Extent Of Habitat Research Articles

Where and why are species' range shifts hampered by unsuitable landscapes?

There is widespread concern that species will fail to track climate change if habitat is too scarce or insufficiently connected. Targeted restoration has been advocated to help species adapt, and a “conductance” metric has been proposed, based on simulation studies, to predict effective habitat configurations. However, until now there is very little empirical evidence on how the configuration of habitat is affecting expansion at species' cool range margins. We analysed the colonisation events that have occurred in continuously monitored trap locations for 54 species of southerly distributed moths in Britain between 1985 and 2011. We tested whether the time until colonisation was affected by attributes of each species, and of intervening landcover and climate between the trap and the baseline distribution (1965–1985). For woodland species, the time until colonisation of new locations was predicted by the “conductance” of woodland habitat, and this relationship was general, regardless of species' exact dispersal distances and habitat needs. This shows that contemporary range shifts are being influenced by habitat configuration as well as simple habitat extent. For species associated with farmland or suburban habitats, colonisation was significantly slower through landscapes with a high variance in elevation and/or temperature. Therefore, it is not safe to assume that such relatively tolerant species face no geographical barriers to range expansion. We thus elucidate how species' attributes interact with landscape characteristics to create highly heterogeneous patterns of shifting at cool range margins. Conductance, and other predictors of range shifts, can provide a foundation for developing coherent conservation strategies to manage range shifts for entire communities.

Inclusion of condition in natural capital assessments is critical to the implementation of marine nature-based solutions

Current approaches to measure ecosystem services (ES) within natural capital (NC) and nature-based solutions (NbS) assessments are generally coarse, often using a single figure for ecosystem services (e.g., nutrient remediation or blue carbon sequestration) applied to the local or national habitat stock, which fails to take account of local ecosystem conditions and regional variability. As such, there is a need for improved understanding of the link between habitat condition and ES provision, using comparable indicators in order to take more informed management decisions. Here the UK, Solent Marine Sites (SEMS) is used as a case study system to demonstrate how Water Framework Directive (WFD) ‘ecological status’ and other indicators of ecosystem condition (state or quality) can be coupled with habitat extent information to deliver a more precise locally-tailored NC approach for active coastal and marine habitat restoration. Habitat extent and condition data are collected for seven NbS relevant coastal habitats (littoral sediment, mat-forming green macroalgae, subtidal sediment, saltmarsh, seagrass, reedbeds and native oyster beds). The workflow includes: 1) biophysical assessment of regulatory ES; 2) monetary valuation; and 3) compilation of future scenarios of habitat restoration and creation. The results indicate that incorporating classifications by condition indices into local NC extent accounts improved ES benefits by 11–67%. This suggests that omitting condition from NC assessments could lead to undervaluation of ES benefits. Future scenarios of restoration in the SEMS also show that the additional regulatory benefits of reaching ‘Good’ ecological status are £376 million annually, but could be as much as £1.218 billion if ‘High‘status and all habitat creation targets were met. This evidence of the potential value of restoration and importance of including condition indices in assessments is highly relevant to consider when investing in water ecosystems conservation and restoration as called for by the UN Decade on Ecosystem Restoration (2021−2030), and more generally in global nutrient neutrality and blue carbon policy strategies.

Habitat Protection Indexes - new monitoring measures for the conservation of coastal and marine habitats

A worldwide call to implement habitat protection aims to halt biodiversity loss. We constructed an open-source, standardized, and reproducible workflow that calculates two indexes to monitor the extent of coastal and marine habitats within protected areas and other effective area-based conservation measures. The Local Proportion of Habitats Protected Index (LPHPI) pinpoints the jurisdictions with the greatest opportunity to expand their protected or conserved areas, while the Global Proportion of Habitats Protected Index (GPHPI) showcases which jurisdictions contribute the most area to the protection of these habitats globally. We also evaluated which jurisdictions have the highest opportunity to contribute globally to protecting habitats by meeting a target of 30% coverage. We found that Areas Beyond National Jurisdiction (ABNJ) have the greatest potential to do so. Our workflow can also be easily extended to terrestrial and freshwater habitats. These indexes are helpful to monitor aspects of the Sustainable Development Goal 14 and the emerging post-2020 global biodiversity framework, to understand the current status of international cooperation on coastal and marine habitats conservation.

