Tree migration in the dynamic, global vegetation model LPJ-GM 1.0: Efficient uncertainty assessment and improved dispersal kernels

The prediction of species geographic redistribution under climate change (i.e. range shifts) has been addressed by both experimental and modelling approaches and can be used to inform efficient policy measures on the functioning and services of future ecosystems. Dynamic Global Vegetation Models (DGVMs) are considered state-of-the art tools to understand and quantify the spatio-temporal dynamics of ecosystems at large scales and their response to changing environments. They can explicitly include local vegetation dynamics relevant to migration (establishment, growth, seed production), species-specific dispersal abilities and the competitive interactions with other species in the new environment. However, the inclusion of more detailed mechanistic formulations of range shift processes may also widen the overall uncertainty of the model. Thus, a quantification of these uncertainties is needed to evaluate and improve our confidence in the model predictions. In this study, we present an efficient assessment of parameter and model uncertainties combining low-cost analyses in successive steps: local sensitivity analysis, exploration of the performance landscape at extreme parameter values, and inclusion of relevant ecological processes in the model structure. This approach was tested on the newly-implemented migration module of the state-of-the-art DGVM, LPJ-GM 1.0. Estimates of post-glacial migration rates obtained from pollen and macrofossil records of dominant European tree taxa were used to test the model performance. The results indicate higher sensitivity of migration rates to parameters associated with the dispersal kernel (dispersal distances and kernel shape) compared to plant traits (germination rate and maximum fecundity) and highlight the importance of representing rare long-distance dispersal events via fat-tailed kernels. Overall, the successful parametrization and model selection of LPJ-GM will allow simulating plant migration with a more mechanistic approach at larger spatial and temporal scales, thus improving our efforts to understand past vegetation dynamics and predict future range shifts in a context of global change.

Range Shifts of Overwintering Birds Depend on Habitat Type, Snow Conditions and Habitat Specialization

Climatic warming is forcing numerous species to shift their ranges poleward, which has been demonstrated for many taxa across the globe. Yet, the influence of habitat types on within- and among-species variations of distribution shifts has rarely been studied, especially so for the non-breeding season. Here, we investigated habitat specific shift distances of northern range margins and directions of the center of gravity based on a long-term dataset of overwintering birds in Finland. Specifically, we explored influences of habitat type, snow cover depths, species’ climatic niche and habitat specialization on range shifts from 1980’s to 2010’s in 81 bird species. Birds overwintering in farmlands shifted significantly more often northwards than birds of the same species in rural and forest habitats, while the northern range margin shift distances did not significantly differ among the habitat types. Snow cover was negatively associated with the eastward shift direction across all habitats, while we found habitat specific relations to snow cover with northward shift directions and northern range margins shift distances. Species with stronger habitat specializations shifted more strongly towards north as compared to generalist species, whereas the climatic niche of bird species only marginally correlated with range shifts, so that cold-dwelling species shifted longer distances and more clearly eastwards. Our study reveals habitat specific patterns linked to snow conditions for overwintering boreal birds and highlights importance of habitat availability and preference in climate driven range shifts.

Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan

Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.

Not all biodiversity rich spots are climate refugia

Anthropogenic climate change is increasingly threatening biodiversity on a global scale. Rich spots of biodiversity, regions with exceptionally high endemism and/or number of species, are a top priority for nature conservation. Terrestrial studies have hypothesized that rich spots occur in places where long-term climate change was dampened relative to other regions. Here we tested whether biodiversity rich spots are likely to provide refugia for organisms during anthropogenic climate change. We assessed the spatial distribution of both historic (absolute temperature change and climate change velocities) and projected climate change in terrestrial, freshwater, and marine rich spots. Our analyses confirm the general consensus that global warming will impact almost all rich spots of all three realms and suggest that their characteristic biota is expected to witness similar forcing to other areas, including range shifts and elevated risk of extinction. Marine rich spots seem to be particularly sensitive to global warming: they have warmed more, have higher climate velocities, and are projected to experience higher future warming than non-rich-spot areas. However, our results also suggest that terrestrial and freshwater rich spots will be somewhat less affected than other areas. These findings emphasize the urgency of protecting a comprehensive and representative network of biodiversity-rich areas that accommodate species range shifts under climate change.

