Environmental changes in biodiversity hotspot ecosystems ofSouth Ecuador: RESPonse and feedback effECTs (FOR2730)

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1-7 of 7 datasets.

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» Land use/land cover map of South Ecuador 1987 created by: Hanna Meyer, Boris Thies, Jörg Bendix (last update: 2011-11-07)

» Land use/land cover map of South Ecuador 2001 created by: Hanna Meyer, Boris Thies, Jörg Bendix (last update: 2011-11-09)

» Prediction map of Pyraloidea species richness created by: Christine Wallis (last update: 2017-09-03)

» Leaf spectroscopy Setaria created by: Brenner Silva (last update: 2012-10-14)

» Leaf spectroscopy bracken created by: Brenner Silva (last update: 2012-10-04)

» Prediction map of litterfall productivity created by: Christine Wallis (last update: 2017-09-03)

» Prediction map of ant species richness created by: Christine Wallis (last update: 2017-09-03)

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Land use/land cover map of South Ecuador 1987

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Dataset ID:	1038
Last updated:	2011-11-07
Dataset creators:	Hanna Meyer Boris Thies Jörg Bendix
Contact:	Boris Thies Jörg Bendix Hanna Meyer
Temporal coverage:	1987-01-01 00:00:00 - 1997-12-31 00:00:00
Geographic coverage:	Loja-Zamora
Abstract:	The map shows land use/land cover (LUC) of the Lo... Abstract: The map shows land use/land cover (LUC) of the Loja-Zamora region in 1987. It consists of 6 LUC classes: Forest, Subparamo, Paramo, Pasture, Urban and Water. The classification is mainly based on a Landsat TM image from 1987/03/26. However, since it features high cloudiness, a composite of 8 further images around the year 1987 was used for filling the gaps.
Additional info:	The map is available in UTM 17S (WGS 84) projecti... Additional info: The map is available in UTM 17S (WGS 84) projection. The basis for the classification was the Landsat Scene LT50100631987085XXX02 (accessed in New Earth explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/) from 1987/03/26. The following TM scenes were used for filling the clouded areas of 1987: -1985/03/20 (LT50100631985079AAA04) -1986/12/04 (LT50100631986338XXX03) -1986/11/02 (LT50100631986306XXX09) -1989/12/28 (LT50100631989362XXX02) -1990/03/02 (LT50100631990061XXX02) -1998/07/14 (LT50100631998195XXX01) -1998/08/15 (LT50100631998227XXX01) -1998/12/21 (LT50100631998355XXX01) The procedure steps 1-5 were accomplished for each of the 9 Landsat images.
Keywords:	\| land use \| Loja \| land cover \| landsat \| remote sensing \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	classification1987
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

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Land use/land cover map of South Ecuador 2001

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Dataset ID:	1039
Last updated:	2011-11-09
Dataset creators:	Hanna Meyer Boris Thies Jörg Bendix
Contact:	Boris Thies Jörg Bendix Hanna Meyer
Temporal coverage:	2001-11-03 00:00:00 - 2001-11-03 00:00:00
Geographic coverage:	Loja-Zamora
Abstract:	The map shows land use/land cover (LUC) of the Lo... Abstract: The map shows land use/land cover (LUC) of the Loja-Zamora region in 2001. It consists of 6 LUC classes: Forest, Subparamo, Paramo, Pasture, Urban and Water. The classification is based on a Landsat ETM+ image from 2011/11/03.
Additional info:	The classification is based on the Landsat ETM+ i... Additional info: The classification is based on the Landsat ETM+ image LE70100632001307EDC00 from 2011/11/03 (accessed in New Earth explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/). The same image was already classified by Göttlicher (2009). The difference to the classification of Göttlicher is that the scene was created for land change modelling (Meyer et al. 2011b). Therefore it was very important that especially forest and non forest could be distinguished perfectly and that the classification is comparable to a second classification of 1987 (Meyer et al. 2011). The classification of 2001 by Göttlicher was classified using expert knowledge. It was not possible to reconstruct detailed classes for the corresponding 1987 scene. Therefore this new classification of 2001 was necessary for a comparison to 1987. The classification of Göttlicher (2009) is recommended if information of current and detailed LUC is needed. For analysis with focus on the contrast of grassland/forest distribution or for change detection matters we recommend using this new classification. citation: Göttlicher D. (2009): Landcover classification Ecuador (10 classes). Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=704) from DFG-FOR816dw Meyer H. , Thies B. , and Bendix J. (2011): Land use/land cover map of South Ecuador 1987 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1038) from DFG-FOR816dw. Meyer H. , Thies B. , and Bendix J. (2011b): Predicted land use/land cover maps of South Ecuador 2010-2100 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1040) from DFG-FOR816dw.
Keywords:	\| land use \| Loja \| land cover \| landsat \| remote sensing \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	classification2001
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

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Prediction map of Pyraloidea species richness

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Dataset ID:	1654
Last updated:	2017-09-03
Dataset creators:	Christine Wallis
Contact:	Christine Wallis
Temporal coverage:	1999-01-01 00:00:00 - 2000-12-31 00:00:00
Geographic coverage:	San francisco basin
Abstract:	The prediction map identifies the estimated richn... Abstract: The prediction map identifies the estimated richness of Pyraloidea species in the mountain rainforest in the San Francisco Valley. The corresponding regression model explained 72% in variation of species richness. Further information about the model and sampled field data are published in Wallis et al. (2017): Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa. doi: 10.1016/j.ecolind.2017.01.022
Additional info:	--- Additional info:
Keywords:	\| model output \| moths \| Pyraloidea \| remote sensing \| species richness \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

