Although New Zealand's 2020 biodiversity strategy, Te Mana o Te Taiao, places a high priority on protecting indigenous ecosystems, it provides minimal detail on how this will be accomplished. Using spatial data and a conservation prioritisation tool we demonstrate the implementation of a comprehensive framework for the systematic conservation of New Zealand's terrestrial ecosystems, as proposed in a pioneering paper by Kelly (1980). Working within the Horizons Region (Manawatu-Whanganui, lower North Island), we analyse the extent of losses of 65 terrestrial ecosystems since human settlement by combining maps of their potential distribution and current land cover. Two-thirds of the original indigenous cover has been lost, with lowland ecosystems suffering greatest losses; much surviving cover is substantially modified. Our prioritisation analyses identify various options for siting conservation management to maintain the integrity of a full range of indigenous ecosystems in a highly modified landscape, given varying degrees of constraint on the availability of land for conservation. Restricting management to DOC-administered land would severely constrain ecosystem representation, but dramatic improvements in ecosystem representation would result from protecting and managing a relatively small number of sites on land of other tenures, mostly at lower elevations. Results such as these could play a crucial role in supporting achievement of New Zealand's high-level goals for ecosystem conservation and meeting international conservation obligations. They could be used to (1) assess the conservation status of individual terrestrial ecosystems, (2) develop national and regional policies specifically targeting protection of at-risk ecosystems, (3) design and implement strategies that explicitly target management across a full range of ecosystems, (4) support processes designed to coordinate management among different conservation actors, and (5) inform individual landowners of the conservation value of indigenous ecosystems on their land. Obstacles to implementing such an approach include a range of technical, institutional, and social factors.

We review the recent rise to prominence in Aotearoa New Zealand of predation-focused conservation management, critically assessing the likelihood that this will deliver outcomes consistent with national biodiversity goals.Using a review of literature describing the impacts and control of three groups of introduced mammals (wild ungulates, brushtail possums, and predators), we identify shifts in management emphasis over a century of conservation decision-making in Aotearoa.Predators are now a major focus and wild ungulates are left largely uncontrolled, despite increasing populations and evidence for their negative impacts on a wide range of indigenous species and ecosystems.This imbalance in management effort, which appears to be influenced increasingly by socio-political pressures, is much less likely to deliver outcomes consistent with Aotearoa's biodiversity goals than a systematic approach that addresses a full range of biodiversity threats.Overall, we interpret these shortcomings as reflecting long recognised issues with the governance and leadership of Aotearoa's biodiversity system.Changes are required to provide adequate, stable funding, improve clarity around goals, leadership, responsibilities and accountabilities, strengthen planning and prioritisation of management actions, and coordinate management among various conservation actors.We also argue for (1) a stronger role for ecological sciences through independent research aimed at strengthening the evidence base for management actions, and (2) explicit inclusion of science expertise in conservation policy development and management decision making.While recent extensive, landscape-scale predator control has caught the imagination of many and has undoubtedly delivered some gains for a small subset of indigenous species, it also risks creating a false sense of achievement that diverts attention away from other serious gaps in progress towards achieving national biodiversity goals.We make 12 recommendations to address these shortcomings.

Habitat modification and introduced mammalian predators are linked to global species extinctions and declines, but their relative influences can be uncertain, often making conservation management difficult. Using landscape-scale models, we quantified the relative impacts of habitat modification and mammalian predation on the range contraction of a threatened New Zealand riverine duck. We combined 38 years of whio (Hymenolaimus malacorhynchos) observations with national-scale environmental data to predict relative likelihood of occurrence (RLO) under two scenarios using bootstrapped boosted regression trees (BRT). Our models used training data from contemporary environments to predict the potential contemporary whio distribution across New Zealand riverscapes in the absence of introduced mammalian predators. Then, using estimates of environments prior to human arrival, we used the same models to hindcast potential pre-human whio distribution prior to widespread land clearance. Comparing RLO differences between potential pre-human, potential contemporary and observed contemporary distributions allowed us to assess the relative impacts of the two main drivers of decline; habitat modification and mammalian predation. Whio have undergone widespread catastrophic declines most likely linked to mammalian predation, with smaller declines due to habitat modification (range contractions of 95% and 37%, respectively). We also identified areas of potential contemporary habitat outside their current range that would be suitable for whio conservation if mammalian predator control could be implemented. Our approach presents a practical technique for estimating the relative importance of global change drivers in species declines and extinctions, as well as providing valuable information to improve conservation planning.

