• Energy Research

Introduction: Cold-adapted bumblebees are vulnerable to climate change (CC). South American Bombus dahlbomii, the southernmost bumblebee worldwide, has strongly declined since the 1990s and may be particularly susceptible to current and future CC. Aims/methods: We asked (1) whether current CC had a role in the observed decline of this species and (2) how projected CC would affect the future distribution of B. dahlbomii. We used a comprehensive record of occurrences for B. dahlbomii and species distribution models (SDMs) to build maps of (1) predicted current climatic suitability using pre-1990s and post-1990s occurrences, and (2) projected current and future climatic suitability under future (2080–2100) RCP 8.5 scenarios predicted by the 5th IPCC Report. Results and discussion: SDMs did not show changes in species climatic suitability pre-1990 vs. post-1990, suggesting no significant role of CC on the observed decline of the species at this time scale. However, a moderate range reduction of 13% and 14% of the ~ 0.041º grid cells was predicted by 2080–2100 under the 70% and 100% consensus models, respectively. Implications for insect conservation: Identifying the threats to B. dahlbomii allows for prioritizing conservation efforts. Short-term threats imposed by invasive bumblebees deserve urgent attention. The potential synergies between this threat and CC need to be understood to better predict the fate of this species. Binational cooperation should guarantee connectivity between climatically suitable areas in Argentina and Chile. Fil: Morales, Carolina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Arbetman, Marina Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Montalva, Jose. East Central University; Estados Unidos. Department of Geography and Environmental Sustainability; Estados Unidos Fil: Silva, Daniel Paiva. Instituto Federal Goiano; Brasil Fil: Martins, Aline C.. Universidade do Brasília; Brasil

Introduction: Cold-adapted bumblebees are vulnerable to climate change (CC). South American Bombus dahlbomii, the southernmost bumblebee worldwide, has strongly declined since the 1990s and may be particularly susceptible to current and future CC. Aims/methods: We asked (1) whether current CC had a role in the observed decline of this species and (2) how projected CC would affect the future distribution of B. dahlbomii. We used a comprehensive record of occurrences for B. dahlbomii and species distribution models (SDMs) to build maps of (1) predicted current climatic suitability using pre-1990s and post-1990s occurrences, and (2) projected current and future climatic suitability under future (2080–2100) RCP 8.5 scenarios predicted by the 5th IPCC Report. Results and discussion: SDMs did not show changes in species climatic suitability pre-1990 vs. post-1990, suggesting no significant role of CC on the observed decline of the species at this time scale. However, a moderate range reduction of 13% and 14% of the ~ 0.041º grid cells was predicted by 2080–2100 under the 70% and 100% consensus models, respectively. Implications for insect conservation: Identifying the threats to B. dahlbomii allows for prioritizing conservation efforts. Short-term threats imposed by invasive bumblebees deserve urgent attention. The potential synergies between this threat and CC need to be understood to better predict the fate of this species. Binational cooperation should guarantee connectivity between climatically suitable areas in Argentina and Chile. Fil: Morales, Carolina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Arbetman, Marina Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Montalva, Jose. East Central University; Estados Unidos. Department of Geography and Environmental Sustainability; Estados Unidos Fil: Silva, Daniel Paiva. Instituto Federal Goiano; Brasil Fil: Martins, Aline C.. Universidade do Brasília; Brasil

Wild and managed pollinators provide a wide range of benefits to society in terms of contributions to food security, farmer and beekeeper livelihoods, social and cultural values, as well as the maintenance of wider biodiversity and ecosystem stability. Pollinators face numerous threats, including changes in land-use and management intensity, climate change, pesticides and genetically modified crops, pollinator management and pathogens, and invasive alien species. There are well-documented declines in some wild and managed pollinators in several regions of the world. However, many effective policy and management responses can be implemented to safeguard pollinators and sustain pollination services.

Wild and managed pollinators provide a wide range of benefits to society in terms of contributions to food security, farmer and beekeeper livelihoods, social and cultural values, as well as the maintenance of wider biodiversity and ecosystem stability. Pollinators face numerous threats, including changes in land-use and management intensity, climate change, pesticides and genetically modified crops, pollinator management and pathogens, and invasive alien species. There are well-documented declines in some wild and managed pollinators in several regions of the world. However, many effective policy and management responses can be implemented to safeguard pollinators and sustain pollination services.

