Predicting invasion risk using measures of introduction effort and environmental niche models.

The Chinese mitten crab (Eriocheir sinensis) is native to east Asia, is established throughout Europe, and is introduced but geographically restricted in North America. We developed and compared two separate environmental niche models using genetic algorithm for rule set prediction (GARP) and mitten crab occurrences in Asia and Europe to predict the species' potential distribution in North America. Since mitten crabs must reproduce in water with >15% per hundred salinity, we limited the potential North American range to freshwater habitats within the highest documented dispersal distance (1260 km) and a more restricted dispersal limit (354 km) from the sea. Applying the higher dispersal distance, both models predicted the lower Great Lakes, most of the eastern seaboard, the Gulf of Mexico and southern extent of the Mississippi River watershed, and the Pacific northwest as suitable environment for mitten crabs, but environmental match for southern states (below 35 degrees N) was much lower for the European model. Use of the lower range with both models reduced the expected range, especially in the Great Lakes, Mississippi drainage, and inland areas of the Pacific Northwest. To estimate the risk of introduction of mitten crabs, the amount of reported ballast water discharge into major United States ports from regions in Asia and Europe with established mitten crab populations was used as an index of introduction effort. Relative risk of invasion was estimated based on a combination of environmental match and volume of unexchanged ballast water received (July 1999-December 2003) for major ports. The ports of Norfolk and Baltimore were most vulnerable to invasion and establishment, making Chesapeake Bay the most likely location to be invaded by mitten crabs in the United States. The next highest risk was predicted for Portland, Oregon. Interestingly, the port of Los Angeles/Long Beach, which has a large shipping volume, had a low risk of invasion. Ports such as Jacksonville, Florida, had a medium risk owing to small shipping volume but high environmental match. This study illustrates that the combination of environmental niche- and vector-based models can provide managers with more precise estimates of invasion risk than can either of these approaches alone.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

Genetic diversity and population structure of the Chinese mitten crab <Emphasis Type="Italic">Eriocheir sinensis</Emphasis> in its native range

The Chinese mitten crab Eriocheir sinensis is an indigenous and economically important species in China, but can also be found as invasive species in Europe and America. Mitten crabs have been exploited extensively as a food resource since the 1990s. Despite its ecological and economic importance, the genetic structure of native mitten crab populations is not well understood. In this paper, we investigated the genetic structure of mitten crab populations in China by screening samples from ten locations covering six river systems at six microsatellite loci. Our results provide further evidence that mitten crabs from the River Nanliujiang in Southern China are a genetically differentiated population within the native range of Eriocheir, and should be recognized as a separate taxonomic unit. In contrast, extremely low levels of genetic differentiation and no significant geographic population structure were found among the samples located north of the River Nanliujiang. Based on the reproductive biology of mitten crabs and the geography of their habitat we argue that both natural and human-mediated gene flow are unlikely to fully account for the similar allele frequency distributions at microsatellite loci. Large population sizes of mitten crabs suggest instead that a virtual absence of genetic drift and significant homoplasy of microsatellite alleles have contributed to the observed pattern. Furthermore, a coalescent-based maximum likelihood method indicated a more than two-fold lower effective population size of the Southern population compared to the Northern Group and low but significant levels of gene flow between both areas.     

Forecasting New Zealand Mudsnail invasion range: model comparisons using native and invaded ranges.

Evaluations of the potential distribution of invasive species can increase the efficiency of their management by focusing prevention measures. Generally, ecological models are built using occurrence data from a species' native range to predict the distribution in areas that the species may invade. However, historical and geographical constraints can limit a species' native distribution. Genetic Algorithm for Rule-set Production (GARP), an ecological niche modeling program, was used to predict the potential distribution of the invasive, freshwater New Zealand mudsnail, Potamopyrgus antipodarum, in Australia and North America. We compared the strength of the predictions made by models built with data from the snail's native range in New Zealand to models built with data from the locations invaded by the species. A time-series analysis of the Australian models demonstrated that range-of-invasion data can make better predictions about the potential distribution of invasive species than models built with native range data. Large differences among the model forecasts indicate that uncritical choice of the data set used in training the GARP models can result in misleading predictions. The models predict a large expansion in the range of P. antipodarum in both Australia and North America unless prevention measures are implemented rapidly.     

