Insights from modeling studies on how climate change affects invasive alien species geography

Climate change and biological invasions are threatening biodiversity and ecosystem services worldwide. It has now been widely acknowledged that climate change will affect biological invasions. A large number of studies have investigated predicted shifts and other changes in the geographic ranges of invasive alien species related to climate change using modeling approaches. Yet these studies have provided contradictory evidence, and no consensus has been reached. We conducted a systematic review of 423 modeling case studies included in 71 publications that have examined the predicted effects of climate change on those species. We differentiate the approaches used in these studies and synthesize their main results. Our results reaffirm the major role of climate change as a driver of invasive alien species distribution in the future. We found biases in the literature both regarding the taxa, toward plants and invertebrates, and the areas of the planet investigated. Despite these biases, we found for the plants and vertebrates studied that climate change will more frequently contribute to a decrease in species range size than an increase in the overall area occupied. This is largely due to oceans preventing terrestrial invaders from spreading poleward. In contrast, we found that the ranges of invertebrates and pathogens studied are more likely to increase following climate change. An important caveat to these findings is that researchers have rarely considered the effects of climate change on transport, introduction success, or the resulting impacts. We recommend closing these research gaps, and propose additional avenues for future investigations, as well as opportunities and challenges for managing invasions under climate change.     

How to deal with ground truthing affected by human‐induced habitat change?: Identifying high‐quality habitats for the Critically Endangered Red Siskin

Species distribution models (SDM) can be valuable for identifying key habitats for conservation management of threatened taxa, but anthropogenic habitat change can undermine SDM accuracy. We used data for the Red Siskin (Spinus cucullatus), a critically endangered bird and ground truthing to examine anthropogenic habitat change as a source of SDM inaccuracy. We aimed to estimate: (1) the Red Siskin's historic distribution in Venezuela; (2) the portion of this historic distribution lost to vegetation degradation; and (3) the location of key habitats or areas with both, a high probability of historic occurrence and a low probability of vegetation degradation. We ground‐truthed 191 locations and used expert opinion as well as landscape characteristics to classify species' habitat suitability as excellent, good, acceptable, or poor. We fit a Random Forest model (RF) and Enhanced Vegetation Index (EVI) time series to evaluate the accuracy and precision of the expert categorization of habitat suitability. We estimated the probability of historic occurrence by fitting a MaxLike model using 88 presence records (1960–2013) and data on forest cover and aridity index. Of the entire study area, 23% (20,696 km²) had a historic probability of Red Siskin occurrence over 0.743. Furthermore, 85% of ground‐truthed locations had substantial reductions in mean EVI, resulting in key habitats totaling just 976 km², in small blocks in the western and central regions. Decline in Area of Occupancy over 15 years was between 40% and 95%, corresponding to an extinction risk category between Vulnerable and Critically Endangered. Relating key habitats with other landscape features revealed significant risks and opportunities for proposed conservation interventions, including the fact that ongoing vegetation degradation could limit the establishment of reintroduced populations in eastern areas, while the conservation of remaining key habitats on private lands could be improved with biodiversity‐friendly agri‐ and silviculture programs.     

Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models

Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears (Ursus arctos) and wolves (Canis lupus) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.     

The role of recruitment and dispersal limitation in tree community assembly in Amazonian forests

Background: Species composition of plant communities is shaped by the interplay between dispersal limitation, environmental filters and stochastic events.

Aims: The aim of this work was to investigate the effects of dispersal limitation and environmental filtering on tree recruitment. To accomplish this, we employed the unified neutral theory of biodiversity and biogeography to examine migration within the metacommunity, defined as a set of interacting local communities linked by the dispersal of multiple potentially interacting species.

Methods: We sampled 12,975 individuals with dbh ≥ 1 cm in 26 1-ha permanent plots, including habitats of terra firme, transitional forests, várzea and campinarana, on the upper Madeira River, Brazilian Amazon.

Results: Campinarana drew individuals from outside the metacommunity species pool at a mean probability of recruitment of 0.06, a much lower probability than terra firme (0.31), transitional (0.21) and várzea forests (0.22). Environmental variables, such as water table depth, soil texture and fertility, were related to differences in community assembly.

Conclusions: Species abundance distribution and diversity patterns of plant assemblages in a large river landscape in the Amazon highlight the importance of environmental heterogeneity that conditions beta-diversity. The high variation in recruitment probabilities from the metacommunity species pool to local communities suggests high habitat variability in the process of maintaining patterns of local diversity.     