Global estimates of the extent and production of macroalgal forests

AbstractAimMacroalgal habitats are believed to be the most extensive and productive of all coastal vegetated ecosystems. In stark contrast to the growing attention on their contribution to carbon export and sequestration, understanding of their global extent and production is limited and these have remained poorly assessed for decades. Here we report a first data‐driven assessment of the global extent and production of macroalgal habitats based on modelled and observed distributions and net primary production (NPP) across habitat types.LocationGlobal coastal ocean.Time periodContemporary.Major taxa studiedMacroalgae.MethodsHere we apply a comprehensive niche model to generate an improved global map of potential macroalgal distribution, constrained by incident light on the seafloor and substrate type. We compiled areal net primary production (NPP) rates across macroalgal habitats from the literature and combined this with our estimates of the global extent of these habitats to calculate global macroalgal NPP.ResultsWe show that macroalgal forests are a major biome with a global area of 6.06–7.22 million km2, dominated by red algae, and NPP of 1.32 Pg C/year, dominated by brown algae.Main conclusionsThe global macroalgal biome is comparable, in area and NPP, to the Amazon forest, but is globally distributed as a thin strip around shorelines. Macroalgae are expanding in polar, subpolar and tropical areas, where their potential extent is also largest, likely increasing the overall contribution of algal forests to global carbon sequestration.

Continuing expansion of Narrow-leaved Cattail (<i>Typha angustifolia</i>) and decline of a provincially rare fen in the Holland Marsh, Ontario

At the time of European settlement, an extensive graminoid wetland existed at the confluence of the East and West Holland Rivers at the southern end of Lake Simcoe, Ontario. However, by 1925, clearing and draining of the marsh for specialty agriculture (i.e., market gardens) had begun and, by the 1940s, ~46% of the wetland had been cleared and another 13% was lost before 2016. Concurrent with marsh conversion has been an increase in Narrow-leaved Cattail (Typha angustifolia) in the remnant wetland. This study documents the change in the Holland Marsh wetland by delineating boundaries between marsh, fen, and shrub communities on aerial photographs taken at ~10-year intervals between 1946 and 2015 and documenting vegetation change along transects running perpendicular to tributaries bisecting the wetland. The extent of fen habitat within the Holland Marsh has been decreasing since 1946 at an average rate of 0.24 ha/year because of increases in both shrub and marsh (i.e., T. angustifolia) communities. Typha angustifolia expansion has been predominantly from along the margins of the Holland River where soil phosphorus concentration is significantly higher than in the core of the fen. Beyond 30 m from the river, vegetation dominance shifts from T. angustifolia to sedges (Cyperaceae). Managing phosphorus loading from upstream land uses will be of critical importance in protecting this habitat, which is rare in southern Ontario.

Global-Scale Environmental Niche and Habitat of Blue Shark (Prionace glauca) by Size and Sex: A Pivotal Step to Improving Stock Management

