Results 41 to 50 of about 6,022,549 (302)

Random forest and spatial cross-validation performance in predicting species abundance distributions

Environmental Systems Research
Random forests (RF) have been widely used to predict spatial variables. Several studies have shown that spatial cross-validation (CV) methods consistently cause RF to yield larger prediction errors compared to standard CV methods. This study examined the
C. Mushagalusa, A. B. Fandohan, Romain Glèlè Kakaï   +2 more
semanticscholar   +1 more source

A global database of ant species abundances [PDF]

Ecology, 2017
AbstractWhat forces structure ecological assemblages? A key limitation to general insights about assemblage structure is the availability of data that are collected at a small spatial grain (local assemblages) and a large spatial extent (global coverage).
Gibb, Heloise, Dunn, Rob R, Sanders, Nathan J, Grossman, Blair F, Photakis, Manoli, Abril, Silvia, Agosti, Donat, Andersen, Alan N, Angulo, Elena, Armbrecht, Inge, Arnan, Xavier, Baccaro, Fabricio B, Bishop, Tom R, Boulay, Raphaël, Brühl, Carsten, CASTRACANI, Cristina, Cerda, Xim, Del Toro, Israel, Delsinne, Thibaut, Diaz, Mireia, Donoso, David A, Ellison, Aaron M, Enriquez, Martha L, Fayle, Tom M, Feener, Donald H, Fisher, Brian L, Fisher, Robert N, Fitzpatrick, Matthew C, Gómez, Crisanto, Gotelli, Nicholas J, Gove, Aaron, GRASSO, Donato Antonio, Groc, Sarah, Guenard, Benoit, Gunawardene, Nihara, Heterick, Brian, Hoffmann, Benjamin, Janda, Milan, Jenkins, Clinton, Kaspari, Michael, Klimes, Petr, Lach, Lori, Laeger, Thomas, Lattke, John, Leponce, Maurice, Lessard, Jean Philippe, Longino, John, Lucky, Andrea, Luke, Sarah H, Majer, Jonathan, Mcglynn, Terrence P, Menke, Sean, Mezger, Dirk, MORI, Alessandra, Moses, Jimmy, Munyai, Thinandavha Caswell, Pacheco, Renata, Paknia, Omid, Pearce Duvet, Jessica, Pfeiffer, Martin, Philpott, Stacy M, Resasco, Julian, Retana, Javier, Silva, Rogerio R, Sorger, Magdalena D, Souza, Jorge, Suarez, Andrew, Tista, Melanie, Vasconcelos, Heraldo L, Vonshak, Merav, Weiser, Michael D, Yates, Michelle, Parr, Catherine L.   +72 more
openaire   +6 more sources

A Comparison between Video and Still Imagery as a Methodology to Determine Southern Hairy-Nosed Wombat (Lasiorhinus latifrons) Burrow Occupancy Rates

Animals, 2018
Broad-scale abundance estimates of the southern hairy-nosed wombat population use a proxy measure based on counting the number of active burrows, which is multiplied by an index of ‘wombats/active burrow’.
Michael J. Swinbourne, David A. Taggart, Bertram Ostendorf   +2 more
doaj   +1 more source

Effect of intercropping of corn and sainfoin on control of the European corn borer, Ostrinia nubilalis (Lepidoptera: Crambidae), and on yield of both crops [PDF]

نامه انجمن حشره‌شناسی ایران, 2019
The European corn borer, Ostrinia nubilalis Hübner, is one of the most important pests of corn. In this study, the influences of corn monoculture (C), sainfoin monoculture (S) and strip-intercropping of corn with sainfoin in the four row ratios: 2C:2S ...
Elham Zarei, Seyed Ali Asghar Fathi, Mahdi Hassanpour, ALI Golizadeh   +3 more
doaj   +1 more source

Exploration de la diversité et de la distribution des arthropodes terrestres dans la Réserve de biosphère des cactus au Maroc

African and Mediterranean Agricultural Journal - Al Awamia
La compréhension de la diversité, des schémas spatiaux et des tendances temporelles des communautés d'arthropodes terrestres dans la Réserve de biosphère de cactus au Maroc reste limitée. Cette étude avait pour objectif d'examiner la richesse spécifique,
Mohamed EL AALAOUI, Mohamed Sbaghi
doaj   +1 more source

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

PLoS ONE, 2016
Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps ...
M. Májeková, Taavi Paal, Nichola S. Plowman, M. Bryndová, Liis Kasari, A. Norberg, M. Weiss, T. R. Bishop, S. Luke, K. Sam, Yoann Le Bagousse‐Pinguet, J. Lepš, L. Götzenberger, Francesco de Bello   +13 more
semanticscholar   +1 more source

Abundance‐mediated species interactions

Ecology
AbstractSpecies interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly
Joshua P. Twining, Ben C. Augustine, J. Andrew Royle, Angela K. Fuller   +3 more
openaire   +2 more sources

Prioritizing Management of Non-Native Eurasian Watermilfoil Using Species Occurrence and Abundance Predictions

Diversity, 2020
Prioritizing the prevention and control of non-native invasive species requires understanding where introductions are likely to occur and cause harm. We developed predictive models for Eurasian watermilfoil (EWM) (Myriophyllum spicatum L.) occurrence and
Alison Mikulyuk, Catherine L. Hein, Scott Van Egeren, Ellen Ruth Kujawa, M. Jake Vander Zanden   +4 more
doaj   +1 more source

Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol

PLoS ONE, 2015
Metabarcoding is an emerging genetic tool to rapidly assess biodiversity in ecosystems. It involves high-throughput sequencing of a standard gene from an environmental sample and comparison to a reference database.
Vasco Elbrecht, F. Leese
semanticscholar   +1 more source

How species richness and total abundance constrain the distribution of abundance

Ecology Letters, 2013
AbstractThe species abundance distribution (SAD) is one of the most intensively studied distributions in ecology and its hollow‐curve shape is one of ecology's most general patterns. We examine the SAD in the context of all possible forms having the same richness (S) and total abundance (N), i.e. the feasible set.
Locey, Kenneth J, White, Ethan P.
openaire   +4 more sources