538 research outputs found
The challenges of integrating biodiversity and ecosystem services monitoring and evaluation at a landscape-scale wetland restoration project in the UK
No full textHughes, F. M. R., W. M. Adams, S. H. M. Butchart, R. H. Field, K. S.-H. Peh, and S. Warrington. 2016. The challenges of integrating biodiversity and ecosystem services monitoring and evaluation at a landscape-scale wetland restoration project in the UK. Ecology and Society 21(3):10.http://dx.doi.org/10.5751/ES-08616-21031
Projected effect of global change on species' change in extinction risk
No full textClimate change has become one of the major drivers of biodiversity loss, its effects are not only already evident across all levels of biological organization (from genes to ecosystems) but are projected to increase in the coming decades. The probability of a species or population being negatively impacted by climate change (i.e., risk) is determined by the occurrence of adverse climatic events or trends (i.e., hazard), the occurrence of the species or population in areas that could be impacted (i.e., exposure), and their predisposition to be adversely affected, including their sensitivity or susceptibility and lack of capacity to cope or adapt (i.e., vulnerability). Species or populations can adapt to adverse climatic conditions by shifting their geographical distribution or adapting in situ, generally by changing their phenology, morphology or physiology.
Recent efforts to assess the impacts of climate change have predominantly relied on bioclimatic niche modeling, which predicts species’ or populations’ distributions by linking their geographical range and bioclimatic variables. However, these models assume that all species are affected and will respond to climate change similarly, and do not consider differences in vulnerability and exposure. Trait-based assessments have aimed to address this gap, identifying which traits influence risk, allowing assessing multiple species simultaneously in a simple way and serving as a useful tool for prioritizing conservation actions, especially in the absence of distribution data. However, their applicability can be limited as they are not spatially explicit, the relationship between traits and responses is still uncertain, there are gaps in trait data availability and the approach is generally implemented at the species level, ignoring intraspecific differences in exposure, vulnerability and hazard. The objective of this thesis is to overcome some of these limitations for birds and terrestrial non-volant mammals.
To overcome gaps in mammal trait data availability, I compiled in my first chapter COMBINE: A Coalesced Mammal Database of Intrinsic and Extrinsic traits data for 54 traits for 6,234 mammal species, using data from 14 different data sources. These traits covered aspects such as physiology, reproduction, behavior, longevity, diet, and dispersal. I further filled in gaps in the data through a phylogenetic multiple imputation procedure, providing a complete dataset for 21 traits. All data sources and imputed data were flagged, facilitating identifying the origin of the data. This dataset constitutes a useful tool for large-scale ecological and conservation analyses that use traits, including identifying species at risk from climate change. In my second analytical chapter, Relative latitude, temperature increase and breadth of climatic niche influence mammal populations’ response to climate change, I identified current terrestrial non-volant mammal responses to climate change and the intrinsic traits and environmental factors influencing risk. To achieve this, I first performed a literature review on responses to climate change and categorized them into changes in (a) distribution and abundance, (b) phenology, and (c) morphology. I also identified the direction of each type of response: expansion or contraction for distribution and abundance, advance or delay for phenology, increase or decrease for body size, and no change if no response was detected. To model the relationship between risk from climate change and intrinsic and environmental factors, I focused exclusively on distribution and abundance responses due to their direct relationship. I then selected and obtained data for a series of intrinsic traits and environmental factors previously associated with climate change risk. To account for intraspecific variability in environmental factors, I identified populations of the species that experience similar climatic conditions. As these populations were distributed across large geographical areas, I grouped the responses by species and country, reducing the number of instances of opposing or mixed responses (i.e., different studies for the same species and country reporting distribution and abundance contractions and expansions or phenological advances and delays) and allowing the inclusion of the location of the response within the population. I obtained 382 responses belonging to 130 species located in 30 countries. Most of these responses were distribution and abundance responses (80.6%) while phenological and morphological changes constituted 4.5% (17 responses) and 10.2% (39 responses) respectively. The remaining 4.7% did not fit into any of these categories. Regarding distribution and abundance responses, there were more than twice as many contractions (46.43%) as expansions (20.78%), while in 32.79% of cases there was no clear response. The results of our model indicated that contractions were more likely at the warm edge of the population, while expansions were more likely at the cold edge. Small litter size, hibernation, high temperature increase, low climate seasonality and low altitudinal breadth were also linked to an elevated risk of experiencing a negative response.
In my third analytical chapter, Local environmental factors influence bird distribution and phenological responses to climate change, I followed the same approach but focused on bird distribution and abundance and spring phenological responses to climate change. I also gathered data for nine intrinsic bird traits that have been previously hypothesized to be relevant in determining responses to climate change. This allowed me to identify which intrinsic traits and environmental factors influence experiencing distribution contractions or expansions and spring phenological advances, delays or no changes. I obtained 3,012 responses for 918 species located in 32 countries, 60% of them were distribution and abundance responses and the remaining 40% were spring phenology responses. I found that environmental factors played an important role in determining both distribution and abundance and phenological responses to climate change. Maximum temperature, restricted climate seasonality, relative latitudinal position, and maximum longevity influenced the probability of experiencing contractions and a subsequent increase in risk. Similarly, maximum temperature, climate seasonality, relative latitudinal position, and temperature increase influenced the probability of experiencing advances in spring phenology.
