TY  - JOUR
A1  - Schleuning, Matthias
A1  - Farwig, Nina
A1  - Peters, Marcell K.
A1  - Bergsdorf, Thomas
A1  - Bleher, Bärbel
A1  - Brandl, Roland
A1  - Dalitz, Helmut
A1  - Fischer, Georg
A1  - Freund, Wolfram
A1  - Gikungu, Mary W.
A1  - Hagen, Melanie
A1  - Garcia, Francisco Hita
A1  - Kagezi, Godfrey H.
A1  - Kaib, Manfred
A1  - Kraemer, Manfred
A1  - Lung, Tobias
A1  - Naumann, Clas M.
A1  - Schaab, Gertrud
A1  - Templin, Mathias
A1  - Uster, Dana
A1  - Wägele, J. Wolfgang
A1  - Böhning-Gaese, Katrin
T1  - Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest
JF  - PLoS ONE
N2  - Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.
KW  - Ant-following birds
KW  - Land-use change
KW  - Habitat fragmentation
KW  - Rain-forest
KW  - Functional diversity
KW  - Plantation forests
KW  - Amazonian forest
KW  - Prunus-africana
KW  - Seed dispersal
KW  - Logged forests
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-140093
VL  - 6
IS  - 11
ER  - 
TY  - JOUR
A1  - Hudson, Lawrence N.
A1  - Newbold, Tim
A1  - Contu, Sara
A1  - Hill, Samantha L. L.
A1  - Lysenko, Igor
A1  - De Palma, Adriana
A1  - Phillips, Helen R. P.
A1  - Senior, Rebecca A.
A1  - Bennett, Dominic J.
A1  - Booth, Hollie
A1  - Choimes, Argyrios
A1  - Correia, David L. P.
A1  - Day, Julie
A1  - Echeverria-Londono, Susy
A1  - Garon, Morgan
A1  - Harrison, Michelle L. K.
A1  - Ingram, Daniel J.
A1  - Jung, Martin
A1  - Kemp, Victoria
A1  - Kirkpatrick, Lucinda
A1  - Martin, Callum D.
A1  - Pan, Yuan
A1  - White, Hannah J.
A1  - Aben, Job
A1  - Abrahamczyk, Stefan
A1  - Adum, Gilbert B.
A1  - Aguilar-Barquero, Virginia
A1  - Aizen, Marcelo
A1  - Ancrenaz, Marc
A1  - Arbelaez-Cortes, Enrique
A1  - Armbrecht, Inge
A1  - Azhar, Badrul
A1  - Azpiroz, Adrian B.
A1  - Baeten, Lander
A1  - Báldi, András
A1  - Banks, John E.
A1  - Barlow, Jos
A1  - Batáry, Péter
A1  - Bates, Adam J.
A1  - Bayne, Erin M.
A1  - Beja, Pedro
A1  - Berg, Ake
A1  - Berry, Nicholas J.
A1  - Bicknell, Jake E.
A1  - Bihn, Jochen H.
A1  - Böhning-Gaese, Katrin
A1  - Boekhout, Teun
A1  - Boutin, Celine
A1  - Bouyer, Jeremy
A1  - Brearley, Francis Q.
A1  - Brito, Isabel
A1  - Brunet, Jörg
A1  - Buczkowski, Grzegorz
A1  - Buscardo, Erika
A1  - Cabra-Garcia, Jimmy
A1  - Calvino-Cancela, Maria
A1  - Cameron, Sydney A.
A1  - Cancello, Eliana M.
A1  - Carrijo, Tiago F.
A1  - Carvalho, Anelena L.
A1  - Castro, Helena
A1  - Castro-Luna, Alejandro A.
A1  - Cerda, Rolando
A1  - Cerezo, Alexis
A1  - Chauvat, Matthieu
A1  - Clarke, Frank M.
A1  - Cleary, Daniel F. R.
A1  - Connop, Stuart P.
A1  - D'Aniello, Biagio
A1  - da Silva, Pedro Giovani
A1  - Darvill, Ben
A1  - Dauber, Jens
A1  - Dejean, Alain
A1  - Diekötter, Tim
A1  - Dominguez-Haydar, Yamileth
A1  - Dormann, Carsten F.
A1  - Dumont, Bertrand
A1  - Dures, Simon G.
A1  - Dynesius, Mats
A1  - Edenius, Lars
A1  - Elek, Zoltán
A1  - Entling, Martin H.
A1  - Farwig, Nina
A1  - Fayle, Tom M.