To support ongoing marine spatial planning in New Zealand, a numerical environmental classification using Gradient Forest models was developed using a broad suite of biotic and high-resolution environmental predictor variables. Gradient Forest modeling uses species distribution data to control the selection, weighting and transformation of environmental predictors to maximise their correlation with species compositional turnover. A total of 630,997 records (39,766 unique locations) of 1,716 taxa living on or near the seafloor were used to inform the transformation of 20 gridded environmental variables to represent spatial patterns of compositional turnover in four biotic groups and the overall seafloor community. Compositional turnover of the overall community was classified using a hierarchical procedure to define groups at different levels of classification detail. The 75-group level classification was assessed as representing the highest number of groups that captured the majority of the variation across the New Zealand marine environment. We refer to this classification as the New Zealand “Seafloor Community Classification” (SCC). Associated uncertainty estimates of compositional turnover for each of the biotic groups and overall community were also produced, and an added measure of uncertainty – coverage of the environmental space – was developed to further highlight geographic areas where predictions may be less certain owing to low sampling effort. Environmental differences among the deep-water New Zealand SCC groups were relatively muted, but greater environmental differences were evident among groups at intermediate depths in line with well-defined oceanographic patterns observed in New Zealand’s oceans. Environmental differences became even more pronounced at shallow depths, where variation in more localised environmental conditions such as productivity, seafloor topography, seabed disturbance and tidal currents were important differentiating factors. Environmental similarities in New Zealand SCC groups were mirrored by their biological compositions. The New Zealand SCC is a significant advance on previous numerical classifications and includes a substantially wider range of biological and environmental data than has been attempted previously. The classification is critically appraised and considerations for use in spatial management are discussed.

Environmental variation is a crucial driver of ecological pattern, and spatial layers representing this variation are key to understanding and predicting important ecosystem distributions and processes. A national, standardised collection of different environmental gradients has the potential to support a variety of large-scale research questions, but to date these data sets have been limited and difficult to obtain. Here we describe the New Zealand Environmental Data Stack (NZEnvDS), a comprehensive set of 72 environmental layers quantifying spatial patterns of climate, soil, topography and terrain, as well as geographical distance at 100 m resolution, covering New Zealand’s three main islands and surrounding inshore islands. NZEnvDS includes layers from the Land Environments of New Zealand (LENZ), additional layers generated for LENZ but never publicly released, and several additional layers generated more recently. We also include an analysis of correlation between variables. All final NZEnvDS layers, their original source layers, and the R-code used to generate them are available publicly for download at https://doi.org/10.7931/m6rm-vz40.

Spatial classifications of the environment have previously been used to characterise biodiversity and to facilitate management planning at large spatial scales. Such classifications are more likely to be adopted if they can demonstrate integration of real patterns in habitats or biotic assemblages, in addition to environment. A previous classification used Gradient Forest analysis to derive 30 classes based on demersal fish assemblage patterns and environmental gradients. Here we provide a detailed description of the similarities and differences in the environment and fish assemblages of classes resulting from an updated classification using the same methodology. Environmental differences were associated with varying levels of differences in the distributions of fish species. At broad spatial scales, assemblages are differentiated primarily according to oceanographic conditions such as temperature and depth; at finer scales, patterns in species assemblages are more closely associated with more localised environmental conditions such as productivity, sea-surface temperature gradients and tidal currents. The 30-group classification allows complex biodiversity information to be summarised in ways accessible to stakeholder and environmental managers. Given the hierarchical nature of the classification, there is considerable scope to use a larger number of groups for applications at regional to local scales.