Entity name:	Prediction map of estimated Pyraloidea species richness
Entity type:	spatialRaster (701 x 693)
Attributes:	Species richness (specrich) [Count]

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Leaf spectroscopy Setaria

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Dataset ID:	1227
Last updated:	2012-10-14
Dataset creators:	Brenner Silva
Contact:	Brenner Silva Dietrich Göttlicher
Temporal coverage:	2008-03-20 15:15:00 - 2008-03-20 16:32:00
Geographic coverage:	ECSF casa
Abstract:	Spectral properties at leaf scale (Reflectance an... Abstract: Spectral properties at leaf scale (Reflectance and transmittance) taken with a handheld spectrometer (Handyspec 14, Tec 5, AG. Germany). Leaves were placed over a tarp within a 1m2 frame and leaf area index measured manually.
Additional info:	For measurement and description and citation plea... Additional info: For measurement and description and citation please refer to Goettlicher et al. 2011: http://dx.doi.org/10.1016/j.ecolmodel.2010.09.021 Data also cited in Bendix et al. 2010: http://dx.doi.org/10.1007/s00484-009-0279-3
Keywords:	\| remote sensing \| Setaria \| Setaria sphacelata \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

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Entity name:	spectrum_leaves_setaria
Entity type:	dataTable
Attributes:	wavelength (wavelength) [Nanometer] reflectance (reflectance) [Ratio] transmittance (transmittance) [Ratio] absorbance (absorbance) [Ratio] Plant functional type (PFT_ID) (Unitless) observation (observation) (Unitless) Date and Time (datetime) (Unitless) ID of the sample (SampleID) (Unitless) repetition (repetition) (Unitless) leaf area index (LAI) [Square meter per square meter] zenith angle (zenith_angle) [Degree]

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Leaf spectroscopy bracken

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Dataset ID:	1216
Last updated:	2012-10-04
Dataset creators:	Brenner Silva
Contact:	Brenner Silva Dietrich Göttlicher
Temporal coverage:	2008-03-19 15:06:00 - 2008-03-20 16:37:00
Geographic coverage:	ECSF casa
Abstract:	Spectral properties at leaf scale (Reflectance an... Abstract: Spectral properties at leaf scale (Reflectance and transmittance) taken with a handheld spectrometer (Handyspec 14, Tec 5, AG. Germany). Leaves were placed over a tarp within a 1m2 frame and leaf area index measured manually.
Additional info:	For measurement and description and citation plea... Additional info: For measurement and description and citation please refer to Göttlicher et al. 2011: http://dx.doi.org/10.1016/j.ecolmodel.2010.09.021 Data also cited in Bendix et al. 2010: http://dx.doi.org/10.1007/s00484-009-0279-3
Keywords:	\| bracken \| leaf \| remote sensing \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

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Entity name:	Leaf spectroscopy of bracken
Entity info:	Bracken spectral properties at leaf level
Entity type:	dataTable
Attributes:	wavelength (wavelength) [Nanometer] reflectance (reflectance) [Ratio] transmittance (transmittance) [Ratio] absorbance (absorbance) [Ratio] Plant functional type (PFT_ID) (Unitless) observation (observation) (Unitless) Date and Time (datetime) (Unitless) ID of the sample (SampleID) (Unitless) repetition (repetition) (Unitless) leaf area index (LAI) [Square meter per square meter] zenith angle (zenith_angle) [Degree]

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Prediction map of litterfall productivity

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Dataset ID:	1656
Last updated:	2017-09-03
Dataset creators:	Christine Wallis
Contact:	Christine Wallis
Temporal coverage:	2016-11-03 00:00:00 - 2016-11-03 00:00:00
Geographic coverage:	South Ecuador
Abstract:	We modeled forest productivity parameters by remo... Abstract: We modeled forest productivity parameters by remote sensing metrics derived from a Landsat-8 image and four Aster elevation images in the mountain rainforest of Southern Ecuador. The validated model for annual litterfall accounted for 68 % in variation of productivity. The partial least square regression model has been predicted across the study area. Non-forest areas have been masked out (using the land cover classification of Göttlicher et al. (2009). Attention this is work in progress. For further information please contact.
Additional info:	--- Additional info:
Keywords:	\| model output \| litterfall \| remote sensing \| Partial least-square regression \| forest productivity \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

Entity name:	AnnualLitterProductionEstMap
Entity type:	spatialRaster (1389 x 843)
Attributes:	Litterfall measured as dry matter weight (Litterfall) [Kilogram per hectare]

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Prediction map of ant species richness

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Dataset ID:	1655
Last updated:	2017-09-03
Dataset creators:	Christine Wallis
Contact:	Christine Wallis
Temporal coverage:	2014-03-01 00:00:00 - 2014-12-20 00:00:00
Geographic coverage:	San francisco basin
Abstract:	The prediction map identifies the estimated richn... Abstract: The prediction map identifies the estimated richness of ant species in the mountain rainforest in the San Francisco Valley. The corresponding regression model explained 78% in variation of species richness. Further information about the model and sampled field data are published in Wallis et al. (2017): Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa. doi: 10.1016/j.ecolind.2017.01.022
Additional info:	--- Additional info:
Keywords:	\| remote sensing \| species richness estimate \| Partial least-square regression \| ants \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

Entity name:	Prediction map of estimated ant species richness
Entity type:	spatialRaster (701 x 693)
Attributes:	Species richness (specrich) [Count]

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Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)

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Environmental changes in biodiversity hotspot ecosystems of South Ecuador: RESPonse and feedback effECTs (FOR2730)

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Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)