Remote sensing variables improve species distribution models for alpine plant species
Species distribution models (SDMs) are cost-effective, transparent and flexible planning tools to support various areas in nature conservation. Variables taken from remote sensing (RS) are broadly applicable to biodiversity studies. In our study, we combined RS-variables (normalized differenced vege...
Saved in:
| Published in | Basic and applied ecology Vol. 54; pp. 1 - 13 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier GmbH
01.08.2021
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Species distribution models (SDMs) are cost-effective, transparent and flexible planning tools to support various areas in nature conservation. Variables taken from remote sensing (RS) are broadly applicable to biodiversity studies. In our study, we combined RS-variables (normalized differenced vegetation index and land surface temperatures), with topographic and geological variables to produce detailed SDMs in the context of a seed collection campaign of the Alpine Seed Conservation and Research Project. To identify effective predictor variable combinations we compiled three different variable sets and compared the predictive model performance.
The full model, that combines all types of variables, slightly outperforms (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.7) models that use topo-climatic variables (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.68) or NDVI (average values for TSS: 0.85, AUC: 0.96, Kappa: 0.54) alone. We also produced ensemble models that performed slightly better compared to the different model algorithms used in our approach. We identified the temperature of the coldest month, mean NDVI and bedrock as important variables that determine the distribution of alpine plant species.
Our full models show high accordance with actual species distribution ranges and are highly relevant for efforts to identify special areas for either in-situ or ex-situ conservation. |
|---|---|
| AbstractList | Species distribution models (SDMs) are cost-effective, transparent and flexible planning tools to support various areas in nature conservation. Variables taken from remote sensing (RS) are broadly applicable to biodiversity studies. In our study, we combined RS-variables (normalized differenced vegetation index and land surface temperatures), with topographic and geological variables to produce detailed SDMs in the context of a seed collection campaign of the Alpine Seed Conservation and Research Project. To identify effective predictor variable combinations we compiled three different variable sets and compared the predictive model performance.
The full model, that combines all types of variables, slightly outperforms (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.7) models that use topo-climatic variables (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.68) or NDVI (average values for TSS: 0.85, AUC: 0.96, Kappa: 0.54) alone. We also produced ensemble models that performed slightly better compared to the different model algorithms used in our approach. We identified the temperature of the coldest month, mean NDVI and bedrock as important variables that determine the distribution of alpine plant species.
Our full models show high accordance with actual species distribution ranges and are highly relevant for efforts to identify special areas for either in-situ or ex-situ conservation. Species distribution models (SDMs) are cost-effective, transparent and flexible planning tools to support various areas in nature conservation. Variables taken from remote sensing (RS) are broadly applicable to biodiversity studies. In our study, we combined RS-variables (normalized differenced vegetation index and land surface temperatures), with topographic and geological variables to produce detailed SDMs in the context of a seed collection campaign of the Alpine Seed Conservation and Research Project. To identify effective predictor variable combinations we compiled three different variable sets and compared the predictive model performance.The full model, that combines all types of variables, slightly outperforms (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.7) models that use topo-climatic variables (average values for TSS: 0.91, AUC: 0.98, Kappa: 0.68) or NDVI (average values for TSS: 0.85, AUC: 0.96, Kappa: 0.54) alone. We also produced ensemble models that performed slightly better compared to the different model algorithms used in our approach. We identified the temperature of the coldest month, mean NDVI and bedrock as important variables that determine the distribution of alpine plant species.Our full models show high accordance with actual species distribution ranges and are highly relevant for efforts to identify special areas for either in-situ or ex-situ conservation. |
| Author | Schwager, Patrick Berg, Christian |
| Author_xml | – sequence: 1 givenname: Patrick surname: Schwager fullname: Schwager, Patrick email: p.schwager@gmx.at organization: Engineering office – Patrick Schwager, Herdergasse 3, 8010 Graz, Austria – sequence: 2 givenname: Christian surname: Berg fullname: Berg, Christian email: christian.berg@uni-graz.at organization: Institute of Biology, Department of Plant Sciences, University of Graz, Holteigasse 6, 8010 Graz, Austria |
| BookMark | eNp9kE1rwyAYgD10sLbbH9gpx12S-ZovA7uMsi8oDMZ6FjVvhiWJmdrC_v0M3S47FAQRn0denxVZjHZEQm6AZkChuttnSkrMGGWQ0SKjlC3IEoq8SaFu4JKsvN9TCgXN-ZLs3nGwAROPozfjZ3KUzkjVo0_MMDl7jDcTahPPrfHBGXUIxo7JYFvsfdJZl8h-MiMmUy_H8AdfkYtO9h6vf_c12T09fmxe0u3b8-vmYZvqvK5D2jRdnbecYYUlAIKSHEpVgNSl4ipnrSo5bSDvkFOOVDEe8RJ0FdmiZVW-Jrend-OoXwf0QQzGa-zjLGgPXrCSFSyupo4oP6HaWe8ddkKbIOfPBCdNL4CKuZ7Yi7memOsJWohYL6rsnzo5M0j3fV66P0mxEx4NOuFjmVFjaxzqIFprzuk_JImNrQ |
| CitedBy_id | crossref_primary_10_1002_rse2_366 crossref_primary_10_1007_s13762_024_06020_w crossref_primary_10_1109_MGRS_2021_3097280 crossref_primary_10_3390_rs16152855 crossref_primary_10_1002_eap_2624 crossref_primary_10_1007_s10531_023_02648_1 crossref_primary_10_1111_jbi_14847 crossref_primary_10_1016_j_sciaf_2023_e01947 crossref_primary_10_3897_jor_33_118937 crossref_primary_10_1016_j_ecoinf_2022_101872 crossref_primary_10_1007_s11258_024_01485_8 crossref_primary_10_1016_j_ecolmodel_2025_111056 crossref_primary_10_1016_j_ecoinf_2023_102433 crossref_primary_10_3390_rs14122898 crossref_primary_10_3897_jor_34_130377 crossref_primary_10_3390_land13121995 crossref_primary_10_1371_journal_pone_0289209 crossref_primary_10_1016_j_jenvman_2022_116428 crossref_primary_10_1016_j_biocon_2024_110963 crossref_primary_10_3390_rs16224271 |