Using Ecological Niche Modelling to Predict Climate Change Responses of Ten Key Fishery Species in Aotearoa New Zealand

<p>The long-term sustainability and security of food sources for an increasing human population will become more challenging as climate change alters growing and harvesting conditions. Significant infrastructure changes could be required to continue to supply food from traditional sources. Fisheries remain the only major protein supply directly harvested from the wild. This likely makes it the most sensitive primary sector to climate change. Overfishing is an additional concern for harvested species. There is a need to anticipate how marine species may respond to climate change to help inform how management might best be prepared for shifting distributions and productivity levels. The most common response of mobile marine species to changes in climate is an alteration of their geographic distributions and/or range shifts. Predicting changes to a species’ range could promote timely development of more sustainable harvest strategies. Additionally, these predictions could reduce potential conflict when different management areas experience increasing or decreasing catches. Ecological Niche Modelling (ENM) is a helpful approach for predicting the response of key fishery species to climate change scenarios. The overall aim of this research was to use the maximum entropy method, Maxent, to perform ENM on 10 commercially important fishery species, managed under the Quota management system in Aotearoa (New Zealand). Occurrence data from trawl surveys were used along with climate layers from Bio-ORACLE to estimate the species niche and then predict distributions in four different future climate scenarios, called Representative Concentration Pathway Scenarios (RCPS), in both 2050 and 2100. With little consensus over the best settings and way to apply the Maxent method, hundreds of variations were tried for each species, and the best model chosen from trial experimentation. In general, Maxent performed well, with evaluation metrics for best models showing little omission error and good discriminatory ability. There was, however, considerable variation between the different species responses to the future climate scenarios. Consistent with other studies, species able to tolerate sub-tropical or temperate conditions tended to expand southward, while subantarctic species generally contracted within their preferred environment. The increasing emissions or ‘business as usual’ climate change scenario consistently presented the most extreme difference from modern predictions. Northern regions of prediction, where sub-tropical or temperate species increased in probability of presence, were often highly uncertain due to novel conditions in future environments. Southern regions were usually less uncertain. Surface temperature consistently influenced base models more so than any other covariates considered, with the exception of bathymetry. Some predictions showed common areas of relative stability, such as hoki and ling on the southern Chatham Rise, potentially indicating future refugia. The preservation of habitats in the putative refugia may be important for long-term fisheries resilience. Furthermore, most species that showed large predicted declines are currently heavily harvested and managed. Overfishing could compound the effects of climate change and put these fisheries at serious risk of collapse. Identification of potential refugial areas could aid strategy adjustments to fishing practice to help preserve stock viability. Additionally, when some species shift, there are areas where new fisheries may emerge. This study offers a perspective of what future distributions could be like under different climate scenarios. The ENM predicts that the ‘business as usual’ scenario, where ‘greenhouse gas’ emissions continue to rise throughout the century, will have a negative impact on multiple aspects of distribution. However, in a reduced emissions scenario, less extreme range shifts are predicted. This study has provided a predictive approach to how fisheries in Aotearoa might change. The next step is to determine whether there is any evidence for the beginning of these changes and to consider how fisheries might best adapt.</p>

Using Ecological Niche Modelling to Predict Climate Change Responses of Ten Key Fishery Species in Aotearoa New Zealand