Forecasting the Spread of Invasive Rainbow Smelt in the Laurentian Great Lakes Region of North America

Abstract:  Rainbow smelt ( Osmerus mordax ) have invaded many North American lakes, often resulting in the extirpation of native fish populations. Yet, their invasion is incipient and provides the rationale for identifying ecosystems likely to be invaded and where management and prevention efforts should be focused. To predict smelt presence and absence, we constructed a classification-tree model based on habitat data from 354 lakes in the native range for smelt in southern Maine. Maximum lake depth, lake area, and Secchi depth (surrogate measure of lake productivity) were the most important predictors. We then used our model to identify lakes vulnerable to invasion in three regions outside the smelt's native range: northern Maine (52 of 244 lakes in the non-native range), Ontario (4447 of 8110), and Wisconsin (553 of 5164). We further identified a subset of lakes with a strong potential for impact (potential–impact lakes) based on the presence of fish species that are affected by rainbow smelt. Ninety-four percent of vulnerable lakes in the non-native range in Maine are also potential–impact lakes, as are 94% and 58% of Ontario and Wisconsin's vulnerable lakes, respectively. Our modeling approach can be applied to other invaders and regions to identify invasion-prone ecosystems, thus aiding in the management of invasive species and the efficient allocation of invasive species mitigation and prevention resources.     

Effects of Climate Change,Invasive Species,and Disease on the Distribution of Native European Crayfishes

Climate change will require species to adapt to new conditions or follow preferred climates to higher latitudes or elevations, but many dispersal‐limited freshwater species may be unable to move due to barriers imposed by watershed boundaries. In addition, invasive nonnative species may expand into new regions under future climate conditions and contribute to the decline of native species. We evaluated future distributions for the threatened European crayfish fauna in response to climate change, watershed boundaries, and the spread of invasive crayfishes, which transmit the crayfish plague, a lethal disease for native European crayfishes. We used climate projections from general circulation models and statistical models based on Mahalanobis distance to predict climate‐suitable regions for native and invasive crayfishes in the middle and at the end of the 21st century. We identified these suitable regions as accessible or inaccessible on the basis of major watershed boundaries and present occurrences and evaluated potential future overlap with 3 invasive North American crayfishes. Climate‐suitable areas decreased for native crayfishes by 19% to 72%, and the majority of future suitable areas for most of these species were inaccessible relative to native and current distributions. Overlap with invasive crayfish plague‐transmitting species was predicted to increase. Some native crayfish species (e.g., noble crayfish [Astacus astacus]) had no future refugia that were unsuitable for the modeled nonnative species. Our results emphasize the importance of preventing additional introductions and spread of invasive crayfishes in Europe to minimize interactions between the multiple stressors of climate change and invasive species, while suggesting candidate regions for the debatable management option of assisted colonization. Efectos del Cambio Climático, Especies Invasoras y Enfermedades sobre la Distribución de Cangrejos de Río Europeos Nativos     

Biotic resistance to green crab, <Emphasis Type="Italic">Carcinus maenas</Emphasis>, in California bays

The distribution of the introduced European green crab, Carcinus maenas, was investigated in the central California embayments of Bodega Bay Harbor (BBH), Tomales Bay, and Bolinas Lagoon using baited traps and snorkel surveys. Adult green crabs were very spatially limited in all three embayments and occurred primarily in warm, shallow areas that lacked large native Cancer spp. crabs. The green crabs that were found in closest proximity to populations of Cancer spp. exhibited high levels of limb damage and loss; damage was strongly correlated with low ratios of intertidal area: edge, indicative of narrow areas of intertidal that are more easily accessed by large Cancer spp. moving up to forage during periods of tidal inundation. Up to 70% of the green crabs tethered in areas of BBH that are utilized by Cancer spp. experienced limb loss, while those tethered in the marsh, where there are no Cancer spp., were undamaged. The results suggest that the potential distribution of green crabs in the northeastern Pacific will be far less than has been predicted, and that their impacts may be largely attenuated through predation by and competition with native crab species.     