| Cites_doi | 10.1111/j.1365-2664.2008.01516.x 10.1016/S0304-3800(03)00237-0 10.1038/sdata.2017.122 10.1007/s10113-016-1090-4 10.1016/j.tree.2005.05.011 10.1111/jvs.12444 10.1007/BF00031679 10.1111/2041-210X.13018 10.1007/s10530-016-1276-1 10.1098/rsbl.2014.0347 10.1007/s11258-020-01061-w 10.1007/s11629-016-4313-8 10.7809/b-e.00125 10.1111/2041-210X.13033 10.1023/A:1009841519580 10.1016/j.ecolmodel.2012.06.019 10.1016/j.ecolind.2017.10.011 10.1111/j.1365-2664.2006.01214.x 10.1111/ele.12189 10.1126/science.aai9214 10.1111/j.1472-4642.2010.00641.x 10.1098/rstb.2013.0190 10.1109/JSTARS.2010.2075916 10.3389/fevo.2019.00009 10.1111/j.1472-4642.2009.00567.x 10.1016/j.ecolmodel.2009.08.013 10.1111/j.0906-7590.2006.04700.x 10.1038/nclimate1514 10.2307/3647447 10.1890/11-0114.1 10.1111/1365-2664.12261 10.1016/j.biocon.2011.04.024 10.1023/A:1010632015572 10.1002/joc.1276 10.1111/j.1365-2486.2009.02122.x 10.1038/sdata.2018.40 10.3354/cr00936 10.1111/jbi.12199 10.1016/j.envsoft.2010.03.014 10.1111/j.1365-2699.2010.02407.x 10.1016/j.rsase.2015.08.001 10.1371/journal.pone.0185591 10.1016/j.rse.2019.111626 10.1002/rse2.7 10.1007/s10531-013-0509-1 10.1007/s10113-019-01554-z 10.1080/01431160117096 10.3390/rs6053822 10.1002/joc.1322 10.1111/j.1365-2486.2005.001018.x 10.3390/rs4072057 10.1111/2041-210X.13057 10.1017/S0376892997000088 10.1177/001316446002000104 10.1111/geb.12426 10.1046/j.0305-0270.2003.00991.x 10.1016/j.biocon.2016.04.023 10.1111/j.1365-2664.2007.01348.x 10.1016/S0304-3800(00)00354-9 |
| ContentType | Journal Article |
| Copyright | 2021 The Authors |
| Copyright_xml | – notice: 2021 The Authors |
| DBID | 6I. AAFTH AAYXX CITATION 7S9 L.6 |
| DOI | 10.1016/j.baae.2021.04.002 |
| DatabaseName | ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology Ecology Environmental Sciences |
| EndPage | 13 |
| ExternalDocumentID | 10_1016_j_baae_2021_04_002 S1439179121000694 |
| GroupedDBID | --K --M .~1 0R~ 1B1 1RT 1~. 1~5 23N 4.4 457 4G. 53G 5GY 5VS 6I. 7-5 71M 8P~ AABNK AABVA AACTN AAEDT AAEDW AAFTH AAIAV AAIKJ AAKOC AALCJ AALRI AAOAW AAQFI AAQXK AATLK AAXUO ABFYP ABGRD ABLST ABMAC ABXDB ABYKQ ACDAQ ACGFS ACRLP ADBBV ADEZE ADMUD ADQTV AEBSH AEKER AENEX AEQOU AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AIEXJ AIKHN AITUG AJBFU AJOXV AKIFW ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG AVWKF AXJTR AZFZN BKOJK BLECG BLXMC CAG CBWCG COF CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FGOYB FIRID FNPLU FYGXN G-Q GBLVA GROUPED_DOAJ HZ~ IHE J1W KCYFY KOM M41 MO0 N9A O-L O9- OAUVE OK1 OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SDF SDG SDP SES SEW SSA SSJ SSZ T5K Y6R ~G- ~KM AAHBH AATTM AAXKI AAYWO AAYXX ABWVN ACRPL ACVFH ADCNI ADNMO ADVLN AEIPS AEUPX AFJKZ AFPUW AGCQF AGQPQ AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU BNPGV CITATION SSH 7S9 L.6 |
| ID | FETCH-LOGICAL-c377t-99f73d82e6e511e1ba815b41ac5b8b32db580913fe808e0b2873d51c61e14d263 |
| IEDL.DBID | .~1 |
| ISSN | 1439-1791 |
| IngestDate | Fri Jul 11 04:44:55 EDT 2025 Tue Jul 01 01:53:57 EDT 2025 Thu Apr 24 23:00:45 EDT 2025 Fri Feb 23 02:44:47 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Ex-situ conservation Land surface and Surface Temperature Species Distribution Models Remote Sensing Styrian Alps NDVI Alpine species |
| Language | English |
| License | This is an open access article under the CC BY license. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c377t-99f73d82e6e511e1ba815b41ac5b8b32db580913fe808e0b2873d51c61e14d263 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://www.sciencedirect.com/science/article/pii/S1439179121000694 |
| PQID | 2524224297 |
| PQPubID | 24069 |
| PageCount | 13 |
| ParticipantIDs | proquest_miscellaneous_2524224297 crossref_citationtrail_10_1016_j_baae_2021_04_002 crossref_primary_10_1016_j_baae_2021_04_002 elsevier_sciencedirect_doi_10_1016_j_baae_2021_04_002 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | August 2021 2021-08-00 20210801 |
| PublicationDateYYYYMMDD | 2021-08-01 |
| PublicationDate_xml | – month: 08 year: 2021 text: August 2021 |
| PublicationDecade | 2020 |
| PublicationTitle | Basic and applied ecology |
| PublicationYear | 2021 |
| Publisher | Elsevier GmbH |
| Publisher_xml | – name: Elsevier GmbH |
| References | Thuiller, Georges, Engler, Breiner (bib0069) 2020 Pasetto, Arenas-Castro, Bustamante, Casagrandi, Chrysoulakis, Cord, Ziv (bib0048) 2018; 9 Bolliger, Schmatz, Pazúr, Ostapowicz, Psomas (bib0005) 2017; 17 Evans, J.S. (.2019). spatialEco. R package version 1.2-0. Available from Bradley, Olsson, Wang, Dickson, Pelech, Sesnie, Zachmann (bib0006) 2012; 244 Feilhauer, He, Rocchini (bib0018) 2012; 4 Nagendra (bib0043) 2001; 22 Hofmann, Everaars, Schweiger, Frenzel, Bannehr, Cord (bib0032) 2017; 12 Körner (bib0035) 2003 Gasser, Gusterhuber, Krische, Puhr, Scheucher, Wagner, Stüwe (bib0022) 2009; 139 Schwager, Berg (bib0064) 2019; 19 Zimmermann, Edwards, Moisen, Frescino, Blackard (bib0079) 2007; 44 Deblauwe, Droissart, Bose, Sonké, Blach-Overgaard, Svenning, Couvreur (bib0013) 2016; 25 Scherrer, Körner (bib0063) 2011; 38 Alleaume, Dusseux, Thierion, Commagnac, Laventure, Lang, Luque (bib0001) 2018; 9 Tan, Morisette, Wolfe, Gao, Ederer, Nightingale, Pedelty (bib0066) 2011; 4 Cohen (bib0009) 1960; 20 Cord, Meentemeyer, Leitão, Václavík (bib0010) 2013; 40 Pettorelli, Vik, Mysterud, Gaillard, Tucker, Stenseth (bib0053) 2005; 20 Goedecke, Bergmeier (bib0023) 2018; 16 Wen, Saintilan, Yang, Hunter, Mawer (bib0076) 2015; 1 Daly (bib0012) 2006; 26 Leitão, Santos, Morgan (bib0036) 2019; 7 Thuiller, Richardson, Pyssek, Midgley, Hughes, Rouget (bib0070) 2005; 11 Scherrer, Körner (bib0062) 2010; 16 Karger, Conrad, Böhner, Kawohl, Kreft, Soria-Auza, Kessler (bib0034) 2017; 4 Pettorelli, Safi, Turner (bib0052) 2014; 369 Guisan, Zimmermann (bib0027) 2000; 135 Nagy, Grabherr, Körner, Thompson (bib0044) 2003 Franklin (bib0021) 2010; 16 Hijmans, Cameron, Parra, Jones, Jarvis (bib0031) 2005; 25 Maurer (bib0039) 1998 Randin, Ashcroft, Bolliger, Cavender-Bares, Coops, Dullinger, Payne (bib0060) 2020; 239 . Václavík, Meentemeyer (bib0073) 2009; 220 Pettorelli, Ryan, Mueller, Bunnefeld, Jędrzejewska, Lima, Kausrud (bib0051) 2011; 46 Brenning, A., Bangs, D., & Becker, M. (2018). Cord, Rödder (bib0011) 2011; 21 Mod, Scherrer, Luoto, Guisan, Scheiner (bib0041) 2016; 27 Hijmans, A.R.J., Phillips, S., Leathwick, J., Elith, J., & Hijmans, M.R.J. (2017). dismo: Species Distribution Modeling. R package version 1.1-4. Available from Skowronek, Ewald, Isermann, Van De Kerchove, Lenoir, Aerts, Feilhauer (bib0065) 2017; 19 Guisan, Weiss, Weiss (bib0026) 1999; 143 Veit (bib0075) 2002 Carvalho, Brito, Crespo, Watts, Possingham (bib0008) 2011; 144 Pottier, Malenovský, Psomas, Homolová, Schaepman, Choler, Zimmermann (bib0056) 2014; 10 Franklin (bib0020) 2010 Pettorelli, Laurance, O'Brien, Wegmann, Nagendra, Turner (bib0050) 2014; 51 Didan, K., Munoz, A.B., .Solano, R., & Huete, A. (2015). MODIS Vegetation Index User ’s Guide (Collection 6), 2015 (May), 31. Parviainen, Luoto, Heikkinen (bib0046) 2010; 15 Williams, Seo, Thorne, Nelson, Erwin, O’Brien, Schwartz (bib0077) 2009; 15 Willner, Berg, Heiselmayer (bib0078) 