一例母及其亲子DNA指纹与血清蛋白、酯酶遗传的研究

采用ＤＮＡ指纹分析和聚丙烯酰胺凝胶电泳法,对一例与公驴交配生育了后代的母后代进行了亲缘鉴定和血清蛋白、酯酶遗传的分析。结果可以认定其亲子关系并证实母骡生育的事实。虽然本例母的后代在Ｐｒ、Ａｌ、Ｐａ和Ｈｂ、Ｅｓ等基因座位上的基因表达倾向于驴,但其外貌仍明显地带有种间杂种的特征。因此,尚不能简单地认为其已“回归”为纯种的驴。     

Placing empirical limits on metapopulation models for terrestrial plants

Both island-biogeographic (dynamic) and niche-based (static) metapopulation models make predictions about the distribution and abundance of species assemblages. We tested the utility of these models concerning such predictions for terrestrial vascular plants using data from 74 landscapes across the globe. We examined correlations between species frequency and local abundance and shapes of the species frequency distribution. No data set met all of the predictions of any single island-biogeographic metapopulation model. In contrast, all data sets met the predictions of the niche-based model. We conclude that in predicting the distribution of species assemblages of plants over scales greater than 10–1 km, niche-based models are robust while current metapopulation models are insufficient. We discuss limitations in the assumptions of the various models and the types of empirical observations that they will each have to deal with in further developments.     

Modelling and simulation of the architecture and development of the oil-palm (Elaeis guineensis Jacq.) root system

A stochastic model of oil-palm (Elaeis guineensis Jacq.) root system architecture and development has been developed. This model enabled us to create 3-D numerical models of complete root systems by simulation. The application of a postprocessor software, called RACINES, to these 3-D numerical models, provided an estimation of some parameters of plant root systems. The objective of this paper is to present oil-palm root characteristics as possible outputs of the application of this RACINES software. The outputs described in this article cover (i) spatial distribution of roots under plantation conditions, (ii) the estimation and distribution of total root biomass, per root type or per soil horizon and (iii) the location and quantification of absorbent surfaces. The computing techniques used were based on voxellization of space and creation of 3-D virtual sceneries exactly reproducing observed planting designs. By comparing the results of observations and simulations for spatial distribution (by trench wall density maps) and root biomasses (by real and virtual sampling) we were able to carry out additional numerical validations of the model.     

Saltatory search: a theoretical analysis

Many animal search in a saltatory fashion: they move forward,pause briefly, and move forward again. Although many optimal-foragingmodels have been developed, most do not address how an animalsearches for food. We view search strategies as "time-distance"functions to allow not only for the possibility of oscillationsin body speed, as implied by saltatory search, but other movementpatterns as well, including cruise search. The key feature ofour models is distinguishing between the body position and thescan position (where the forager is looking). We see the varyingmovement of saltatory search as a consequence of the curvaturein the functions that relate body speed to benefits (Jensen'sinequality)     

LAKE SEDIMENT CHRYSOPHYTE SCALES FROM THE NORTHEASTERN U.S.A. AND THEIR RELATIONSHIP TO ENVIRONMENTAL VARIABLES

Chrysophyte scale assemblages were analyzed in the surface sediments (0–1 cm) of 146 lakes sampled in the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring and Assessment Program–Surface Waters (EMAP-SW) in the northeastern U.S.A. Chrysophyte data from the EMAP lakes were combined with a previous study of 71 Adirondack PIRLA (Paleoecological Investigation of Recent Lake Acidification) lakes and collectively analyzed to examine the indicator potential of scaled chrysophytes in the northeastern U.S.A. with respect to several environmental variables. Canonical correspondence analysis (CCA) was used to determine which environmental variables influenced the distributions of species. Forward selection and Monte Carlo permutation tests showed that 51% of the variance in the chrysophyte assemblages was related to pH. The other six significant variables (conductivity, chloride, total phosphorus [TP], elevation, lake depth, and watershed area) contributed an additional 31% of the total (82%) variance explained by the seven forward-selected variables. Similar to previous studies, many taxa showed distinct distribution patterns with respect to pH. Partial and constrained CCAs indicated that, although all seven variables explained significant proportions of variation in the species data, a reliable inference model could be developed only for lake-water pH. The strength of this model ( R ²= 0.78, RMSE_boot= 0.47 of a pH unit) is comparable to a recently constructed diatom-based model for the EMAP lakes. The use of both models in paleolimnological and biomonitoring studies would be advantageous because they would provide two independent lines of evidence of environmental change.