{"vid":"113115","uid":"0","title":"SRTMN - Management priority on a scale of 1:9 where 1 is highest priority (i.e. high river temperature and high climate sensitivity) and 9 is lowest (hidden when zoomed in past 1:5,000)","log":"Updated by FeedsNodeProcessor","status":"1","comment":"0","promote":"0","sticky":"0","ds_switch":"","nid":"16578","type":"nmpilayer","language":"und","created":"1545310672","changed":"1677776473","tnid":"0","translate":"0","revision_timestamp":"1677776473","revision_uid":"1","body":{"und":[{"value":"
This layer has been developed to combine the outputs from \u201csummer_max_tw_2003\u201d and \u201csummer_climate_change_sensitivity\u201d SRTMN layers into a single layer that can be used to prioritise management where the relative importance of maximum temperature and temperature change are considered to be equal.
\r\n\r\nThis was achieved by (1) dividing the predictions of \u2018summer_max_tw_2003\u2019 and \u2018summer_climate_change_sensitivity\u2019 into 5 equal categories between the minimum and maximum observed values (2) assigning these categories a value ranging from 1 (the hottest / most sensitive rivers) to 5 (the coolest / least sensitive rivers) (3) sum the rankings (-1) to produce an overall priority ranking (1:9) where rivers ranked as 1 are the highest priority for management (i.e. high river temperature and high climate sensitivity) and 9 the lowest.
\r\n\r\n\r\n","summary":"","format":"filtered_html","safe_value":"
This layer has been developed to combine the outputs from \u201csummer_max_tw_2003\u201d and \u201csummer_climate_change_sensitivity\u201d SRTMN layers into a single layer that can be used to prioritise management where the relative importance of maximum temperature and temperature change are considered to be equal.
\nThis was achieved by (1) dividing the predictions of \u2018summer_max_tw_2003\u2019 and \u2018summer_climate_change_sensitivity\u2019 into 5 equal categories between the minimum and maximum observed values (2) assigning these categories a value ranging from 1\u00a0 (the hottest / most sensitive rivers) to 5 (the coolest / least sensitive rivers) (3) sum the rankings (-1) to produce an overall priority ranking (1:9) where rivers ranked as 1 are the highest priority for management (i.e. high river temperature and high climate sensitivity) and 9 the lowest.
\n\u00a0
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\r\n\r\nThe following copyright and acknowledgement should be placed on all copies of information or images derived from the licensed CEH river network data: \u2018Based on digital spatial data licensed from the Centre for Ecology & Hydrology, \u00a9 NERC (CEH)' (preceded if appropriate by 'Some features of this map are'). And: 'Contains Ordnance Survey data \u00a9 Crown copyright and database right [year]'
\r\n\r\nThe following citation must be included in the reference list of any reports or publications in which the licensed CEH river network data, or derived data, have been used. \u2018Moore RV, Morris DG and Flavin RW, 1994. Sub-set of UK digital 1:50,000 scale river centre-line network. NERC, Institute of Hydrology, Wallingford.\u2019
\r\n","format":"filtered_html","safe_value":"Where the predictions are used, reference must be made to the original publication: Jackson, F. L., Fryer, R. J., Hannah, D. M., Millar, C.P., and Malcolm, I. A. (2018) A spatio-temporal statistical model of maximum daily river temperatures to inform the management of Scotland's Atlantic salmon rivers under climate change. Science of The Total Environment., 612, 1543-1558.
\nThe following copyright and acknowledgement should be placed on all copies of information or images derived from the licensed CEH river network data: \u2018Based on digital spatial data licensed from the Centre for Ecology & Hydrology, \u00a9 NERC (CEH)' (preceded if appropriate by 'Some features of this map are'). And: 'Contains Ordnance Survey data \u00a9 Crown copyright and database right [year]'
\nThe following citation must be included in the reference list of any reports or publications in which the licensed CEH river network data, or derived data, have been used. \u2018Moore RV, Morris DG and Flavin RW, 1994. Sub-set of UK digital 1:50,000 scale river centre-line network. NERC, Institute of Hydrology, Wallingford.\u2019
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