2012; 4 Metz, Rocchini, Neteler (bib0040) 2014; 6 Allouche, Tsoar, Kadmon (bib0002) 2006; 43 Tulloch, Sutcliffe, Naujokaitis-Lewis, Tingley, Brotons, Ferraz, Rhodes (bib0072) 2016; 199 Dittrich, Roilo, Sonnenschein, Cerrato, Ewald, Viterbi, Cord (bib0015) 2020; 12 Jelaska, Antonić, Nikolić, Hršak, Plazibat, Križan (bib0033) 2003; 170 Amatulli, Domisch, Tuanmu, Parmentier, Ranipeta, Malczyk, Jetz (bib0003) 2018; 5 Thuiller, Araújo, Lavorel (bib0068) 2004; 31 Raduła, Szymura, Szymura (bib0059) 2018; 85 Guisan, Tingley, Baumgartner, Naujokaitis-Lewis, Sutcliffe, Tulloch, Buckley (bib0025) 2013; 16 Fielding, Bell (bib0019) 1997; 24 Rouse, Hass, Schell, Deering (bib0061) 1974; 3 Luque, Pettorelli, Vihervaara, Wegmann (bib0037) 2018; 9 Vaze, Teng, Spencer (bib0074) 2010; 25 Dullinger, Gattringer, Thuiller, Moser, Zimmermann, Guisan, Hülber (bib0016) 2012; 2 He, Bradley, Cord, Rocchini, Tuanmu, Schmidtlein, Pettorelli (bib0028) 2015; 1 Guisan, Thuiller, Zimmermann (bib0024) 2017 Hernandez, Graham, Master, Albert (bib0029) 2006; 29 (bib0058) 2019 Parviainen, Zimmermann, Heikkinen, Luoto (bib0047) 2013; 22 Theurillat, Guisan (bib0067) 2001; 50 (bib0057) 2020 Tribsch, Schönswetter (bib0071) 2003; 52 Pilger, Podesser, Prettenthaler (bib0054) 2010 Pinto-Ledezma, Cavender-Bares (bib0055) 2020; 231 Parolo, Rossi, Ferrarini (bib0045) 2008; 45 Margreiter, Pagitz, Berg, Schwager, Erschbamer (bib0038) 2020; 221 Müller, Berg, Détraz-Méroz, Erschbamer, Fort, Lambelet-Haueter, Breman (bib0042) 2017; 14 Pecl, Araújo, Bell, Blanchard, Bonebrake, Chen, Williams (bib0049) 2017; 355 Austin, Smith (bib0004) 1989; 83 Guisan (10.1016/j.baae.2021.04.002_bib0025) 2013; 16 Guisan (10.1016/j.baae.2021.04.002_bib0027) 2000; 135 Hijmans (10.1016/j.baae.2021.04.002_bib0031) 2005; 25 Pettorelli (10.1016/j.baae.2021.04.002_bib0052) 2014; 369 Pinto-Ledezma (10.1016/j.baae.2021.04.002_bib0055) 2020; 231 Guisan (10.1016/j.baae.2021.04.002_bib0024) 2017 Pecl (10.1016/j.baae.2021.04.002_bib0049) 2017; 355 Cord (10.1016/j.baae.2021.04.002_bib0011) 2011; 21 (10.1016/j.baae.2021.04.002_bib0058) 2019 Parolo (10.1016/j.baae.2021.04.002_bib0045) 2008; 45 Tulloch (10.1016/j.baae.2021.04.002_bib0072) 2016; 199 Jelaska (10.1016/j.baae.2021.04.002_bib0033) 2003; 170 Mod (10.1016/j.baae.2021.04.002_bib0041) 2016; 27 Hofmann (10.1016/j.baae.2021.04.002_bib0032) 2017; 12 Margreiter (10.1016/j.baae.2021.04.002_bib0038) 2020; 221 Nagy (10.1016/j.baae.2021.04.002_bib0044) 2003 Austin (10.1016/j.baae.2021.04.002_bib0004) 1989; 83 Daly (10.1016/j.baae.2021.04.002_bib0012) 2006; 26 Fielding (10.1016/j.baae.2021.04.002_bib0019) 1997; 24 Hernandez (10.1016/j.baae.2021.04.002_bib0029) 2006; 29 Pettorelli (10.1016/j.baae.2021.04.002_bib0050) 2014; 51 Raduła (10.1016/j.baae.2021.04.002_bib0059) 2018; 85 Franklin (10.1016/j.baae.2021.04.002_bib0021) 2010; 16 Zimmermann (10.1016/j.baae.2021.04.002_bib0079) 2007; 44 Guisan (10.1016/j.baae.2021.04.002_bib0026) 1999; 143 Dittrich (10.1016/j.baae.2021.04.002_bib0015) 2020; 12 Thuiller (10.1016/j.baae.2021.04.002_bib0068) 2004; 31 Feilhauer (10.1016/j.baae.2021.04.002_bib0018) 2012; 4 10.1016/j.baae.2021.04.002_bib0017 Randin (10.1016/j.baae.2021.04.002_bib0060) 2020; 239 Pottier (10.1016/j.baae.2021.04.002_bib0056) 2014; 10 Nagendra (10.1016/j.baae.2021.04.002_bib0043) 2001; 22 Scherrer (10.1016/j.baae.2021.04.002_bib0062) 2010; 16 Tribsch (10.1016/j.baae.2021.04.002_bib0071) 2003; 52 Thuiller (10.1016/j.baae.2021.04.002_bib0070) 2005; 11 Willner (10.1016/j.baae.2021.04.002_bib0078) 2012; 4 Amatulli (10.1016/j.baae.2021.04.002_bib0003) 2018; 5 Allouche (10.1016/j.baae.2021.04.002_bib0002) 2006; 43 Gasser (10.1016/j.baae.2021.04.002_bib0022) 2009; 139 Williams (10.1016/j.baae.2021.04.002_bib0077) 2009; 15 Parviainen (10.1016/j.baae.2021.04.002_bib0047) 2013; 22 Luque (10.1016/j.baae.2021.04.002_bib0037) 2018; 9 Skowronek (10.1016/j.baae.2021.04.002_bib0065) 2017; 19 Tan (10.1016/j.baae.2021.04.002_bib0066) 2011; 4 Goedecke (10.1016/j.baae.2021.04.002_bib0023) 2018; 16 Leitão (10.1016/j.baae.2021.04.002_bib0036) 2019; 7 Parviainen (10.1016/j.baae.2021.04.002_bib0046) 2010; 15 Theurillat (10.1016/j.baae.2021.04.002_bib0067) 2001; 50 Vaze (10.1016/j.baae.2021.04.002_bib0074) 2010; 25 Körner (10.1016/j.baae.2021.04.002_bib0035) 2003 Veit (10.1016/j.baae.2021.04.002_bib0075) 2002 10.1016/j.baae.2021.04.002_bib0014 Cohen (10.1016/j.baae.2021.04.002_bib0009) 1960; 20 Wen (10.1016/j.baae.2021.04.002_bib0076) 2015; 1 Cord (10.1016/j.baae.2021.04.002_bib0010) 2013; 40 10.1016/j.baae.2021.04.002_bib0007 He (10.1016/j.baae.2021.04.002_bib0028) 2015; 1 (10.1016/j.baae.2021.04.002_bib0057) 2020 Thuiller (10.1016/j.baae.2021.04.002_bib0069) 2020 Alleaume (10.1016/j.baae.2021.04.002_bib0001) 2018; 9 Schwager (10.1016/j.baae.2021.04.002_bib0064) 2019; 19 Franklin (10.1016/j.baae.2021.04.002_bib0020) 2010 Pettorelli (10.1016/j.baae.2021.04.002_bib0053) 2005; 20 Pasetto (10.1016/j.baae.2021.04.002_bib0048) 2018; 9 Scherrer (10.1016/j.baae.2021.04.002_bib0063) 2011; 38 Karger (10.1016/j.baae.2021.04.002_bib0034) 2017; 4 Pettorelli (10.1016/j.baae.2021.04.002_bib0051) 2011; 46 Maurer (10.1016/j.baae.2021.04.002_bib0039) 1998 Müller (10.1016/j.baae.2021.04.002_bib0042) 2017; 14 Rouse (10.1016/j.baae.2021.04.002_bib0061) 1974; 3 Václavík (10.1016/j.baae.2021.04.002_bib0073) 2009; 220 Bradley (10.1016/j.baae.2021.04.002_bib0006) 2012; 244 Carvalho (10.1016/j.baae.2021.04.002_bib0008) 2011; 144 Pilger (10.1016/j.baae.2021.04.002_bib0054) 2010 Bolliger (10.1016/j.baae.2021.04.002_bib0005) 2017; 17 10.1016/j.baae.2021.04.002_bib0030 Dullinger (10.1016/j.baae.2021.04.002_bib0016) 2012; 2 Deblauwe (10.1016/j.baae.2021.04.002_bib0013) 2016; 25 Metz (10.1016/j.baae.2021.04.002_bib0040) 2014; 6 |
| References_xml | – volume: 83 start-page: 35 year: 1989 end-page: 47 ident: bib0004 article-title: A new model for the continuum concept publication-title: Vegetatio – volume: 7 start-page: 1 year: 2019 end-page: 7 ident: bib0036 article-title: Improving models of species ecological niches : a remote sensing overview publication-title: Frontiers in Ecology and Evolution – year: 2010 ident: bib0054 article-title: Klimaatlas Steiermark – volume: 25 start-page: 443 year: 2016 end-page: 454 ident: bib0013 article-title: Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics publication-title: Global Ecology and Biogeography – volume: 16 start-page: 1424 year: 2013 end-page: 1435 ident: bib0025 article-title: Predicting species distributions for conservation decisions publication-title: Ecology Letters – volume: 51 start-page: 839 year: 2014 end-page: 848 ident: bib0050 article-title: Satellite remote sensing for applied ecologists: opportunities and challenges publication-title: Journal of Applied Ecology – reference: Evans, J.S. (.2019). spatialEco. R package version 1.2-0. Available from: – volume: 19 start-page: 2411 year: 2019 end-page: 2421 