A1  - Felicioli, Antonio
A1  - Felton, Annika M.
A1  - Ficetola, Gentile F.
A1  - Filgueiras, Bruno K. C.
A1  - Fonte, Steve J.
A1  - Fraser, Lauchlan H.
A1  - Fukuda, Daisuke
A1  - Furlani, Dario
A1  - Ganzhorn, Jörg U.
A1  - Garden, Jenni G.
A1  - Gheler-Costa, Carla
A1  - Giordani, Paolo
A1  - Giordano, Simonetta
A1  - Gottschalk, Marco S.
A1  - Goulson, Dave
A1  - Gove, Aaron D.
A1  - Grogan, James
A1  - Hanley, Mick E.
A1  - Hanson, Thor
A1  - Hashim, Nor R.
A1  - Hawes, Joseph E.
A1  - Hébert, Christian
A1  - Helden, Alvin J.
A1  - Henden, John-André
A1  - Hernández, Lionel
A1  - Herzog, Felix
A1  - Higuera-Diaz, Diego
A1  - Hilje, Branko
A1  - Horgan, Finbarr G.
A1  - Horváth, Roland
A1  - Hylander, Kristoffer
A1  - Horváth, Roland
A1  - Isaacs-Cubides, Paola
A1  - Ishitani, Mashiro
A1  - Jacobs, Carmen T.
A1  - Jaramillo, Victor J.
A1  - Jauker, Birgit
A1  - Jonsell, Matts
A1  - Jung, Thomas S.
A1  - Kapoor, Vena
A1  - Kati, Vassiliki
A1  - Katovai, Eric
A1  - Kessler, Michael
A1  - Knop, Eva
A1  - Kolb, Annette
A1  - Körösi, Àdám
A1  - Lachat, Thibault
A1  - Lantschner, Victoria
A1  - Le Féon, Violette
A1  - LeBuhn, Gretchen
A1  - Légaré, Jean-Philippe
A1  - Letcher, Susan G.
A1  - Littlewood, Nick A.
A1  - López-Quintero, Carlos A.
A1  - Louhaichi, Mounir
A1  - Lövei, Gabor L.
A1  - Lucas-Borja, Manuel Esteban
A1  - Luja, Victor H.
A1  - Maeto, Kaoru
A1  - Magura, Tibor
A1  - Mallari, Neil Aldrin
A1  - Marin-Spiotta, Erika
A1  - Marhall, E. J. P.
A1  - Martínez, Eliana
A1  - Mayfield, Margaret M.
A1  - Mikusinski, Gregorz
A1  - Milder, Jeffery C.
A1  - Miller, James R.
A1  - Morales, Carolina L.
A1  - Muchane, Mary N.
A1  - Muchane, Muchai
A1  - Naidoo, Robin
A1  - Nakamura, Akihiro
A1  - Naoe, Shoji
A1  - Nates-Parra, Guiomar
A1  - Navarerete Gutierrez, Dario A.
A1  - Neuschulz, Eike L.
A1  - Noreika, Norbertas
A1  - Norfolk, Olivia
A1  - Noriega, Jorge Ari
A1  - Nöske, Nicole M.
A1  - O'Dea, Niall
A1  - Oduro, William
A1  - Ofori-Boateng, Caleb
A1  - Oke, Chris O.
A1  - Osgathorpe, Lynne M.
A1  - Paritsis, Juan
A1  - Parrah, Alejandro
A1  - Pelegrin, Nicolás
A1  - Peres, Carlos A.
A1  - Persson, Anna S.
A1  - Petanidou, Theodora
A1  - Phalan, Ben
A1  - Philips, T. Keith
A1  - Poveda, Katja
A1  - Power, Eileen F.
A1  - Presley, Steven J.
A1  - Proença, Vânia
A1  - Quaranta, Marino
A1  - Quintero, Carolina
A1  - Redpath-Downing, Nicola A.
A1  - Reid, J. Leighton
A1  - Reis, Yana T.
A1  - Ribeiro, Danilo B.
A1  - Richardson, Barbara A.
A1  - Richardson, Michael J.
A1  - Robles, Carolina A.
A1  - Römbke, Jörg
A1  - Romero-Duque, Luz Piedad
A1  - Rosselli, Loreta
A1  - Rossiter, Stephen J.
A1  - Roulston, T'ai H.
A1  - Rousseau, Laurent
A1  - Sadler, Jonathan P.
A1  - Sáfián, Szbolcs
A1  - Saldaña-Vásquez, Romeo A.