<p>The long-term sustainability and security of food sources for an increasing human population will become more challenging as climate change alters growing and harvesting conditions. Significant infrastructure changes could be required to continue to supply food from traditional sources. Fisheries remain the only major protein supply directly harvested from the wild. This likely makes it the most sensitive primary sector to climate change. Overfishing is an additional concern for harvested species. There is a need to anticipate how marine species may respond to climate change to help inform how management might best be prepared for shifting distributions and productivity levels. The most common response of mobile marine species to changes in climate is an alteration of their geographic distributions and/or range shifts. Predicting changes to a species’ range could promote timely development of more sustainable harvest strategies. Additionally, these predictions could reduce potential conflict when different management areas experience increasing or decreasing catches. Ecological Niche Modelling (ENM) is a helpful approach for predicting the response of key fishery species to climate change scenarios. The overall aim of this research was to use the maximum entropy method, Maxent, to perform ENM on 10 commercially important fishery species, managed under the Quota management system in Aotearoa (New Zealand). Occurrence data from trawl surveys were used along with climate layers from Bio-ORACLE to estimate the species niche and then predict distributions in four different future climate scenarios, called Representative Concentration Pathway Scenarios (RCPS), in both 2050 and 2100. With little consensus over the best settings and way to apply the Maxent method, hundreds of variations were tried for each species, and the best model chosen from trial experimentation. In general, Maxent performed well, with evaluation metrics for best models showing little omission error and good discriminatory ability. There was, however, considerable variation between the different species responses to the future climate scenarios. Consistent with other studies, species able to tolerate sub-tropical or temperate conditions tended to expand southward, while subantarctic species generally contracted within their preferred environment. The increasing emissions or ‘business as usual’ climate change scenario consistently presented the most extreme difference from modern predictions. Northern regions of prediction, where sub-tropical or temperate species increased in probability of presence, were often highly uncertain due to novel conditions in future environments. Southern regions were usually less uncertain. Surface temperature consistently influenced base models more so than any other covariates considered, with the exception of bathymetry. Some predictions showed common areas of relative stability, such as hoki and ling on the southern Chatham Rise, potentially indicating future refugia. The preservation of habitats in the putative refugia may be important for long-term fisheries resilience. Furthermore, most species that showed large predicted declines are currently heavily harvested and managed. Overfishing could compound the effects of climate change and put these fisheries at serious risk of collapse. Identification of potential refugial areas could aid strategy adjustments to fishing practice to help preserve stock viability. Additionally, when some species shift, there are areas where new fisheries may emerge. This study offers a perspective of what future distributions could be like under different climate scenarios. The ENM predicts that the ‘business as usual’ scenario, where ‘greenhouse gas’ emissions continue to rise throughout the century, will have a negative impact on multiple aspects of distribution. However, in a reduced emissions scenario, less extreme range shifts are predicted. This study has provided a predictive approach to how fisheries in Aotearoa might change. The next step is to determine whether there is any evidence for the beginning of these changes and to consider how fisheries might best adapt.</p>

Limited movement of a hybrid zone in relation to regional variation in magnitude of climate change

Hybrid zones can provide clear documentation of range shifts in response to climate change and identify loci important to reproductive isolation. Using a deep temporal (36-38 years) comparison of the black-capped (Poecile atricapillus) and Carolina (P. carolinensis) chickadee hybrid zone, we investigated movement of the under-sampled western portion of the zone (western Missouri) as well as investigating whether loci and pathways underpinning reproductive isolation were similar to those from the eastern portion of the hybrid zone. Using 92 birds sampled along the hybrid zone transect in 2016, 68 birds sampled between 1978 and 1980, and 5 additional reference birds sampled from outside the hybrid zone, we generated 11,669 SNPs via ddRADseq. We used these SNPs to interpolate spatially and assess the movement of the hybrid zone interface through time, and to assess variation in introgression among loci. We demonstrate that the interface has moved approximately 5-8 km to the northwest over the last 36-38 years, i.e., at only one-fifth the rate at which the eastern portion of the hybrid zone (e.g. Pennsylvania, Ohio) has moved. Temperature trends across the last 38 years reveal that eastern areas have warmed 50% more than western areas in terms of annual mean temperature, possibly providing an explanation for the slower movement of the hybrid zone in Missouri. Using genomic cline analyses, we detected four genes that showed restricted introgression in both Missouri and Pennsylvania, including Pnoc, a gene involved in metabolism, learning and memory, concordant with previous physiological and behavioral findings on hybrids and the parental species.