ident: bib0064 article-title: Global warming threatens conservation status of alpine EU habitat types in the European Eastern Alps publication-title: Regional Environmental Change – volume: 221 start-page: 1045 year: 2020 end-page: 1067 ident: bib0038 article-title: Pros and cons of using a standard protocol to test germination of Alpine species publication-title: Plant Ecology – volume: 15 start-page: 301 year: 2010 end-page: 318 ident: bib0046 article-title: NDVI-based productivity and heterogeneity as indicators of plant-species richness in boreal landscapes publication-title: Boreal Environment Research – volume: 24 start-page: 38 year: 1997 end-page: 49 ident: bib0019 article-title: A review of methods for the assessment of prediction errors in conservation presence/absence models publication-title: Environmental Conservation – volume: 9 start-page: 1784 year: 2018 end-page: 1786 ident: bib0037 article-title: Improving biodiversity monitoring using satellite remote sensing to provide solutions towards the 2020 conservation targets publication-title: Methods in Ecology and Evolution – volume: 355 start-page: 1 year: 2017 end-page: 9 ident: bib0049 article-title: Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being publication-title: Science (New York, N.Y.) – volume: 29 start-page: 773 year: 2006 end-page: 785 ident: bib0029 article-title: The effect of sample size and species characteristics on performance of different species distribution modeling methods publication-title: Ecography – reference: Brenning, A., Bangs, D., & Becker, M. (2018). – volume: 14 start-page: 806 year: 2017 end-page: 810 ident: bib0042 article-title: The Alpine Seed Conservation and Research Network - a new initiative to conserve valuable plant species in the European Alps publication-title: Journal of Mountain Science – volume: 220 start-page: 3248 year: 2009 end-page: 3258 ident: bib0073 article-title: Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions? publication-title: Ecological Modelling – volume: 85 start-page: 172 year: 2018 end-page: 179 ident: bib0059 article-title: Topographic wetness index explains soil moisture better than bioindication with Ellenberg's indicator values publication-title: Ecological Indicators – volume: 244 start-page: 57 year: 2012 end-page: 64 ident: bib0006 article-title: Species detection vs. habitat suitability: are we biasing habitat suitability models with remotely sensed data? publication-title: Ecological Modelling – volume: 27 start-page: 1308 year: 2016 end-page: 1322 ident: bib0041 article-title: What we use is not what we know: Environmental predictors in plant distribution models publication-title: Journal of Vegetation Science – volume: 1 start-page: 85 year: 2015 end-page: 97 ident: bib0076 article-title: MODIS NDVI based metrics improve habitat suitability modelling in fragmented patchy floodplains publication-title: Remote Sensing Applications: Society and Environment – volume: 9 start-page: 1810 year: 2018 end-page: 1821 ident: bib0048 article-title: Integration of satellite remote sensing data in ecosystem modelling at local scales: Practices and trends publication-title: Methods in Ecology and Evolution – year: 2003 ident: bib0044 article-title: Alpine Biodiversity in Europe – volume: 170 start-page: 333 year: 2003 end-page: 343 ident: bib0033 article-title: Estimating plant species occurrence in MTB/64 quadrants as a function of DEM-based variables - A case study for Medvednica Nature Park, Croatia publication-title: Ecological Modelling – volume: 20 start-page: 503 year: 2005 end-page: 510 ident: bib0053 article-title: Using the satellite-derived NDVI to assess ecological responses to environmental change publication-title: Trends in Ecology and Evolution – year: 2020 ident: bib0069 article-title: BIOMOD2: Ensemble Platform for Species Distribution Modeling – volume: 40 start-page: 2226 year: 2013 end-page: 2227 ident: bib0010 article-title: Modelling species distributions with remote sensing data: Bridging disciplinary perspectives publication-title: Journal of Biogeography – start-page: 239 year: 1998 ident: bib0039 article-title: Flora der steiermark. Band II/1. Verwachsenkronblättrige Blütenpflanzen (Sympetale) – volume: 16 start-page: 321 year: 2010 end-page: 330 ident: bib0021 article-title: Moving beyond static species distribution models in support of conservation biogeography publication-title: Diversity and Distributions – volume: 231 start-page: 199 year: 2020 end-page: 223 ident: bib0055 article-title: Using Remote Sensing for Modeling and Monitoring Species Distributions. In: Wang,R., & Gamon,J. A. (2020). remote sensing of terrestrial plant biodiversity publication-title: Remote Sensing of Environment – volume: 2 start-page: 619 year: 2012 end-page: 622 ident: bib0016 article-title: Extinction debt of high-mountain plants under twenty-first-century climate change publication-title: Nature Climate Change – volume: 15 start-page: 565 year: 2009 end-page: 576 ident: bib0077 article-title: Using species distribution models to predict new occurrences for rare plants publication-title: Diversity and Distributions – volume: 135 start-page: 147 year: 2000 end-page: 186 ident: bib0027 article-title: Predictive habitat distribution models in ecology publication-title: Ecological Modelling – year: 2002 ident: bib0075 article-title: Die alpen – reference: Didan, K., Munoz, A.B., .Solano, R., & Huete, A. (2015). MODIS Vegetation Index User ’s Guide (Collection 6), 2015 (May), 31. – year: 2017 ident: bib0024 article-title: Habitat Suitability and Distribution Models: With Applications in R. Ecology – volume: 22 start-page: 1731 year: 2013 end-page: 1754 ident: bib0047 article-title: Using unclassified continuous remote sensing data to improve distribution models of red-listed plant species publication-title: Biodiversity and Conservation – volume: 19 start-page: 239 year: 2017 end-page: 254 ident: bib0065 article-title: Mapping an invasive bryophyte species using hyperspectral remote sensing data publication-title: Biological Invasions – volume: 369 start-page: 1 year: 2014 end-page: 5 ident: bib0052 article-title: Satellite remote sensing, biodiversity research and conservation of the future publication-title: Philosophical Transactions of the Royal Society B – year: 2019 ident: bib0058 article-title: R: A Language and Environment for Statistical Computing – volume: 52 start-page: 477 year: 2003 end-page: 497 ident: bib0071 article-title: Patterns of endemism and comparative phylogeography confirm palaeoenvironmental evidence for Pleistocene refugia in the Eastern Alps publication-title: Taxon – volume: 4 start-page: 1 year: 2017 end-page: 20 ident: bib0034 article-title: Data Descriptor : Climatologies at high resolution for the earth’ s land surface areas publication-title: Scientific Data – volume: 143 start-page: 107 year: 1999 