess and paleosol with a geographic location of China, Eastern Asia. The time period coverage is from 20500000 to 6500000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic location of Global. The time period coverage is from 324000000 to 950000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic location of Colorado, United States Of America. The time period coverage is from 51550000 to 49320000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing (carbon dioxide) with a geographic location of Western Pacific Ocean. The time period coverage is from 15690000 to 900000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing|plant macrofossils with a geographic _location of Wyoming, United States Of America. The time period coverage is from 66000000 to 65000000 in calendar years before present (BP). See metadata information for parameter and study _location details. Please cite this study when using the data.

The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).

The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).

Jupyter workflows to extract information from the resources using Hydroshare THREDDS Data Service: https://github.com/Geodels/paleoPhysiography

Understanding factors driving diversity across biodiversity hotspots is critical for formulating conservation priorities in the face of ongoing and escalating environmental deterioration. While biodiversity hotspots encompass a small fraction of Earth's land surface, more than half the world's plants and two-thirds of terrestrial vertebrate species are endemic to these hotspots. Tropical Southeast Asia displays extraordinary species richness, encompassing four biodiversity hotspots, though disentangling multiple potential drivers of species richness is confounded by the region's dynamic geological and climatic history. Here, we use multi-locus molecular genetic data from dense multi-species sampling of freshwater fishes across three biodiversity hotspots, to test the effect of Quaternary climate change and resulting drainage rearrangements on aquatic faunal diversification. While Cenozoic geological processes have clearly shaped evolutionary history in Southeast Asian halfbeak fishes, we show that paleo-drainage re-arrangements resulting from Quaternary climate change played a significant role in the spatiotemporal evolution of lowland aquatic taxa, and provides priorities for conservation efforts.

These data were compiled from published paleo-CO₂ data that have been assembled by an international group of proxy experts supported through an NSF-funded Research Coordination Network. It brings together paleo-CO₂ reconstruction data from terrestrial and marine samples, and the compilation includes data derived from multiple proxies including Phytoplankton, Boron, Stomatal Frequencies, Leaf Gas Exchange, Liverworts, C3 Plants, Paleosols, and Nahcolite. These are used in the interactive archive plot made available on the Paleo-CO2 project web page at (https://www.paleo-co2.org) and are also archived in the NCDC database (https://www.ncdc.noaa.gov/paleo/study/35079).

Paleo Food Market Size, Share, Forecast, & Trends Analysis by Type (Vegetables and Fruits, Meat, Nuts & Seeds, Oil & Fats), Application (Cereals, Bakery Products), Distribution Channel (Offline {Supermarkets}, Online)- Global Forecast to 2032

June 1998.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Forcing. The data include parameters of climate forcing with a geographic _location of Idaho, United States Of America. The time period coverage is from 15780000 to 15740000 in calendar years before present (BP). See metadata information for parameter and study _location details. Please cite this study when using the data.

PALEO-PGEM-Series is a global spatiotemporal dataset of the climate over the last 5 million years, derived from the intermediate complexity atmosphere-ocean general circulation model PLASIM-GENIE using emulation and downscaling techniques (Holden et al. 2019). It consists of estimates of monthly temperature (in degrees Celsius), monthly precipitation (in millimeters), and 17 bioclimatic variables over the last 5 million years every 1,000 years at 1º x 1º spatial resolution.We provide the mean and the standard deviation of the estimates across the 10 stochastic GCM emulation runs. We suggest that users take advantage of these uncertainty estimates by conducting sensitivity tests to assess how robust results derived using PALEO-PGEM-Series are in the face of emulation uncertainty.Each .txt file contains 19,233 rows representing geographic grided cells and 5003 columns, the first two with coordinates (longitude and latitude) and the others with the estimates for each time slice, starting from 5,000,000 years and ending with the pre-industrial. Each column is named with “T” followed by a number representing the time in years divided by 1,000 (i.e., T5000 corresponds to time 5,000,000 years ago). These tables can easily be converted into spatial files (e.g., raster) and visualized and explored using GIS libraries. We also provide the data as netcdf raster files, which are included in the pastclim R package (https://doi.org/10.1111/ecog.06481).We provide an R script to derive the 17 bioclimatic variables from the monthly estimates (code adapted from the function biovars in R package dismo, Hijmans et al. 2021). These bioclimatic variables summarize central tendencies (e.g., annual means), seasonality (e.g., range of monthly means) and extreme conditions (e.g., maximum and minimum monthly means) of relevance for ecological and evolutionary studies. Mean diurnal range (BIO 2) and isothermality (BIO 3) cannot be derived from PALEO-PGEM-Series as they require diurnal cycles. Maximum (BIO 5) and minimum temperature (BIO 6) are modified versions of the original bioclimatic variables, as they are derived from monthly means and thus refer to the maximum and minimum monthly means of temperatures in the year. Consequently, the temperature annual range (BIO 7) is also with reference to monthly means.

Climatic niches describe the climatic conditions in which species can persist. Shifts in climatic niches have been observed to coincide with major climatic change, suggesting that species adapt to new conditions. We test the relationship between rates of climatic niche evolution and paleo-climatic conditions through time for 71 Old-World flycatcher species (Aves: Muscicapidae). We combine niche quantification for all species with dated phylogenies to infer past changes in the rates of niche evolution rates for temperature and precipitation niches. Paleo-climatic conditions were inferred independently using two datasets: a paleo-elevation reconstruction and the mammal fossil record. We find changes in climatic niches through time, but no or weak support for a relationship between niche evolution rates and rates of paleo-climatic change for both temperature and precipitation niche and for both reconstruction methods. In contrast, the inferred relationship between climatic conditions and niche evolution rates depends on paleo-climatic reconstruction method: rates of temperature niche evolution are significantly negatively related to absolute temperatures inferred using the paleo-elevation model but not those reconstructed from the fossil record. We suggest that paleo-climatic change might be a weak driver of climatic niche evolution in birds and highlight the need for greater integration of different paleo-climate reconstructions.