A1  - Samnegård, Ulrika
A1  - Schüepp, Christof
A1  - Schweiger, Oliver
A1  - Sedlock, Jodi L.
A1  - Shahabuddin, Ghazala
A1  - Sheil, Douglas
A1  - Silva, Fernando A. B.
A1  - Slade, Eleanor
A1  - Smith-Pardo, Allan H.
A1  - Sodhi, Navjot S.
A1  - Somarriba, Eduardo J.
A1  - Sosa, Ramón A.
A1  - Stout, Jane C.
A1  - Struebig, Matthew J.
A1  - Sung, Yik-Hei
A1  - Threlfall, Caragh G.
A1  - Tonietto, Rebecca
A1  - Tóthmérész, Béla
A1  - Tscharntke, Teja
A1  - Turner, Edgar C.
A1  - Tylianakis, Jason M.
A1  - Vanbergen, Adam J.
A1  - Vassilev, Kiril
A1  - Verboven, Hans A. F.
A1  - Vergara, Carlos H.
A1  - Vergara, Pablo M.
A1  - Verhulst, Jort
A1  - Walker, Tony R.
A1  - Wang, Yanping
A1  - Watling, James I.
A1  - Wells, Konstans
A1  - Williams, Christopher D.
A1  - Willig, Michael R.
A1  - Woinarski, John C. Z.
A1  - Wolf, Jan H. D.
A1  - Woodcock, Ben A.
A1  - Yu, Douglas W.
A1  - Zailsev, Andreys
A1  - Collen, Ben
A1  - Ewers, Rob M.
A1  - Mace, Georgina M.
A1  - Purves, Drew W.
A1  - Scharlemann, Jörn P. W.
A1  - Pervis, Andy
T1  - The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts
JF  - Ecology and Evolution
N2  - Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
KW  - urban-rural gradient
KW  - instensively managed farmland
KW  - Mexican coffee plantations
KW  - Bombus Spp. Hymenoptera
KW  - bumblebee nest density
KW  - data sharing
KW  - land use
KW  - habitat destruction
KW  - global change
KW  - land-use change
KW  - plant community composition
KW  - Northeastern Costa Rica
KW  - dung beetle coleoptera
KW  - bird species richness
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114425
VL  - 4
IS  - 24
ER  - 
TY  - JOUR
A1  - Peters, Marcell K.
A1  - Hemp, Andreas
A1  - Appelhans, Tim
A1  - Behler, Christina
A1  - Classen, Alice
A1  - Detsch, Florian
A1  - Ensslin, Andreas
A1  - Ferger, Stefan W.
A1  - Frederiksen, Sara B.
A1  - Gebert, Frederike
A1  - Haas, Michael
A1  - Helbig-Bonitz, Maria
A1  - Hemp, Claudia
A1  - Kindeketa, William J.
A1  - Mwangomo, Ephraim
A1  - Ngereza, Christine
A1  - Otte, Insa
A1  - Röder, Juliane
A1  - Rutten, Gemma
A1  - Costa, David Schellenberger
A1  - Tardanico, Joseph
A1  - Zancolli, Giulia
A1  - Deckert, Jürgen
A1  - Eardley, Connal D.
A1  - Peters, Ralph S.
A1  - Rödel, Mark-Oliver
A1  - Schleuning, Matthias
A1  - Ssymank, Axel
A1  - Kakengi, Victor
A1  - Zhang, Jie
A1  - Böhning-Gaese, Katrin
A1  - Brandl, Roland
A1  - Kalko, Elisabeth K.V.
A1  - Kleyer, Michael
A1  - Nauss, Thomas
A1  - Tschapka, Marco
A1  - Fischer, Markus
A1  - Steffan-Dewenter, Ingolf
T1  - Predictors of elevational biodiversity gradients change from single taxa to the multi-taxa community level
JF  - Nature Communications
N2  - The factors determining gradients of biodiversity are a fundamental yet unresolved topic in ecology. While diversity gradients have been analysed for numerous single taxa, progress towards general explanatory models has been hampered by limitations in the phylogenetic coverage of past studies. By parallel sampling of 25 major plant and animal taxa along a 3.7 km elevational gradient on Mt. Kilimanjaro, we quantify cross-taxon consensus in diversity gradients and evaluate predictors of diversity from single taxa to a multi-taxa community level. While single taxa show complex distribution patterns and respond to different environmental factors, scaling up diversity to the community level leads to an unambiguous support for temperature as the main predictor of species richness in both plants and animals. Our findings illuminate the influence of taxonomic coverage for models of diversity gradients and point to the importance of temperature for diversification and species coexistence in plant and animal communities.