Blue shark (Prionace glauca) is amongst the most abundant shark species in international trade, however this highly migratory species has little effective management and the need for spatio-temporal strategies increases, possibly involving the most vulnerable stage or sex classes. We combined 265,595 blue shark observations (capture or satellite tag) with environmental data to present the first global-scale analysis of species’ habitat preferences for five size and sex classes (small juveniles, large juvenile males and females, adult males and females). We leveraged the understanding of blue shark biotic environmental associations to develop two indicators of foraging location: productivity fronts in mesotrophic areas and mesopelagic micronekton in oligotrophic environments. Temperature (at surface and mixed layer depth plus 100 m) and sea surface height anomaly were used to exclude unsuitable abiotic environments. To capture the horizontal and vertical extent of thermal habitat for the blue shark, we defined the temperature niche relative to both sea surface temperature (SST) and the temperature 100 m below the mixed layer depth (Tmld+100). We show that the lifetime foraging niche incorporates highly diverse biotic and abiotic conditions: the blue shark tends to shift from mesotrophic and temperate surface waters during juvenile stages to more oligotrophic and warm surface waters for adults. However, low productivity limits all classes of blue shark habitat in the tropical western North Atlantic, and both low productivity and warm temperatures limit habitat in most of the equatorial Indian Ocean (except for the adult males) and tropical eastern Pacific. Large females tend to have greater habitat overlap with small juveniles than large males, more defined by temperature than productivity preferences. In particular, large juvenile females tend to extend their range into higher latitudes than large males, likely due to greater tolerance to relatively cold waters. Large juvenile and adult females also seem to avoid areas with intermediate SST (~21.7-24.0°C), resulting in separation from large males mostly in the tropical and temperate latitudes in the cold and warm seasons, respectively. The habitat requirements of sensitive size- and sex-specific stages to blue shark population dynamics are essential in management to improve conservation of this near-threatened species.

Underwater Photographic Survey of Coastal Fish Community of Terra Nova Bay, Ross Sea

Although the extent of near-shore and coastal habitats around the Antarctic Continent is limited, they host an abundant and diversified fish fauna dominated by notothenioids. Nevertheless, the spatial distribution of fishes at small scales and their relationships with the surrounding habitat are still poorly known. The purpose of this study is to provide new insights on the inshore fish community of Terra Nova Bay, Ross Sea, which is now part of the largest marine protected area established so far in the Southern Ocean. As a low-impact and effective methodology of investigation, an underwater photographic survey was conducted through two remotely operated vehicle (ROV) transects set down to 300 m depth. The faunistic inventory consisted of twelve species of notothenioids, which complements previous data obtained by conventional samplings. The most abundant species exhibited wide depth distribution ranges, and they were generally associated with areas with a rich benthic macrofauna composed of alcyonaceans, sponges, bryozoans, polychaetes, and echinoderms. Nesting behavior was documented in two species, Trematomus bernacchii and Pagetopsis macropterus. The present data provide further evidence of the importance of inshore waters for the local fish community, representing a proper habitat for settling, foraging, and spawning activities.

Species composition, distribution and relative abundance of the inshore fish community off the Argentine Islands, Bellingshausen Sea

In the last three decades, several interdisciplinary studies investigated the marine ecosystems off the West Antarctic Peninsula (WAP), one of the most impacted areas of the Southern Ocean by the global warming. Although the extent of near-shore habitats along the WAP is wider than elsewhere in Antarctica, the coastal fish communities have been rarely studied. Complementing these previous studies, we provide new data on the species composition, population structure and relative abundance of the inshore fish community living off the Argentine Islands (Bellingshausen Sea). Fish samples were caught all the year round during four different periods spread over ten years (from 2006 to 2017). The fish fauna consisted of fourteen high-Antarctic and low-Antarctic species of notothenioids, most of them belonging to the Nototheniidae. Notothenia coriiceps was by far the most abundant species, followed in decreasing abundance by Chaenocephalus aceratus, Notothenia rossii, Trematomus newnesi and Trematomus bernacchii. Our findings provide context for future ecological studies as this area represents either a spawning and nursery area for multiple species in this study. More generally, the inshore waters off the Argentine Islands represent the southern limit of distribution for several low-Antarctic species, and our results provide critical baseline data for assessing possible disruptions in population dynamics driven by the ongoing climate change.