end-page: 122 ident: bib0026 article-title: GLM versus CCA spatial modeling of plant species distribution publication-title: Plant Ecology – volume: 199 start-page: 157 year: 2016 end-page: 171 ident: bib0072 article-title: Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes publication-title: Biological Conservation – volume: 20 start-page: 37 year: 1960 end-page: 46 ident: bib0009 article-title: A coefficient of agreement for nominal scales publication-title: Educational and Psychological Measurement – volume: 144 start-page: 2020 year: 2011 end-page: 2030 ident: bib0008 article-title: Conservation planning under climate change: toward accounting for uncertainty in predicted species distributions to increase confidence in conservation investments in space and time publication-title: Biological Conservation – volume: 4 start-page: 361 year: 2011 end-page: 371 ident: bib0066 article-title: An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing – volume: 43 start-page: 1223 year: 2006 end-page: 1232 ident: bib0002 article-title: Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS) publication-title: Journal of Applied Ecology – volume: 1 start-page: 4 year: 2015 end-page: 18 ident: bib0028 article-title: Will remote sensing shape the next generation of species distribution models? publication-title: Remote Sensing in Ecology and Conservation – volume: 6 start-page: 3822 year: 2014 end-page: 3840 ident: bib0040 article-title: Surface temperatures at the continental scale: Tracking changes with remote sensing at unprecedented detail publication-title: Remote Sensing – volume: 16 start-page: 15 year: 2018 end-page: 26 ident: bib0023 article-title: Ecology and potential distribution of the Cretan endemic tree species Zelkova abelicea publication-title: Journal of Mediterranean Ecology – volume: 38 start-page: 406 year: 2011 end-page: 416 ident: bib0063 article-title: Topographically controlled thermal-habitat differentiation buffers alpine plant diversity against climate warming publication-title: Journal of Biogeography – volume: 31 start-page: 353 year: 2004 end-page: 361 ident: bib0068 article-title: Do we need land-cover data to model species distributions in Europe? publication-title: Journal of Biogeography – year: 2003 ident: bib0035 article-title: Alpine Plant Life. functional Plant Ecology of High Mountain Ecosystems – volume: 16 start-page: 2602 year: 2010 end-page: 2613 ident: bib0062 article-title: Infra-red thermometry of alpine landscapes challenges climatic warming projections publication-title: Global Change Biology – year: 2010 ident: bib0020 article-title: Mapping Species Distributions. Spatial Inference and Prediction – volume: 12 start-page: 1 year: 2020 end-page: 24 ident: bib0015 article-title: Modelling distributions of rove beetles in mountainous areas using remote sensing data publication-title: Remote Sensing – reference: . – volume: 17 start-page: 2265 year: 2017 end-page: 2277 ident: bib0005 article-title: Reconstructing forest-cover change in the Swiss Alps between 1880 and 2010 using ensemble modelling publication-title: Regional Environmental Change – volume: 3 start-page: 301 year: 1974 end-page: 317 ident: bib0061 article-title: Monitoring vegetation systems in the great plains with ERTS publication-title: Third Earth Resources Technology Satellite (ERTS) symposium – volume: 50 start-page: 77 year: 2001 end-page: 109 ident: bib0067 article-title: Potential impact of Climate Change on vegetation in the European Alps : A review publication-title: Climatic Change – volume: 12 start-page: 1 year: 2017 end-page: 17 ident: bib0032 article-title: Modelling patterns of pollinator species richness and diversity using satellite image texture publication-title: PloS one – volume: 44 start-page: 1057 year: 2007 end-page: 1067 ident: bib0079 article-title: Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah publication-title: Journal of Applied Ecology – reference: Hijmans, A.R.J., Phillips, S., Leathwick, J., Elith, J., & Hijmans, M.R.J. (2017). dismo: Species Distribution Modeling. R package version 1.1-4. Available from: – year: 2020 ident: bib0057 article-title: QGIS Geographic Information System – volume: 5 start-page: 1 year: 2018 end-page: 15 ident: bib0003 article-title: Data Descriptor: A suite of global, cross-scale topographic variables for environmental and biodiversity modeling publication-title: Scientific Data – volume: 4 start-page: 2057 year: 2012 end-page: 2075 ident: bib0018 article-title: Modeling species distribution using niche-based proxies derived from composite bioclimatic variables and MODIS NDVI publication-title: Remote Sensing – volume: 45 start-page: 1410 year: 2008 end-page: 1418 ident: bib0045 article-title: Toward improved species niche modelling: Arnica montana in the Alps as a case study publication-title: Journal of Applied Ecology – volume: 11 start-page: 2234 year: 2005 end-page: 2250 ident: bib0070 article-title: Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale publication-title: Global Change Biology – volume: 9 start-page: 1822 year: 2018 end-page: 1836 ident: bib0001 article-title: A generic remote sensing approach to derive operational essential biodiversity variables (EBVs) for conservation planning publication-title: Methods in Ecology and Evolution – volume: 22 start-page: 2377 year: 2001 end-page: 2400 ident: bib0043 article-title: Using remote sensing to assess biodiversity publication-title: International Journal of Remote Sensing – volume: 10 start-page: 1 year: 2014 end-page: 4 ident: bib0056 article-title: Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy publication-title: Biology Letters – volume: 239 start-page: 1 year: 2020 end-page: 18 ident: bib0060 article-title: Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models publication-title: Remote Sensing of Environment – volume: 26 start-page: 707 year: 2006 end-page: 721 ident: bib0012 article-title: Guidelines for assessing the suitability of spatial climate data sets publication-title: International Journal of Climatology – volume: 139 start-page: 5 year: 2009 end-page: 36 ident: bib0022 article-title: Geology of Styria: An overview publication-title: Mitteilungen Des Naturwissenschaftlichen Vereines Für Steiermark – volume: 25 start-page: 1965 year: 2005 end-page: 1978 ident: bib0031 article-title: Very high resolution interpolated climate surfaces for global land areas publication-title: International Journal of Climatology – volume: 4 start-page: 333 year: 2012 ident: bib0078 article-title: Austrian vegetation database publication-title: Biodiversity & Ecology – volume: 21 start-page: 3285 year: 2011 end-page: 3298 ident: bib0011 article-title: Inclusion of habitat availability in species distribution models through multi-temporal remote sensing data? towards multifunctional agricultural landscapes in Europe: Assessing and governing