Although the freshwater environments of New Zealand once comprised an extensive interconnected network of rivers, lakes, and wetlands, their extent, condition, and connectivity have been reduced since human settlement, with consequent impacts on ecosystem functioning and the species that reside within them. An imbalance in the protection of freshwater ecosystems, with significant under-representation of lowland freshwater ecosystems, makes these the most threatened ecosystems in New Zealand. Recent policy initiatives are attempting to take a whole-catchment view, i.e. 'from the mountains to the sea'. There is also an increased focus on the restoration of vulnerable water bodies that still support moderate values, in preference to previous long-term restoration programmes for the most degraded freshwater sites. The outcomes of these programmes have been less certain, with opportunities lost for systems that are declining in condition but have not yet reached the threshold of degradation for investment. This work demonstrates the gains that can be made through the use of spatial conservation prioritization software to identify priority catchments for freshwater restoration, emphasizing the representation of a full range of ecosystems and species, while also taking account of longitudinal-connectivity constraints within catchments. Third-order subcatchments were the most suitable scale for this prioritization, to capture the most important components within the largest river catchments. Populations of important native fish populations and the locations of major terrestrial conservation projects were also considered when assessing priorities; iteratively chosen weightings were applied to control the balance of representation across these different features. Consideration was also given to existing patterns of protection, in order to assess the biodiversity representation within areas currently protected and to identify sites that would provide maximum additional benefits if restored or protected. The resulting subcatchment prioritizations have contributed strongly to regional collaborative restoration processes.

Aim: Producing quantitative descriptions of large-scale biodiversity patterns is challenging, particularly where biological sampling is sparse or inadequate. This issue is particularly problematic in marine environments, where sampling is both difficult and expensive, often resulting in patchy and/or uneven coverage. Here, we evaluate the ability of Gradient Forest (GF) modelling to describe broad-scale marine biodiversity patterns, using a large dataset that also provided opportunity to investigate the effects of sample size on model stability. Location: New Zealand's Extended Continental Shelf to depths of 2,000 m. Methods: GF models were used to analyse and predict spatial patterns of demersal fish species turnover (beta diversity) using an extensive demersal fish dataset (>27,000 research trawls) and high-resolution environmental data layers (1 km(2) grid resolution). GF models were fitted using various sized, mutually exclusive subsets of the demersal fish data to explore the effect of variation in numbers of training observations on model performance and stability. A final GF model using 13,917 samples was used to transform the environmental layers, which were then classified to produce 30 spatial groups; the ability of these groups to identify fish samples with similar composition was evaluated using independent sample data. Results: Model fitting using varying sized subsets of the data indicated only minimal changes in model outcomes when using >7,000 observations. A multiscale spatial classification of marine environments created using results from a final GF model fitted using similar to 14,000 samples was highly effective at summarizing spatial variation in both fish assemblage composition and species turnover. Main conclusions: The hierarchical nature of the classification supports its use at varying levels of classification detail, which is advantageous for conservation planning at differing spatial scales. This approach also facilitates the incorporation of information on intergroup similarities into conservation planning, allowing greater protection of distinctive groups likely to support unusual assemblages of species.

Predictions of invasion risk for seven non-indigenous fish species, ecological impact scores for individual species, and lake conservation rankings were linked to develop Invasion Risk Impact (IRI) and Lake Vulnerability (LV) indices that help identify New Zealand lakes most at risk of loss of conservation value from potential multi-species invasions. Species-specific IRI scores (the product of predicted invasion risk and species impact) highlighted Eurasian perch (Perca fluviatilis) and the brown bullhead (Ameiurus nebulosus), as the species most likely to spread and cause ecological harm in lakes. For 3431 lakes >1 ha throughout New Zealand, total IRI tended to be highest for lowland riverine and dune lakes most of which are already colonized by multiple invasive fish species. The LV index indicated that lakes most at risk of loss of conservation value from invasive fish impacts were predominantly (i) in the northern half of the North Island where several uncommon lake types occur, and (ii) along the west coast of the South Island where conservation value is often greater, largely because of low catchment modification. The IRI and LV indices can be used to assist with setting priorities for surveillance monitoring, advocacy, and response planning targeted at preventing the establishment of invasive fish in moderate-to-high value lakes most susceptible to ecological impacts. Both indices can be adapted to accommodate alternative impact and conservation scoring systems, providing a flexible tool for local- and national-scale assessments of lake vulnerability to fish invasion impacts. Copyright © 2016 John Wiley & Sons, Ltd.