The results presented in this thesis constitute an advance in current knowledge on the variables influencing responses to climate change locally and serve as a starting point for future research
Formulating smart commitments on biodiversity: lessons from the Aichi Targets
No full textThe world is currently not on course to achieve most of the Convention on Biological Diversity's Aichi Targets to address biodiversity loss. One challenge for those implementing actions to achieve them may be the complexity and lack of clarity in the wording of the targets, which also make it difficult to stimulate and quantify progress. Drawing on experience in developing and measuring indicators to assess progress toward targets, we identify four key issues: ambiguity, quantifiability, complexity, and redundancy. The magnitude of required commitments under some targets is rendered ambiguous by the use of imprecise terms (e.g., “substantially”), while many targets contain poorly defined operational terms (e.g., “essential services”). Seventy percent of targets lack quantifiable elements, meaning that there is no clear binary or numeric threshold to be met in order for the target to be achieved. Most targets are excessively complex, containing up to seven different elements, while one-third of them contain redundancies. In combination, these four issues make it difficult to operationalize the targets and to ensure consistent interpretation by signatories. For future policy commitments, we recommend the adoption of a smaller number of more focused headline targets (alongside subsidiary targets) that are specific, quantified, simple, succinct, and unambiguous
Poor overlap between the distribution of Protected Areas and globally threatened birds in Africa
No full textProtected Areas (PAs) form a core component of efforts to conserve biodiversity, but are designated for a variety of reasons. We assessed the effectiveness of PAs in covering the ranges of 157 globally threatened terrestrial bird species in mainland Africa and Madagascar. To reduce commission errors, rather than using Extent of Occurrence (EOO) as a measure of distribution, we estimated the Extent of potentially Suitable Habitat (ESH) for each species within its EOO, using data on habitat preferences and land cover. On average, 14% of species' ESH fell within PAs, with negligible coverage of Critically Endangered species. By contrast, an average of 30% of species' ESH fell within Important Bird Areas (IBAs), a network of sites identified using globally standardized criteria as critical for bird conservation. IBAs that overlapped or fell within PAs were significantly less effective at covering the ESH of threatened birds than those falling outside the PA network, and for IBAs partly overlapping with PAs, coverage of threatened birds was significantly greater in the unprotected part. Expansion of the PA (and IBA) networks in parts of Madagascar, the Albertine Rift, Cameroon Highlands, Eastern Arc and eastern Kenya would benefit globally threatened bird species conservation
Erratum to: Species’ traits influenced their response to recent climate change (Nature Climate Change, (2017), 7, 3, (205-208), 10.1038/nclimate3223)
No full textIn the Supplementary Information PDF published with this Letter, under the heading ‘Keywords used to select the papers for the literature review’, operator (*) use in the search strings is inconsistent and at times incorrect. In addition, the full list of references shortlisted from the Web of Science search criteria used in this study was not provided. The amended PDF is available as Supplementary Information to this Correction; those references not cited in the main paper and Methods have been included: refs 59–124 relate to mammals and refs 125–190 to birds
Species' traits influenced their response to recent climate change
No full textAlthough it is widely accepted that future climatic change—if unabated—is likely to have major impacts on biodiversity1, 2, few studies have attempted to quantify the number of species whose populations have already been impacted by climate change3, 4. Using a systematic review of published literature, we identified mammals and birds for which there is evidence that they have already been impacted by climate change. We modelled the relationships between observed responses and intrinsic (for example, body mass) and spatial traits (for example, temperature seasonality within the geographic range). Using this model, we estimated that 47% of terrestrial non-volant threatened mammals (out of 873 species) and 23.4% of threatened birds (out of 1,272 species) may have already been negatively impacted by climate change in at least part of their distribution. Our results suggest that populations of large numbers of threatened species are likely to be already affected by climate change, and that conservation managers, planners and policy makers must take this into account in efforts to safeguard the future of biodiversity
Hepatic CC chemokines control the magnitude of the inflammatory response within the injured rodent brain
No full textHepatic CXC chemokines, behaving as acute phase proteins, regulate neutrophil mobilisation and recruitment following focal IL-1h-mediated inflammation to the rat brain. To determine whether this response was specific to CXC chemokines or whether it represented a more generalised response to acute brain inflammation, we examined brain and liver production of MCP-1, a CC chemokine, when rats were microinjected with TNF-a into the brain. As early as 2h after the TNF-a challenge, MCP-1 mRNA and protein were observed in the liver by Taqman RT-PCR and ELISA. The serum MCP-1 level was also elevated between 2 and 4 h, which was consistent with maximal mobilisation of leukocytes into the blood. Monocyte recruitment was most marked in the liver after 6 h, but was delayed in the brain until 24 h. Elevated hepaticand serum chemokines are implicated in the control of leukocytosis and leukocyte recruitment to the brain and liver, since dexamethasone pretreatment attenuated the hepatic MCP-1 response, modulated leukocyte mobilisation and reduced monocyte entry not only to the brain but also to the liver. Thus hepatic chemokine production controls and amplifies the CNS response to inflammation by controlling the rate, timing, magnitude and composition of leukocyte recruitment to the damaged brain
Minding the protection gap: estimates of species' range sizes and holes in the Protected Area network
No full text[No abstract available
Area of Habitat maps for the world’s terrestrial birds and mammals
No full textMeasurement(s) Species Distributions Technology Type(s) Area of Habitat Factor Type(s) Habitat Sample Characteristic - Organism Mammalia • Aves Sample Characteristic - Environment Terrestrial Habitat
Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments
No full textThe IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment
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