synergies between food production, biodiversity, and ecosystem publication-title: Ecological Applications – volume: 46 start-page: 15 year: 2011 end-page: 27 ident: bib0051 article-title: The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology publication-title: Climate Research – volume: 25 start-page: 1086 year: 2010 end-page: 1098 ident: bib0074 article-title: Impact of DEM accuracy and resolution on topographic indices publication-title: Environmental Modelling and Software – volume: 45 start-page: 1410 year: 2008 ident: 10.1016/j.baae.2021.04.002_bib0045 article-title: Toward improved species niche modelling: Arnica montana in the Alps as a case study publication-title: Journal of Applied Ecology doi: 10.1111/j.1365-2664.2008.01516.x – volume: 170 start-page: 333 year: 2003 ident: 10.1016/j.baae.2021.04.002_bib0033 article-title: Estimating plant species occurrence in MTB/64 quadrants as a function of DEM-based variables - A case study for Medvednica Nature Park, Croatia publication-title: Ecological Modelling doi: 10.1016/S0304-3800(03)00237-0 – volume: 4 start-page: 1 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0034 article-title: Data Descriptor : Climatologies at high resolution for the earth’ s land surface areas publication-title: Scientific Data doi: 10.1038/sdata.2017.122 – volume: 17 start-page: 2265 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0005 article-title: Reconstructing forest-cover change in the Swiss Alps between 1880 and 2010 using ensemble modelling publication-title: Regional Environmental Change doi: 10.1007/s10113-016-1090-4 – volume: 20 start-page: 503 year: 2005 ident: 10.1016/j.baae.2021.04.002_bib0053 article-title: Using the satellite-derived NDVI to assess ecological responses to environmental change publication-title: Trends in Ecology and Evolution doi: 10.1016/j.tree.2005.05.011 – volume: 27 start-page: 1308 year: 2016 ident: 10.1016/j.baae.2021.04.002_bib0041 article-title: What we use is not what we know: Environmental predictors in plant distribution models publication-title: Journal of Vegetation Science doi: 10.1111/jvs.12444 – volume: 83 start-page: 35 year: 1989 ident: 10.1016/j.baae.2021.04.002_bib0004 article-title: A new model for the continuum concept publication-title: Vegetatio doi: 10.1007/BF00031679 – volume: 9 start-page: 1810 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0048 article-title: Integration of satellite remote sensing data in ecosystem modelling at local scales: Practices and trends publication-title: Methods in Ecology and Evolution doi: 10.1111/2041-210X.13018 – volume: 19 start-page: 239 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0065 article-title: Mapping an invasive bryophyte species using hyperspectral remote sensing data publication-title: Biological Invasions doi: 10.1007/s10530-016-1276-1 – volume: 10 start-page: 1 year: 2014 ident: 10.1016/j.baae.2021.04.002_bib0056 article-title: Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy publication-title: Biology Letters doi: 10.1098/rsbl.2014.0347 – volume: 221 start-page: 1045 year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0038 article-title: Pros and cons of using a standard protocol to test germination of Alpine species publication-title: Plant Ecology doi: 10.1007/s11258-020-01061-w – volume: 14 start-page: 806 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0042 article-title: The Alpine Seed Conservation and Research Network - a new initiative to conserve valuable plant species in the European Alps publication-title: Journal of Mountain Science doi: 10.1007/s11629-016-4313-8 – volume: 15 start-page: 301 year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0046 article-title: NDVI-based productivity and heterogeneity as indicators of plant-species richness in boreal landscapes publication-title: Boreal Environment Research – year: 2019 ident: 10.1016/j.baae.2021.04.002_bib0058 – volume: 4 start-page: 333 year: 2012 ident: 10.1016/j.baae.2021.04.002_bib0078 article-title: Austrian vegetation database publication-title: Biodiversity & Ecology doi: 10.7809/b-e.00125 – volume: 9 start-page: 1822 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0001 article-title: A generic remote sensing approach to derive operational essential biodiversity variables (EBVs) for conservation planning publication-title: Methods in Ecology and Evolution doi: 10.1111/2041-210X.13033 – volume: 143 start-page: 107 year: 1999 ident: 10.1016/j.baae.2021.04.002_bib0026 article-title: GLM versus CCA spatial modeling of plant species distribution publication-title: Plant Ecology doi: 10.1023/A:1009841519580 – year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0057 – volume: 244 start-page: 57 year: 2012 ident: 10.1016/j.baae.2021.04.002_bib0006 article-title: Species detection vs. habitat suitability: are we biasing habitat suitability models with remotely sensed data? publication-title: Ecological Modelling doi: 10.1016/j.ecolmodel.2012.06.019 – volume: 85 start-page: 172 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0059 article-title: Topographic wetness index explains soil moisture better than bioindication with Ellenberg's indicator values publication-title: Ecological Indicators doi: 10.1016/j.ecolind.2017.10.011 – volume: 231 start-page: 199 year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0055 article-title: Using Remote Sensing for Modeling and Monitoring Species Distributions. In: Wang,R., & Gamon,J. A. (2020). remote sensing of terrestrial plant biodiversity publication-title: Remote Sensing of Environment – volume: 43 start-page: 1223 year: 2006 ident: 10.1016/j.baae.2021.04.002_bib0002 article-title: Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS) publication-title: Journal of Applied Ecology doi: 10.1111/j.1365-2664.2006.01214.x – volume: 16 start-page: 1424 year: 2013 ident: 10.1016/j.baae.2021.04.002_bib0025 article-title: Predicting species distributions for conservation decisions publication-title: Ecology Letters doi: 10.1111/ele.12189 – volume: 355 start-page: 1 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0049 article-title: Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being publication-title: Science (New York, N.Y.) doi: 10.1126/science.aai9214 – ident: 10.1016/j.baae.2021.04.002_bib0007 – year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0054 – volume: 16 start-page: 321 year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0021 article-title: Moving beyond static species distribution models in support of conservation biogeography publication-title: Diversity and Distributions doi: 10.1111/j.1472-4642.2010.00641.x – volume: 369 start-page: 1 year: 2014 ident: 10.1016/j.baae.2021.04.002_bib0052 article-title: Satellite remote sensing, biodiversity research and conservation of the future publication-title: Philosophical Transactions of the Royal