Several international agreements and conventions require nations to establish Marine Protected Area (MPA) networks as an approach to alleviating biodiversity declines; however, a common problem in planning MPA networks is how to balance conservation objectives against economic objectives. Here, using the distributions of 102 biodiversity features and 7 extractive uses we trial the systematic conservation planning software Zonation as a decision-support tool to facilitate progress towards New Zealand's commitment to establishing a representative network of MPAs while providing for economic development. Our results indicate that: (i) New Zealand's existing MPAs provide on average 70% less representation of the input biodiversity features than would be achieved by an MPA network of equivalent area designed from the outset using Zonation; (ii) small increases in the geographic extent of existing protection results in rapid increases in representation of the selected biodiversity features when systematic conservation planning software is used to inform expansion of existing protection; and (iii) the impacts on existing resource users of an expanded MPA system can be minimized by using Zonation to identify areas that increase biodiversity representation, while avoiding areas where existing uses may be incompatible with marine protection. These results demonstrate the utility of systematic conservation planning software as a decision-support tool within a broader social process for MPA network design and implementation. The iterative application of tools such as Zonation during participatory processes that balance alternative uses could potentially lead to more informed, efficient and socially enduring outcomes that enhance the ability to establish representative MPA networks.

Summary The ability to predict invasive species spread is essential for effective biosecurity management and the allocation of scarce monitoring resources. Prevention of invasive fish incursions poses a significant challenge because of the wide physiological tolerances of many species, their mobility and the role that human vectors play in their spread. In New Zealand, seven introduced fish species are distributed to varying extents in lakes across the two main islands. We used field survey data from 470 New Zealand lakes to fit statistical models of the current geographic distributions of seven introduced species; the resulting models were then used to predict risks of future establishment of each species in 3595 New Zealand lakes >1 ha. Initial models fitted using lake‐ and catchment‐scale environmental predictors identified summer temperature among the top two most influential variables, with lake density and size also important for some species. Distribution models for Eurasian perch (Perca fluviatilis), rudd (Scardinius erythrophthalmus) and tench (Tinca tinca) were substantially improved by the addition of variables describing human population densities and lake accessibility. All seven species occurred most frequently in lakes close to human population centres suggesting that human‐mediated dispersal has played at least some role in determining current distributions. Addition of a spatial variable, representing the presence or absence of the modelled species within the broader catchment within which each lake is located, improved the predictive performance of models for the brown bullhead catfish (Ameiurus nebulosus), perch and rudd. This finding indicates that the current distributions of these species include clusters of lakes within ‘occupied’ catchments, resulting in geographic patchiness that is independent of the available environmental and human population predictors. This distribution has most likely resulted from spread into accessible and suitable lakes from one or more initial liberation points, either by natural dispersal along waterways or through human‐assisted movement. Predictions to all mapped lakes throughout New Zealand indicate (i) that the potential for future spread is greatest for catfish, perch and rudd and (ii) the high vulnerability to invasion for lakes along the east coast of both islands and in inland montane regions of the South Island. Our results allow for improved identification of lakes likely to be suitable for invasive fish species and which should therefore be accorded priority for surveillance; they highlight in particular the potential for perch and catfish to establish in higher‐elevation lakes distant from human population centres.