Using Niche-Based Models to Improve the Sampling of Rare Species

Abstract:  Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.     

Current and Potential Ranges of Three Exotic Goldenrods (Solidago) in Europe

Abstract: The homoclime approach has been used to estimate the potential distributions of the exotic goldenrods Solidago altissima , S. gigantea , and S. graminifolia in Europe. These three rhizomatous perennial plants were introduced as ornamentals about 250 years ago. Whereas S. altissima and S. gigantea have become widespread and serious invaders of abandoned fields, forest edges, and river banks, S. graminifolia is still confined to a few sites in Europe. Climatic profiles of their native ranges have been established for each species based on nine parameters from stations throughout their American ranges. I determined potential distributions for each species by mapping European stations that match the climatic profiles. The potential distributions of all three species are substantially larger than their current distributions in Europe. Areas not yet colonized but predicted to be climatically suitable included parts of southern and southeastern Europe, Scandinavia, and the Middle East. Among the three species, the potential range of S. altissima was largest in its latitudinal extent. The discrepancy between current and potential range was highest in S. graminifolia because of its restricted distribution. My results strongly suggest that the spread of S. altissima and S. gigantea has not yet reached its limits and that their range expansion will continue. Large parts of Europe were estimated to be climatically suitable to S. graminifolia , but invasion has not yet occurred. This species is either in lag phase or its spread is limited by factors other than climate.     

Predicting Risk of Habitat Conversion in Native Temperate Grasslands

Abstract: Native grasslands that support diverse populations of birds are being converted to cropland at an increasing rate in the Prairie Pothole Region of North America. Although limited funding is currently available to mitigate losses, accurate predictions of probability of conversion would increase the efficiency of conservation measures. We studied conversion of native grassland to cropland in the Missouri Coteau region of North and South Dakota (U.S.A.) during 1989–2003. We estimated the probability of conversion of native grassland to cropland with satellite imagery and logistic regression models that predicted risk of conversion and by comparing the overlap between areas of high biological value and areas most vulnerable to conversion. Annualized probability of conversion was 0.004, and 36,540 ha of native grassland were converted to cropland during the period of our study. Our predictive models fit the data and correctly predicted 70% of observed conversions of grassland. Probability of conversion varied spatially and was correlated with landscape features like amount of surrounding grassland, slope, and soil productivity. Tracts of high biological value were not always at high risk of conversion. We concluded the most biologically valuable areas that are most vulnerable to conversion should be prioritized for conservation. This approach can be applied broadly to other systems and offers great utility for implementing conservation in areas with spatially variable biological value and probability of conversion.     

Increase in Quantity and Quality of Suitable Areas for Invasive Species as Climate Changes

As climatically suitable range projections become increasingly used to assess distributions of species, we recommend systematic assessments of the quality of habitat in addition to the classical binary classification of habitat. We devised a method to assess occurrence probability, captured by a climatic suitability index, through which we could determine variations in the quality of potential habitat. This relative risk assessment circumvents the use of an arbitrary suitability threshold. We illustrated our method with 2 case studies on invasive ant species. We estimated invasion potential of the destroyer ant (Monomorium destructor) and the European fire ant (Myrmica rubra) on a global scale currently and by 2080 with climate change. We found that 21.1% of the world's landmass currently has a suitable climate for the destroyer ant and 16% has a suitable climate for European fire ant. Our climatic suitability index showed that both ant species would benefit from climate change, but in different ways. The size of the potential distribution increased by 35.8% for the destroyer ant. Meanwhile, the total area of potential distribution remained the same for the European fire ant (>0.05%), but the level of climatic suitability within this range increased greatly and led to an improvement in habitat quality (i.e., of invasive species’ establishment likelihood). Either through quantity or quality of suitable areas, both invasive ant species are likely to increase the extent of their invasion in the future, following global climate change. Our results show that species may increase their range if either more areas become suitable or if the available areas present improved suitability. Studies in which an arbitrary suitability threshold was used may overlook changes in area quality within climatically suitable areas and as a result reach incorrect predictions. Incremento de la Cantidad y Calidad de Áreas Idóneas para Especies Invasoras a Medida que Cambia el Clima     

Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America

In the Pacific northwestern (PNW) region of North America, climatic conditions have significantly warmed since a predominantly cool phase of the Pacific North American circulation patterns between 1950 and 1975. What are the implications of this shift in climate for the vulnerability of native tree species? To address this question, we combined mechanistic and statistical models to assess where a variety of native tree species might be more vulnerable within their recorded ranges and where they might potentially migrate. For long-lived species that are well adapted to compete, seasonal differences in photosynthesis and water use offer insights helpful in predicting their distributions. To evaluate the general response of conifers to climatic variation across the region, we previously applied a process-based model (3-PG), to simulate the growth and maximum leaf area index that Douglas-fir could attain within recognized forested areas. We then constructed automated decision tree models to define and map the ecological distributions of 15 tree species based on differences in how photosynthesis was constrained by drought, daytime temperatures, high evaporative demand, and the frequency of frost. For the baseline climate period (1950-1975), the decision tree models predicted presence and absence of each species at ∼23,000 observations with an average accuracy of 81%, with an average kappa statistic of 0.74. In this paper the same models were run annually for the period between 1976 and 2006 for each species, and the areas defined as remaining suitable or becoming vulnerable to disturbance were identified based on whether more or less than half of the years fell within the originally defined limits. Based on these criteria, 70% of the species recorded ranges remained suitable, with 30% deemed vulnerable. Results varied notably by species with western red cedar and western hemlock remaining highly adapted, with potential for range expansion in area of up to 50% relative to the baseline period. In contrast, ponderosa pine, lodgepole pine, grand, and noble fir were classified as vulnerable with potential net contractions in their ranges. The analysis was extended through the rest of the 21st century using climatic projections from the Canadian global circulation model with a high fossil fuel emission scenario (A2) and compared to other previously published species range predictions.     

Native ecotypic variation and the role of host identity in the spread of an invasive herbivore, Cactoblastis cactorum

Environmental niche models (ENMs) have gained enormous popularity as tools to investigate potential changes in species distributions resulting from climate change and species introductions. Despite recognition that species interactions can influence the dynamics of invasion spread, most implementations of ENMs focus on abiotic factors as the sole predictors of potential range limits. Implicit in this approach is the assumption that biotic interactions are relatively unimportant, either because of scaling issues, or because fundamental and realized niches are equivalent in a species' native range. When species are introduced into exotic landscapes, changes in biotic interactions relative to the native range can lead to occupation of different regions of niche space and apparent shifts in physiological tolerances. We use an escaped biological control organism, Cactoblastis cactorum (Berg.), to assess the role of the environmental envelope as compared with patterns of host-herbivore associations based on collections made in the native range. Because all nonnative populations are derived from a single C. cactorum ecotype, we hypothesize that biotic interactions associated with this ecotype are driving the species' invasion dynamics. Environmental niche models constructed from known native populations perform poorly in predicting nonnative distributions of this species, except where there is an overlap in niche space. In contrast, genetic isolation in the native range is concordant with the observed pattern of host use, and strong host association has been noted in nonnative landscapes. Our results support the hypothesis that the apparent shift in niche space from the native to the exotic ranges results from a shift in biotic interactions, and demonstrate the importance of considering biotic interactions in assessing the risk of future spread for species whose native range is highly constrained by biotic interactions.     