Society B doi: 10.1098/rstb.2013.0190 – volume: 4 start-page: 361 year: 2011 ident: 10.1016/j.baae.2021.04.002_bib0066 article-title: An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing doi: 10.1109/JSTARS.2010.2075916 – volume: 12 start-page: 1 year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0015 article-title: Modelling distributions of rove beetles in mountainous areas using remote sensing data publication-title: Remote Sensing – volume: 7 start-page: 1 year: 2019 ident: 10.1016/j.baae.2021.04.002_bib0036 article-title: Improving models of species ecological niches : a remote sensing overview publication-title: Frontiers in Ecology and Evolution doi: 10.3389/fevo.2019.00009 – volume: 15 start-page: 565 year: 2009 ident: 10.1016/j.baae.2021.04.002_bib0077 article-title: Using species distribution models to predict new occurrences for rare plants publication-title: Diversity and Distributions doi: 10.1111/j.1472-4642.2009.00567.x – year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0069 – volume: 220 start-page: 3248 year: 2009 ident: 10.1016/j.baae.2021.04.002_bib0073 article-title: Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions? publication-title: Ecological Modelling doi: 10.1016/j.ecolmodel.2009.08.013 – volume: 29 start-page: 773 year: 2006 ident: 10.1016/j.baae.2021.04.002_bib0029 article-title: The effect of sample size and species characteristics on performance of different species distribution modeling methods publication-title: Ecography doi: 10.1111/j.0906-7590.2006.04700.x – volume: 2 start-page: 619 year: 2012 ident: 10.1016/j.baae.2021.04.002_bib0016 article-title: Extinction debt of high-mountain plants under twenty-first-century climate change publication-title: Nature Climate Change doi: 10.1038/nclimate1514 – ident: 10.1016/j.baae.2021.04.002_bib0014 – volume: 52 start-page: 477 year: 2003 ident: 10.1016/j.baae.2021.04.002_bib0071 article-title: Patterns of endemism and comparative phylogeography confirm palaeoenvironmental evidence for Pleistocene refugia in the Eastern Alps publication-title: Taxon doi: 10.2307/3647447 – volume: 21 start-page: 3285 year: 2011 ident: 10.1016/j.baae.2021.04.002_bib0011 article-title: Inclusion of habitat availability in species distribution models through multi-temporal remote sensing data? towards multifunctional agricultural landscapes in Europe: Assessing and governing synergies between food production, biodiversity, and ecosystem publication-title: Ecological Applications doi: 10.1890/11-0114.1 – year: 2003 ident: 10.1016/j.baae.2021.04.002_bib0035 – volume: 51 start-page: 839 year: 2014 ident: 10.1016/j.baae.2021.04.002_bib0050 article-title: Satellite remote sensing for applied ecologists: opportunities and challenges publication-title: Journal of Applied Ecology doi: 10.1111/1365-2664.12261 – volume: 139 start-page: 5 year: 2009 ident: 10.1016/j.baae.2021.04.002_bib0022 article-title: Geology of Styria: An overview publication-title: Mitteilungen Des Naturwissenschaftlichen Vereines Für Steiermark – year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0024 – volume: 144 start-page: 2020 year: 2011 ident: 10.1016/j.baae.2021.04.002_bib0008 article-title: Conservation planning under climate change: toward accounting for uncertainty in predicted species distributions to increase confidence in conservation investments in space and time publication-title: Biological Conservation doi: 10.1016/j.biocon.2011.04.024 – volume: 3 start-page: 301 year: 1974 ident: 10.1016/j.baae.2021.04.002_bib0061 article-title: Monitoring vegetation systems in the great plains with ERTS publication-title: Third Earth Resources Technology Satellite (ERTS) symposium – volume: 50 start-page: 77 year: 2001 ident: 10.1016/j.baae.2021.04.002_bib0067 article-title: Potential impact of Climate Change on vegetation in the European Alps : A review publication-title: Climatic Change doi: 10.1023/A:1010632015572 – volume: 25 start-page: 1965 year: 2005 ident: 10.1016/j.baae.2021.04.002_bib0031 article-title: Very high resolution interpolated climate surfaces for global land areas publication-title: International Journal of Climatology doi: 10.1002/joc.1276 – year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0020 – volume: 16 start-page: 2602 year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0062 article-title: Infra-red thermometry of alpine landscapes challenges climatic warming projections publication-title: Global Change Biology doi: 10.1111/j.1365-2486.2009.02122.x – volume: 5 start-page: 1 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0003 article-title: Data Descriptor: A suite of global, cross-scale topographic variables for environmental and biodiversity modeling publication-title: Scientific Data doi: 10.1038/sdata.2018.40 – year: 2002 ident: 10.1016/j.baae.2021.04.002_bib0075 – volume: 46 start-page: 15 year: 2011 ident: 10.1016/j.baae.2021.04.002_bib0051 article-title: The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology publication-title: Climate Research doi: 10.3354/cr00936 – volume: 40 start-page: 2226 year: 2013 ident: 10.1016/j.baae.2021.04.002_bib0010 article-title: Modelling species distributions with remote sensing data: Bridging disciplinary perspectives publication-title: Journal of Biogeography doi: 10.1111/jbi.12199 – start-page: 239 year: 1998 ident: 10.1016/j.baae.2021.04.002_bib0039 – volume: 25 start-page: 1086 year: 2010 ident: 10.1016/j.baae.2021.04.002_bib0074 article-title: Impact of DEM accuracy and resolution on topographic indices publication-title: Environmental Modelling and Software doi: 10.1016/j.envsoft.2010.03.014 – volume: 38 start-page: 406 year: 2011 ident: 10.1016/j.baae.2021.04.002_bib0063 article-title: Topographically controlled thermal-habitat differentiation buffers alpine plant diversity against climate warming publication-title: Journal of Biogeography doi: 10.1111/j.1365-2699.2010.02407.x – volume: 1 start-page: 85 year: 2015 ident: 10.1016/j.baae.2021.04.002_bib0076 article-title: MODIS NDVI based metrics improve habitat suitability modelling in fragmented patchy floodplains publication-title: Remote Sensing Applications: Society and Environment doi: 10.1016/j.rsase.2015.08.001 – ident: 10.1016/j.baae.2021.04.002_bib0017 – ident: 10.1016/j.baae.2021.04.002_bib0030 – volume: 12 start-page: 1 year: 2017 ident: 10.1016/j.baae.2021.04.002_bib0032 article-title: Modelling patterns of pollinator species richness and diversity using satellite image texture publication-title: PloS one doi: 10.1371/journal.pone.0185591 – volume: 239 start-page: 1 year: 2020 ident: 10.1016/j.baae.2021.04.002_bib0060 article-title: Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models publication-title: Remote Sensing of Environment doi: 10.1016/j.rse.2019.111626 – volume: 1 start-page: 4 year: 2015 ident: 10.1016/j.baae.2021.04.002_bib0028 article-title: Will remote