ABSTRACTResponses of macroinvertebrate communities to human pressure are poorly known in large rivers compared with wadeable streams, in part because of variable substrate composition and the need to disentangle pressure responses from underlying natural environmental variation. To investigate the interaction between these factors, we sampled macroinvertebrates from the following: (i) submerged wood; (ii) littoral substrates < 0.8 m deep; and (iii) inorganic substrates in deep water (> 1.5 m) benthic habitats in eleven 6th‐ or 7th‐order New Zealand rivers spanning a catchment vegetation land cover gradient. Cluster analysis identified primary site groupings reflecting regional environmental characteristics and secondary groupings for moderate gradient rivers reflecting the extent of catchment native vegetation cover. Low pressure sites with high levels of native vegetation had higher habitat quality and higher percentages of several Ephemeroptera and Trichoptera taxa than sites in developed catchments, whereas developed sites were more typically dominated by Diptera, Mollusca and other Trichoptera. Partial regression analysis indicated that the combination of underlying environment and human pressure accounted for 77–89% of the variation in Ephemeroptera, Trichoptera and Plecoptera taxa richness, %Diptera and %Mollusca, with human pressure explaining more variance than underlying environment for %Mollusca. Analysis of replicate deepwater and littoral samples from moderate gradient sites at the upper and lower ends of the pressure gradient indicated that total Trichoptera and Diptera richness and %Diptera responded to land use differences in these boatable river catchments. Responses to human pressure were substrate specific with the combination of littoral and deepwater substrates providing the most consistent response and yielding the highest number of taxa. These results indicate that multiple substrate sampling is required to document the biodiversity and condition of boatable river macroinvertebrate communities and that spatial variation in the underlying natural environment needs to be accounted for when interpreting pressure–response relationships. Copyright © 2012 John Wiley & Sons, Ltd.

Summary1. Modification of natural landscapes and land‐use intensification are global phenomena that can result in a range of differing pressures on lotic ecosystems. We analysed national‐scale databases to quantify the relationship between three land uses (indigenous vegetation, urbanisation and agriculture) and indicators of stream ecological integrity. Boosted regression tree modelling was used to test the response of 14 indicators belonging to four groups – water quality (at 578 sites), benthic invertebrates (at 2666 sites), fish (at 6858 sites) and ecosystem processes (at 156 sites). Our aims were to characterise the ecological response curves of selected functional and structural metrics in relation to three land uses, examine the environmental moderators of these relationships and quantify the relative utility of metrics as indicators of stream ecological integrity.2. The strongest indicators of land‐use effects were nitrate + nitrite, delta‐15 nitrogen value (δ15N) of primary consumers and the Macroinvertebrate Community Index (a biotic index of organic pollution), while the weakest overall indicators were gross primary productivity, benthic invertebrate richness and fish richness. All indicators declined in response to removal of indigenous vegetation and urbanisation, while variable responses to agricultural intensity were observed for some indicators.3. The response curves for several indicators suggested distinct thresholds in response to urbanisation and agriculture, specifically at 10% impervious cover and at 0.1 g m−3 nitrogen concentration, respectively.4. Water quality and ecosystem process indicators were influenced by a combination of temperature, slope and flow variables, whereas for macroinvertebrate indicators, catchment rainfall, segment slope and temperature were significant environmental predictor variables. Downstream variables (e.g. distance to the coast) were significant in explaining residual variation in fish indicators, not surprisingly given the preponderance of diadromous fish species in New Zealand waterways. The inclusion of continuous environmental variables used to develop a stream typology improved model performance more than the inclusion of stream type alone.5. Our results reaffirm the importance of accounting for underlying spatial variation in the environment when quantifying relationships between land use and the ecological integrity of streams. Of distinctive interest, however, were the contrasting and complementary responses of different indicators of stream integrity to land use, suggesting that multiple indicators are required to identify land‐use impact thresholds, develop environmental standards and assign ecological scores for reporting purposes.