Testing the Generality of Bird-Habitat Models

Bird-habitat models are frequently used as predictive modeling tools—for example, to predict how a species will respond to habitat modifications. We investigated the generality of the predictions from this type of model. Multivariate models were developed for Golden Eagle (Aquila chrysaetos), Raven (Corvus corax), and Buzzard (Buteo buteo) living in northwest Scotland. Data were obtained for all habitat and nest locations within an area of 2349 km². This assemblage of species is relatively static with respect to both occupancy and spatial positioning. The area was split into five geographic subregions: two on the mainland and three on the adjacent Island of Mull, which has one of United Kingdom's richest raptor fauna assemblages. Because data were collected for all nest locations and habitats, it was possible to build models that did not incorporate sampling error. A range of predictive models was developed using discriminant analysis and logistic regression. The models differed with respect to the geographical origin of the data used for model development. The predictive success of these models was then assessed by applying them to validation data. The models showed a wide range of predictive success, ranging from only 6% of nest sites correctly predicted to 100% correctly predicted. Model validation techniques were used to ensure that the models' predictions were not statistical artefacts. The variability in prediction success seemed to result from methodological and ecological processes, including the data recording scheme and interregional differences in nesting habitat. The results from this study suggest that conservation biologists must be very careful about making predictions from such studies because we may be working with systems that are inherently unpredictable.     

Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges because (i) they typically violate SDM's assumption that the organism is in equilibrium with its environment, and (ii) species absence data are often unavailable or believed to be too difficult to interpret. This often leads researchers to generate pseudo-absences for model training or utilize presence-only methods, and to confuse the distinction between predictions of potential vs. actual distribution. We examined the hypothesis that true-absence data, when accompanied by dispersal constraints, improve prediction accuracy and ecological understanding of iSDMs that aim to predict the actual distribution of biological invasions. We evaluated the impact of presence-only, true-absence and pseudo-absence data on model accuracy using an extensive dataset on the distribution of the invasive forest pathogen Phytophthora ramorum in California. Two traditional presence/absence models (generalized linear model and classification trees) and two alternative presence-only models (ecological niche factor analysis and maximum entropy) were developed based on 890 field plots of pathogen occurrence and several climatic, topographic, host vegetation and dispersal variables. The effects of all three possible types of occurrence data on model performance were evaluated with receiver operating characteristic (ROC) and omission/commission error rates. Results show that prediction of actual distribution was less accurate when we ignored true-absences and dispersal constraints. Presence-only models and models without dispersal information tended to over-predict the actual range of invasions. Models based on pseudo-absence data exhibited similar accuracies as presence-only models but produced spatially less feasible predictions. We suggest that true-absence data are a critical ingredient not only for accurate calibration but also for ecologically meaningful assessment of iSDMs that focus on predictions of actual distributions.     

Avoiding Pitfalls of Using Species Distribution Models in Conservation Planning

Abstract:   Museum records have great potential to provide valuable insights into the vulnerability, historic distribution, and conservation of species, especially when coupled with species-distribution models used to predict species' ranges. Yet, the increasing dependence on species-distribution models in identifying conservation priorities calls for a more critical evaluation of model robustness. We used 11 bird species of conservation concern in Brazil's highly fragmented Atlantic Forest and data on environmental conditions in the region to predict species distributions. These predictions were repeated for five different model types for each of the 11 bird species. We then combined these species distributions for each model separately and applied a reserve-selection algorithm to identify priority sites. We compared the potential outcomes from the reserve selection among the models. Although similarity in identification of conservation reserve networks occurred among models, models differed markedly in geographic scope and flexibility of reserve networks. It is essential for planners to evaluate the conservation implications of false-positive and false-negative errors for their specific management scenario before beginning the modeling process. Reserve networks selected by models that minimized false-positive errors provided a better match with priority areas identified by specialists. Thus, we urge caution in the use of models that overestimate species' occurrences because they may misdirect conservation action. Our approach further demonstrates the great potential value of museum records to biodiversity studies and the utility of species-distribution models to conservation decision-making. Our results also demonstrate, however, that these models must be applied critically and cautiously.     

Predicting Bird Species Distributions in Reconstructed Landscapes

Abstract:  Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box–ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40%). Model averaging produced more accurate predictions than "single best" models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995–1997) and validation (2004–2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km² region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.     