Spatial Shifts in Species Richness in Response to Climate and Environmental Change: An Adaption of the EUROMOVE Model in the Czech Republic

Climate change has greatly altered plant habitats, resulting in greater biodiversity loss at different scales. Therefore, it is important to quantify such changes for better monitoring and conservation. In this study, we adapt the EUROMOVE model and its mean stable area indicator (MSAi) to the conditions in the Czech Republic. Our objective was to predict change in species richness from a representative pool of 687 species from 1990 to 2100 under the RCP 8.5 climate scenario, focusing on the current period (2018). Another objective was to assess the effectiveness of the MSAi as a tool for quantifying landscape vulnerability. Our result shows that species habitat expanded between 1990 and 2018, although about 2 per cent of species were lost. The average MSAi of the most favourable highland habitats may decrease from 0.85 to 0.65 by 2100 as >20% of baseline species may be lost. Indicator species of Alnus (alder) and Festuca (fescue), typical of lowland habitats, are among the most vulnerable, already showing a net loss of their current habitat extent. The MSAi can be applied as a comprehensive tool to quantify the impact of climate change on landscape vulnerability as more survey data becomes available.

Stakeholder perspectives on nature, people and sustainability at Mount Kilimanjaro

Abstract Effective approaches towards sustainability need to be informed by a diverse array of stakeholder perspectives. However, capturing these perspectives in a way that can be integrated with other forms of knowledge can represent a challenge. Here we present the first application of the conceptual framework of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services (IPBES) to a participatory assessment of local perspectives on nature, people and sustainability on Mount Kilimanjaro, Tanzania. This assessment was organized in the form of a participatory workshop with five different groups of stakeholders. Following this framework, we assembled information on the state of and trends in species diversity, Nature's Contributions to People (NCP), and on the main drivers of changes in species and habitats. Additionally, we gathered perspectives on the needs and opportunities for the sustainable management and conservation of natural resources from the individual to the international level. The various stakeholders agreed that both the condition and extent of the various habitats and NCP are declining. In line with available knowledge, the key direct drivers of change mentioned by the workshop participants were land use and climate change, whereas human population growth was singled out as the most important indirect driver. The most frequently suggested measures to address the observed decline in species diversity and its drivers were related to land and water management and to education and awareness raising. Yet, the stakeholder groups differed in the measures they suggested. The willingness of a diversity of knowledge holders to systematically engage in a structured discussion around all the elements of the IPBES framework provides support for its applicability in participatory workshops aimed at capturing nuanced and context‐based perspectives on social–ecological systems from informed stakeholders. The application of the IPBES framework enabled the comparability needed for developing narratives of stakeholder visions that can help identify new pathways towards sustainability and guide planning while retaining the context‐based nuances that remain unresolved with non‐participatory methods. Read the free Plain Language Summary for this article on the Journal blog.

Arctic marine forest distribution models showcase potentially severe habitat losses for cryophilic species under climate change.

The Arctic is among the fastest‐warming areas of the globe. Understanding the impact of climate change on foundational Arctic marine species is needed to provide insight on ecological resilience at high latitudes. Marine forests, the underwater seascapes formed by seaweeds, are predicted to expand their ranges further north in the Arctic in a warmer climate. Here, we investigated whether northern habitat gains will compensate for losses at the southern range edge by modelling marine forest distributions according to three distribution categories: cryophilic (species restricted to the Arctic environment), cryotolerant (species with broad environmental preferences inclusive but not limited to the Arctic environment), and cryophobic (species restricted to temperate conditions) marine forests. Using stacked MaxEnt models, we predicted the current extent of suitable habitat for contemporary and future marine forests under Representative Concentration Pathway Scenarios of increasing emissions (2.6, 4.5, 6.0, and 8.5). Our analyses indicate that cryophilic marine forests are already ubiquitous in the north, and thus cannot expand their range under climate change, resulting in an overall loss of habitat due to severe southern range contractions. The extent of marine forests within the Arctic basin, however, is predicted to remain largely stable under climate change with notable exceptions in some areas, particularly in the Canadian Archipelago. Succession may occur where cryophilic and cryotolerant species are extirpated at their southern range edge, resulting in ecosystem shifts towards temperate regimes at mid to high latitudes, though many aspects of these shifts, such as total biomass and depth range, remain to be field validated. Our results provide the first global synthesis of predicted changes to pan‐Arctic coastal marine forest ecosystems under climate change and suggest ecosystem transitions are unavoidable now for some areas.