Marcelo A. Aizen, Gabriela R. Gleiser, Thomas Kitzberger, Ruben Milla. Being a tree crop increases the odds of experiencing yield declines irrespective of pollinator dependence (to be submitted to PCI) Data and R scripts to reproduce the analyses and the figures shown in the paper. All analyses were performed using R 4.0.2. Data 1. FAOdata_21-12-2021.csv This file includes yearly data (1961-2020, column 8) on yield and cultivated area (columns 6 and 10) at the country, sub-regional, and regional levels (column 2) for each crop (column 4) drawn from the United Nations Food and Agriculture Organization database (data available at http://www.fao.org/faostat/en; accessed July 21-12-2021). [Used in Script 1 to generate the synthesis dataset] 2. countries.csv This file provides information on the region (column 2) to which each country (column 1) belongs. [Used in Script 1 to generate the synthesis dataset] 3. dependence.csv This file provides information on the pollinator dependence category (column 2) of each crop (column 1). 4. traits.csv This file provides information on the traits of each crop other than pollinator dependence, including, besides the crop name (column1), the variables type of harvested organ (column 5) and growth form (column 6). [Used in Script 1 to generate the synthesis dataset] 5. dataset.csv The synthesis dataset generated by Script 1. 6. growth.csv The yield growth dataset generated by Script 1 and used as input by Scripts 2 and 3. 7. phylonames.csv This file lists all the crops (column 1) and their equivalent tip names in the crop phylogeny (column 2). [Used in Script 2 for the phylogenetically-controlled analyses] 8.phylo137.tre File containing the phylogenetic tree. Scripts 1. dataset This R script curates and merges all the individual datasets mentioned above into a single dataset, estimating and adding to this single dataset the growth rate for each crop and country, and the (log) cumulative harvested area per crop and country over the period 1961-2020. 2. analyses This R script includes all the analyses described in the article’s main text. 3. figures This R script creates all the main and supplementary figures of this article. 4. lme4_phylo_setup R function written by Li and Bolker (2019) to carry out phylogenetically-controlled generalized linear mixed-effects models as described in the main text of the article. References Li, M., and B. Bolker. 2019. wzmli/phyloglmm: First release of phylogenetic comparative analysis in lme4- verse. Zenodo. https://doi.org/10.5281/zenodo.2639887. The R scripts included here are updated versions of those than can be found at https://doi.org/10.5281/zenodo.7863825

Marcelo A. Aizen, Gabriela R. Gleiser, Thomas Kitzberger, Ruben Milla. Being a tree crop increases the odds of experiencing yield declines irrespective of pollinator dependence (to be submitted to PCI) Data and R scripts to reproduce the analyses and the figures shown in the paper. All analyses were performed using R 4.0.2. Data 1. FAOdata_21-12-2021.csv This file includes yearly data (1961-2020, column 8) on yield and cultivated area (columns 6 and 10) at the country, sub-regional, and regional levels (column 2) for each crop (column 4) drawn from the United Nations Food and Agriculture Organization database (data available at http://www.fao.org/faostat/en; accessed July 21-12-2021). [Used in Script 1 to generate the synthesis dataset] 2. countries.csv This file provides information on the region (column 2) to which each country (column 1) belongs. [Used in Script 1 to generate the synthesis dataset] 3. dependence.csv This file provides information on the pollinator dependence category (column 2) of each crop (column 1). 4. traits.csv This file provides information on the traits of each crop other than pollinator dependence, including, besides the crop name (column1), the variables type of harvested organ (column 5) and growth form (column 6). [Used in Script 1 to generate the synthesis dataset] 5. dataset.csv The synthesis dataset generated by Script 1. 6. growth.csv The yield growth dataset generated by Script 1 and used as input by Scripts 2 and 3. 7. phylonames.csv This file lists all the crops (column 1) and their equivalent tip names in the crop phylogeny (column 2). [Used in Script 2 for the phylogenetically-controlled analyses] 8.phylo137.tre File containing the phylogenetic tree. Scripts 1. dataset This R script curates and merges all the individual datasets mentioned above into a single dataset, estimating and adding to this single dataset the growth rate for each crop and country, and the (log) cumulative harvested area per crop and country over the period 1961-2020. 2. analyses This R script includes all the analyses described in the article’s main text. 3. figures This R script creates all the main and supplementary figures of this article. 4. lme4_phylo_setup R function written by Li and Bolker (2019) to carry out phylogenetically-controlled generalized linear mixed-effects models as described in the main text of the article. References Li, M., and B. Bolker. 2019. wzmli/phyloglmm: First release of phylogenetic comparative analysis in lme4- verse. Zenodo. https://doi.org/10.5281/zenodo.2639887. The R scripts included here are updated versions of those than can be found at https://doi.org/10.5281/zenodo.7863825

ABSTRACTCrop yields,i.e., harvestable production per unit of cropland area, are in decline for a number of crops and regions, but the drivers of this process are poorly known. Global decreases in pollinator abundance and diversity have been proposed as a major driver of yield declines in crops that depend on animals, mostly bees, to produce fruits and seeds. Alternatively, widespread tree mortality has been directly and indirectly related to global climate change, which could also explain yield decreases in tree crops. As tree crops are expected to be more dependent on pollinators than other crop types, disentangling the relative influence of growth form and pollinator dependence is relevant to identify the ultimate factors driving yield declines. Yield decline, defined here as a negative average annual yearly change in yield from 1961 to 2020, was measured in 4270 time series, involving 136 crops and 163 countries and territories. About one-fourth of all time series showed declines in crop yield, a characteristic associated with both high pollinator dependence and a tree growth form. Because pollinator dependence and plant growth form were partially correlated, we disentangled the effect of each of these two predictors using a series of generalized linear mixed models that evaluated direct and indirect associations. Our analyses revealed a stronger association of yield decline with growth form than with pollinator dependence, a relationship that persisted after partialling out the effect of pollinator dependence. In particular, yield declines were more common among tree than herbaceous and shrub crops in all major regions but in Africa, a continent showing a high incidence of yield declines irrespective of growth form. These results suggest that pollinator decline is not the main reason behind crop productivity loss, but that other factors such as climate change could be already affecting crop yield.