sensing shape the next generation of species distribution models? publication-title: Remote Sensing in Ecology and Conservation doi: 10.1002/rse2.7 – year: 2003 ident: 10.1016/j.baae.2021.04.002_bib0044 – volume: 22 start-page: 1731 year: 2013 ident: 10.1016/j.baae.2021.04.002_bib0047 article-title: Using unclassified continuous remote sensing data to improve distribution models of red-listed plant species publication-title: Biodiversity and Conservation doi: 10.1007/s10531-013-0509-1 – volume: 19 start-page: 2411 year: 2019 ident: 10.1016/j.baae.2021.04.002_bib0064 article-title: Global warming threatens conservation status of alpine EU habitat types in the European Eastern Alps publication-title: Regional Environmental Change doi: 10.1007/s10113-019-01554-z – volume: 22 start-page: 2377 year: 2001 ident: 10.1016/j.baae.2021.04.002_bib0043 article-title: Using remote sensing to assess biodiversity publication-title: International Journal of Remote Sensing doi: 10.1080/01431160117096 – volume: 6 start-page: 3822 year: 2014 ident: 10.1016/j.baae.2021.04.002_bib0040 article-title: Surface temperatures at the continental scale: Tracking changes with remote sensing at unprecedented detail publication-title: Remote Sensing doi: 10.3390/rs6053822 – volume: 26 start-page: 707 year: 2006 ident: 10.1016/j.baae.2021.04.002_bib0012 article-title: Guidelines for assessing the suitability of spatial climate data sets publication-title: International Journal of Climatology doi: 10.1002/joc.1322 – volume: 16 start-page: 15 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0023 article-title: Ecology and potential distribution of the Cretan endemic tree species Zelkova abelicea publication-title: Journal of Mediterranean Ecology – volume: 11 start-page: 2234 year: 2005 ident: 10.1016/j.baae.2021.04.002_bib0070 article-title: Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale publication-title: Global Change Biology doi: 10.1111/j.1365-2486.2005.001018.x – volume: 4 start-page: 2057 year: 2012 ident: 10.1016/j.baae.2021.04.002_bib0018 article-title: Modeling species distribution using niche-based proxies derived from composite bioclimatic variables and MODIS NDVI publication-title: Remote Sensing doi: 10.3390/rs4072057 – volume: 9 start-page: 1784 year: 2018 ident: 10.1016/j.baae.2021.04.002_bib0037 article-title: Improving biodiversity monitoring using satellite remote sensing to provide solutions towards the 2020 conservation targets publication-title: Methods in Ecology and Evolution doi: 10.1111/2041-210X.13057 – volume: 24 start-page: 38 year: 1997 ident: 10.1016/j.baae.2021.04.002_bib0019 article-title: A review of methods for the assessment of prediction errors in conservation presence/absence models publication-title: Environmental Conservation doi: 10.1017/S0376892997000088 – volume: 20 start-page: 37 year: 1960 ident: 10.1016/j.baae.2021.04.002_bib0009 article-title: A coefficient of agreement for nominal scales publication-title: Educational and Psychological Measurement doi: 10.1177/001316446002000104 – volume: 25 start-page: 443 year: 2016 ident: 10.1016/j.baae.2021.04.002_bib0013 article-title: Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics publication-title: Global Ecology and Biogeography doi: 10.1111/geb.12426 – volume: 31 start-page: 353 year: 2004 ident: 10.1016/j.baae.2021.04.002_bib0068 article-title: Do we need land-cover data to model species distributions in Europe? publication-title: Journal of Biogeography doi: 10.1046/j.0305-0270.2003.00991.x – volume: 199 start-page: 157 year: 2016 ident: 10.1016/j.baae.2021.04.002_bib0072 article-title: Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes publication-title: Biological Conservation doi: 10.1016/j.biocon.2016.04.023 – volume: 44 start-page: 1057 year: 2007 ident: 10.1016/j.baae.2021.04.002_bib0079 article-title: Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah publication-title: Journal of Applied Ecology doi: 10.1111/j.1365-2664.2007.01348.x – volume: 135 start-page: 147 year: 2000 ident: 10.1016/j.baae.2021.04.002_bib0027 article-title: Predictive habitat distribution models in ecology publication-title: Ecological Modelling doi: 10.1016/S0304-3800(00)00354-9 |
| SSID | ssj0014038 |
| Score | 2.4140952 |
| Snippet | Species distribution models (SDMs) are cost-effective, transparent and flexible planning tools to support various areas in nature conservation. Variables taken... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1 |
| SubjectTerms | alpine plants Alpine species applied ecology bedrock biodiversity cost effectiveness Ex-situ conservation geographical distribution Land surface and Surface Temperature NDVI Remote Sensing research projects seed collecting Species Distribution Models Styrian Alps topography |
| Title | Remote sensing variables improve species distribution models for alpine plant species |
| URI | https://dx.doi.org/10.1016/j.baae.2021.04.002 https://www.proquest.com/docview/2524224297 |
| Volume | 54 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dS8MwEA9jIvgifg3nFxF8k7p-pWkfx9iYintQB3sLSZrKZHTDboIv_u3etelEkT0IfUjbSyh3yd0lvfsdIVdZ5qYGdlYOc3XkhIkMHAl2xNE6MTzwJXjoeKD_MIqG4_BuwiYN0qtzYTCs0ur-SqeX2to-6VhudhbTaefJw6RRniACFuLtIiZoGHKc5Tef6zAPhKMr0-GAuITitIkzVYyXkhKhMn2vhDu1Ryt_GKdfarq0PYM9smudRtqtvmufNEx-QLarMpIf0Opr22r1v_PWoINduMUhGT8akImhBcar5y_0HbbImDRV0Gl5qgBvsBA93KeIpGuLYNGyTk5BwbGlcrYAh5QuZiCKmviIjAf9597QsRUVHB1wvnSSJONBGvsmMuBoGU-BXJgKPamZilXgp4rFCBSamdiNjatgOxWkzNMR0IapHwUt0sznuTkmNOU6MjKMFIMBmMmUzwLXzeKEJWnGOW8Tr2al0BZuHKtezEQdV_YqkP0C2S_cUAD72-R63WdRgW1spGa1hMSPKSPAGmzsd1mLU8Bawh8kMjfzVSF8Bg4LXAk_-efYp2QH76oIwTPSXL6tzDl4LUt1UU7LC7LVvb0fjr4AmUDrdA |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8QwEB50RfQiPvFtBG9Stq807VFkZX3tQV3wFpI0lZWlu9hV8N8706aKIh6EHtJmEspMMpkkM98AnBSFn1vcWXncN4kXZyryFK4jnjGZFVGo0EKnA_3bQdIfxleP_HEOzttYGHKrdLq_0em1tnZfuo6b3elo1L0PKGhUZISARXi78TwsEDoV78DC2eV1f_B5mRD7dUJroq_ROF3sTOPmpZUitMwwqBFP3enKL-vTD01dLz8Xq7Di7EZ21vzaGszZch0Wm0yS71jqGVfa6n2FrmEDN3erDRjeWRSLZRW5rJdP7A13yRQ3VbFRfbCANZSLHt9zAtN1ebBYnSqnYmjbMjWeok3KpmOURku8CcOL3sN533NJFTwTCTHzsqwQUZ6GNrFoa9lAo2i4jgNluE51FOaap4QVWtjUT62vcUcV5TwwCdLGeZhEW9ApJ6XdBpYLk1gVJ5pjB9wWOuSR7xdpxrO8EELsQNCyUhqHOE6JL8aydS17lsR-SeyXfiyR_Ttw-tlm2uBt_EnNWwnJb6NG4oLwZ7vjVpwSpxPdkajSTl4rGXK0WfDJxO4_-z6Cpf7D7Y28uRxc78Ey1TQOg_vQmb282gM0Ymb60A3SD7A77iU |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Remote+sensing+variables+improve+species+distribution+models+for+alpine+plant+species&rft.jtitle=Basic+and+applied+ecology&rft.au=Schwager%2C+Patrick&rft.au=Berg%2C+Christian&rft.date=2021-08-01&rft.issn=1439-1791&rft.volume=54+p.1-13&rft.spage=1&rft.epage=13&rft_id=info:doi/10.1016%2Fj.baae.2021.04.002&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1439-1791&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1439-1791&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1439-1791&client=summon |