Urban expansion and infrastructure development reduce habitat suitability for Asian elephants in southwestern China

AbstractConservation interventions for threatened species must be based on accurate assessments of the effects of anthropogenic pressures on habitat suitability. We used multiscale multivariable species‐distribution modeling to evaluate habitat suitability for an Asian elephant (Elephas maximus) population in Shangyong Reserve, Yunnan Province, southwestern China. We investigated the scales at which measurements of environmental variables best reflected elephant habitat selection, and examined whether these responses changed over 2 decades (2000–2010 and 2011–2020) in response to 20 environmental variables, including 14 variables reflecting landscape fragmentation, the extent of buildings, and transport infrastructure. Elephant presence was sensitive to the scale of each variable, and the effects differed among variables within and between decades. More than half of the variables influenced elephant presence at coarse scales of 8 or 16 km, including 12 variables reflecting anthropogenic pressures in 2000–2010 and 10 in 2011–2020. Overall, multivariate models with variables at their optimal scales had higher discrimination than models at uniformly fine scales of 1 km or 2 km. The extent of suitable habitat for elephants declined by 24% over 2 decades. Less than half of elephant habitat was located within Shangyong Reserve (49% in 2000–2010, 40% in 2011–2020), indicating the importance of managing suitable habitat beyond reserve boundaries. Roads and buildings reduced the probability of elephant presence, with effects that extended beyond their immediate footprint. We advocate that infrastructure be planned with buffers, ≥8 km wide, between roads or buildings and core elephant habitat. Multiscale multivariable species‐distribution modeling should be employed to ensure that all suitable habitat for the remaining fragmented elephant populations in Yunnan is identified, mapped, and protected.

Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting US imperiled species.

Continental‐ and regional‐scale assessments of gaps in protected area networks typically use relatively coarse range maps for well documented species groups, creating uncertainty about the fate of unexamined biodiversity and providing insufficient guidance for land managers. By building habitat suitability models for a taxonomically diverse group of 2216 imperiled plants and animals, we revealed comprehensive and detailed protection opportunities in the conterminous United States. Summing protection‐weighted range‐size rarity (PWRSR, the product of the percent of modeled habitat outside of protected areas and the inverse of modeled habitat extent) uncovered novel patterns of biodiversity importance. Concentrations of unprotected imperiled species in places such as the northern Sierra Nevada, central and northern Arizona, the Rocky Mountains of Utah and Colorado, southeastern Texas, southwestern Arkansas, and Florida's Lake Wales Ridge have rarely if ever been featured in continental‐ and regional‐scale analyses. Inclusion of diverse taxa (vertebrates, freshwater mussels, crayfishes, bumble bees, butterflies, skippers, and vascular plants) partially drove these new patterns. When analyses were restricted to groups typically included in previous studies (birds, mammals, and amphibians), up to 53% of imperiled species in other groups were left out. The finer resolution of modeled inputs (990 m) also resulted in a more geographically dispersed pattern. For example, 90% of the human population of the conterminous United States lives within 50 km of modeled habitat for one or more species with high PWRSR scores. Over one‐half of the habitat for 818 species occurs within federally lands managed for biodiversity protection; an additional 360 species have over one‐half of their modeled habitat on federal multiple use land. Freshwater animals occur in places with poorer landscape condition but with less exposure to climate change than other groups, suggesting that habitat restoration is an important conservation strategy for these species. The results provide fine‐scale, taxonomically diverse inputs for local and regional priority‐setting and show that although protection efforts are still widely needed on private lands, notable gains can be achieved by increasing protection status on selected federal lands.