Summary1. Models predicting invasive macrophyte spread between lakes provide an important tool for focusing proactive management efforts to lakes deemed susceptible to invasion. However, challenges to forecasting macrophyte spread include wide physiological tolerances of invasive macrophytes and a lack of information on the relative importance of the various human vectors (e.g. boating traffic). In New Zealand, three invasive species that reproduce vegetatively, Ceratophyllum demersum, Lagarosiphon major, Egeria densa, and a single species that reproduces sexually, Utricularia gibba, are currently spreading across the lake landscape at a great cost to the local ecology and economy.2. In this study, we first examined whether variables that indirectly describe weed spread via human access and use, as well as a lake’s position in the landscape, could describe the distribution of these four species using a boosted regression trees (BRT) modelling approach. Then, as these invasive species have not reached their full invasion potential, we examined how giving more influence to infected lakes at the edge of the invasion front, and including all lakes across New Zealand as background samples, simulating ‘absences beyond the invasion front’, influenced our ability to forecast the potential for new lakes to be invaded.3. The BRT models identified that variables characterising human access and use, as well as lake position, were associated with the occurrence of the three vegetatively reproducing macrophytes. Weed occurrence was more likely when there was a highway in the vicinity, human population density was high and if the lake was large (c. 55 km2). But in the single case of U. gibba, temperature was the variable that best explained occurrence. This is consistent with the suggestion that U. gibba is predominantly dispersed by waterbirds, rather than human activity.4. But for all four species, the BRT models based on the recorded observations alone predicted observed invasions with low prediction probabilities and did not forecast further spread. By contrast, when observations at the edge of the invasion front were upweighted, and additional background lakes implemented into the model, recorded observations were predicted and additional lakes were forecast to be at risk, suggesting that these models better captured the current and potential distribution of these macrophyte species.5. The use of variables that characterise weed spread could provide similar insights into other systems where survey information on the nature, strength and direction of invasion vectors is lacking. Furthermore, when weighting the data, many lakes across New Zealand were forecasted to be at risk of invasion. The advantage of weighing the presence data was that insights into the potential for a species to spread were obtained. The probabilistic estimates of risk, as derived from the models, together with other information for prioritising lakes, can be used to focus surveillance and protection efforts.

We develop a high-resolution conservation prioritization analysis for New Zealand's rivers and streams that simultaneously consider both the present state (representation) of ecosystems, and the prioritization of management actions designed to mitigate ongoing human impacts on their expected future state (retention). As input we used information about the geographic distributions of river ecosystem groups and their compositional similarity, species richness, present condition as compared to their estimated pristine state, and upstream and downstream connectivity. Candidate management actions included riparian planting, establishment of wetlands on tile-drain outflows, and use of riparian buffer strips in plantation forests. The analysis, carried out at a 1-ha resolution for a study area of 22,000 km(2) in Southland, New Zealand, demonstrates a credible range of options for management intervention, particularly in lowland streams under serious threat from agricultural intensification. The proposed analysis can be replicated elsewhere for terrestrial, freshwater, or marine systems using publicly available software.

If temperature increases occur during the next century as predicted by climatologists, then major changes in New Zealand's natural and plantation forests can be expected. Current relationships between temperature and occurrence of natural forest species suggest major changes in forest pattern with an increase in temperature. Because of widely varying relationships between species and climate, changes will likely occur at a species, rather than at a community level. Initial changes should favour species with wide tolerance to climatic factors, good dispersal capacity, and short generation times. Shifts in distribution will be influenced by the availability of sites for colonisation, i.e., they will depend on mortality of the current site occupants. Disruption in forest composition is most likely to occur in forest patches where there is little potential for dispersal of new, more suitable species. This could result from a narrow, within-patch temperature range, geographic isolation from other patches which might act as seed sources, or dependence on longer-distance latitudinal rather than shorter-distance altitudinal migration. The plantation estate across the country can be classified in relation to present-day temperature and rainfall regimes. The mean annual temperature is between 10° and 15°C for 90%, and between 10° and 11°C for 35% of the plantation area. Mean annual rainfall is between 1250 and 2250 mm for 75% of the plantation area. If the worst-case climate change scenario is realised, then 96% of the plantation area will experience mean annual temperatures above 13°C. Twenty-one percent of the plantation area will experience mean annual temperatures above 17°C which is near the top of the optimal temperature range for growth of Pinus radiata D.Don, and warmer than any current values in the present climate. The effect of this on timber yield and log quality is still uncertain. Recommendations for future research include an extension of the current analysis to a national scale for natural forests, and an urgent need for process studies to investigate the effects of climate variables, particularly temperature and carbon dioxide, on the physiological response of all forest species. This is required as a basis for further modelling of the long-term ecological effects.

Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use.” Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty. 677 A nn u. R ev . E co l. Ev ol . S ys t. 20 09 .4 0: 67 769 7. D ow nl oa de d fro m a rjo ur na ls. an nu al re vi ew s.o rg by D ire ct or at e O f F ish er ie s o n 01 /1 5/ 10 . F or p er so na l u se o nl y. ANRV393-ES40-32 ARI 8 October 2009 12:26