Predicting Invasiveness of Plant Species Based on Biological Information

Abstract: Previous studies suggest that, within particular groups of plant species, biological attributes can be used to predict the potential invasiveness of species that are intentionally introduced for horticultural or agricultural purposes. We examined the broad question of whether commonly available biological information can predict the invasiveness of a wide range of intentionally and accidentally introduced species. We collected information from published floras on 165 pairs of plant species. In each pair, one species originated in Europe and successfully invaded New Brunswick, Canada, and the other was a congeneric species that has not invaded North America. Only three biological characters—lifeform, stem height, and flowering period—and European geographic range were known for all species. We conducted multiple logistic regression analyses using two-thirds (110) of the species pairs and tested the predictive ability of resulting models using the remaining 55 pairs. Although a significant logistic regression model was obtained using the biological attributes, the model could not predict invasiveness of the test species pairs. In contrast, a model using only European range successfully predicted invasiveness in 70% of the test species. The importance of geographic range suggests that prediction of invasiveness on a species-by-species basis is not likely to help stem the flow of accidentally introduced invasive species. Species that are inadvertently picked up and moved to a new location due to their wide distribution are the same species that are likely to succeed in a new environment due to their wide environmental tolerances.     

Climate change and the cost of conserving species in Madagascar

We examined the cost of conserving species as climate changes. We used a Maxent species distribution model to predict the ranges from 2000 to 2080 of 74 plant species endemic to the forests of Madagascar under 3 climate scenarios. We set a conservation target of achieving 10,000 ha of forest cover for each species and calculated the cost of achieving this target under each scenario. We interviewed managers of projects to restore native forests and conducted a literature review to obtain the net present cost per hectare of management actions to maintain or establish forest cover. For each species, we added hectares of land from lowest to highest cost per additional year of forest cover until the conservation target was achieved throughout the time period. Climate change was predicted to reduce the size of species' ranges, the overlap between species' ranges and existing or planned protected areas, and the overlap between species' ranges and existing forest. As a result, climate change increased the cost of achieving the conservation target by necessitating successively more costly management actions: additional management within existing protected areas (US$0-60/ha); avoidance of forest degradation (i.e., loss of biomass) in community-managed areas ($160-576/ha); avoidance of deforestation in unprotected areas ($252-1069/ha); and establishment of forest on nonforested land within protected areas ($802-2710/ha), in community-managed areas ($962-3226/ha), and in unprotected areas ($1054-3719/ha). Our results suggest that although forest restoration may be required for the conservation of some species as climate changes, it is more cost-effective to maintain existing forest wherever possible.     

Aquatic plant community invasibility and scale-dependent patterns in native and invasive species richness

Invasive species richness often is negatively correlated with native species richness at the small spatial scale of sampling plots, but positively correlated in larger areas. The pattern at small scales has been interpreted as evidence that native plants can competitively exclude invasive species. Large-scale patterns have been understood to result from environmental heterogeneity, among other causes. We investigated species richness patterns among submerged and floating-leaved aquatic plants (87 native species and eight invasives) in 103 temperate lakes in Connecticut (northeastern USA) and found neither a consistently negative relationship at small (3-m2) scales, nor a positive relationship at large scales. Native species richness at sampling locations was uncorrelated with invasive species richness in 37 of the 60 lakes where invasive plants occurred; richness was negatively correlated in 16 lakes and positively correlated in seven. No correlation between native and invasive species richness was found at larger spatial scales (whole lakes and counties). Increases in richness with area were uncorrelated with abiotic heterogeneity. Logistic regression showed that the probability of occurrence of five invasive species increased in sampling locations (3 m2, n = 2980 samples) where native plants occurred, indicating that native plant species richness provided no resistance against invasion. However, the probability of three invasive species' occurrence declined as native plant density increased, indicating that density, if not species richness, provided some resistance with these species. Density had no effect on occurrence of three other invasive species. Based on these results, native species may resist invasion at small spatial scales only in communities where density is high (i.e., in communities where competition among individuals contributes to community structure). Most hydrophyte communities, however, appear to be maintained in a nonequilibrial condition by stress and/or disturbance. Therefore, most aquatic plant communities in temperate lakes are likely to be vulnerable to invasion.