KW  - community ecology
KW  - macroecology
KW  - tropical ecology
KW  - biodiversity
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-169374
VL  - 7
ER  - 
TY  - JOUR
A1  - Bowler, Diana E.
A1  - Bjorkman, Anne D.
A1  - Dornelas, Maria
A1  - Myers‐Smith, Isla H.
A1  - Navarro, Laetitia M.
A1  - Niamir, Aidin
A1  - Supp, Sarah R.
A1  - Waldock, Conor
A1  - Winter, Marten
A1  - Vellend, Mark
A1  - Blowes, Shane A.
A1  - Böhning‐Gaese, Katrin
A1  - Bruelheide, Helge
A1  - Elahi, Robin
A1  - Antão, Laura H.
A1  - Hines, Jes
A1  - Isbell, Forest
A1  - Jones, Holly P.
A1  - Magurran, Anne E.
A1  - Cabral, Juliano Sarmento
A1  - Bates, Amanda E.
T1  - Mapping human pressures on biodiversity across the planet uncovers anthropogenic threat complexes
JF  - People and Nature
N2  - Climate change and other anthropogenic drivers of biodiversity change are unequally distributed across the world. Overlap in the distributions of different drivers have important implications for biodiversity change attribution and the potential for interactive effects. However, the spatial relationships among different drivers and whether they differ between the terrestrial and marine realm has yet to be examined.

We compiled global gridded datasets on climate change, land‐use, resource exploitation, pollution, alien species potential and human population density. We used multivariate statistics to examine the spatial relationships among the drivers and to characterize the typical combinations of drivers experienced by different regions of the world.

We found stronger positive correlations among drivers in the terrestrial than in the marine realm, leading to areas with high intensities of multiple drivers on land. Climate change tended to be negatively correlated with other drivers in the terrestrial realm (e.g. in the tundra and boreal forest with high climate change but low human use and pollution), whereas the opposite was true in the marine realm (e.g. in the Indo‐Pacific with high climate change and high fishing).

We show that different regions of the world can be defined by Anthropogenic Threat Complexes (ATCs), distinguished by different sets of drivers with varying intensities. We identify 11 ATCs that can be used to test hypotheses about patterns of biodiversity and ecosystem change, especially about the joint effects of multiple drivers.

Our global analysis highlights the broad conservation priorities needed to mitigate the impacts of anthropogenic change, with different priorities emerging on land and in the ocean, and in different parts of the world.
KW  - Anthropocene
KW  - biodiversity threats
KW  - direct drivers
KW  - global change
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-213634
VL  - 2
IS  - 2
SP  - 380
EP  - 394
ER  - 
TY  - JOUR
A1  - Ziegler, Alice
A1  - Meyer, Hanna
A1  - Otte, Insa
A1  - Peters, Marcell K.
A1  - Appelhans, Tim
A1  - Behler, Christina
A1  - Böhning-Gaese, Katrin
A1  - Classen, Alice
A1  - Detsch, Florian
A1  - Deckert, Jürgen
A1  - Eardley, Connal D.
A1  - Ferger, Stefan W.
A1  - Fischer, Markus
A1  - Gebert, Friederike
A1  - Haas, Michael
A1  - Helbig-Bonitz, Maria
A1  - Hemp, Andreas
A1  - Hemp, Claudia
A1  - Kakengi, Victor
A1  - Mayr, Antonia V.
A1  - Ngereza, Christine
A1  - Reudenbach, Christoph
A1  - Röder, Juliane
A1  - Rutten, Gemma
A1  - Schellenberger Costa, David
A1  - Schleuning, Matthias
A1  - Ssymank, Axel
A1  - Steffan-Dewenter, Ingolf
A1  - Tardanico, Joseph
A1  - Tschapka, Marco
A1  - Vollstädt, Maximilian G. R.
A1  - Wöllauer, Stephan
A1  - Zhang, Jie
A1  - Brandl, Roland
A1  - Nauss, Thomas
T1  - Potential of airborne LiDAR derived vegetation structure for the prediction of animal species richness at Mount Kilimanjaro
JF  - Remote Sensing
N2  - The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
KW  - biodiversity
KW  - species richness
KW  - LiDAR
KW  - elevation
KW  - partial least square regression
KW  - arthropods
KW  - birds
KW  - bats
KW  - predictive modeling
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262251
SN  - 2072-4292
VL  - 14
IS  - 3
ER  -