Predicting habitat suitability and connectivity for management and conservation of urban wildlife: A real‐time web application for grassland water voles

Abstract Natural habitats in urban areas provide benefits for both humans and biodiversity. However, to achieve biodiversity gains, we require new techniques to determine habitat suitability and ecological connectivity that will inform urban planning and development. Using an example of an urban population of water voles Arvicola amphibius, we developed a habitat suitability model and a resistance‐surface‐based model of landscape connectivity to identify potential connectivity between areas of suitable habitat. We then updated the environmental variables according to new urban development plans and used our models to generate spatially explicit predictions of both habitat suitability and connectivity. To make models accessible to urban and conservation planners, we developed an interactive mapping tool that provided users with a graphical user interface (GUI) to inform conservation planning for this species. The model found that habitat suitability for water voles was related to the proportion and distance from key environmental variables, such as built‐up areas and urban green spaces, while the connectivity model identified important corridors connecting areas of potential distribution for this species. Future development plans altered the potential spatial distribution of the water vole population, reducing the extent of suitable habitat in some core areas. The interactive mapping tool made available suitable habitat and connectivity maps for conservation managers to assess new planning applications and for the development of a conservation action plan for water voles. Synthesis and applications. We believe this approach provides a framework for future development of nature conservation tools that can be used by planners to inform ecological decision‐making, increase biodiversity and reduce human–wildlife conflict in urban environments.

Species distribution models as a tool for early detection of the invasive Raphidiopsis raciborskii in European lakes

In freshwater habitats, invasive species and the increase of cyanobacterial blooms have been identified as a major cause of biodiversity loss. The invasive cyanobacteria Raphidiopsis raciborskii a toxin-producing and bloom-forming species affecting local biodiversity and ecosystem services is currently expanding its range across Europe. We used species distribution models (SDMs) and regional bioclimatic environmental variables, such as temperature and precipitation, to identify suitable areas for the colonization and survival of R. raciborskii, with special focus on the geographic extent of potential habitats in Northern Europe. SDMs predictions uncovered areas of high occurrence probability of R. raciborskii in locations where it has not been recorded yet, e.g. some areas in Central and Northern Europe. In the southeastern part of Sweden, areas of suitable climate for R. raciborskii corresponded with lakes of high concentrations of total phosphorus, increasing the risk of the species to thrive. To our knowledge, this is the first attempt to predict areas at high risk of R. raciborskii colonization in Europe. The results from this study suggest several areas across Europe that would need monitoring programs to determine if the species is present or not, to be able to prevent its potential colonization and population growth. Regarding an undesirable microorganism like R. raciborskii, authorities may need to start information campaigns to avoid or minimize the spread.

Combining multiscale niche modeling, landscape connectivity, and gap analysis to prioritize habitats for conservation of striped hyaena (Hyaena hyaena).

Identifying spatial gaps in conservation networks requires information on species-environment relationships, and prioritization of habitats and corridors. We combined multi-extent niche modeling, landscape connectivity, and gap analysis to investigate scale-dependent environmental relationships, and identify core habitats and corridors for a little-known carnivore in Iran, the striped hyaena (Hyaena hyaena). This species is threatened in Iran by road vehicle collisions and direct killing. Therefore, understanding the factors that affect its habitat suitability, spatial pattern of distribution, and connectivity among them are prerequisite steps to delineate strategies aiming at human-striped hyaena co-existence. The results showed that the highest predictive power and extent of habitats was obtained at the extent sizes of 4 and 2 km, respectively. Also, connectivity analysis revealed that the extent and number of core habitats and corridors changed with increasing dispersal distance, and approximately 21% of the landscape was found to support corridors. The results of gap analysis showed that 15–17% of the core habitats overlapped with conservation areas. Given the body size of the species, its mobility, and lack of significant habitat specialization we conclude that this species would be more strongly influenced by changes in habitat amount rather than landscape configuration. Our approach showed that the scale of variables and dispersal ability must be accounted for in conservation efforts to prioritize habitats and corridors, and designing conservation areas. Our results could facilitate the conservation of striped hyaena through the identification and prioritization of habitats, establishment of conservation areas, and mitigating conflicts in corridors.

Forest Disturbance Detection with Seasonal and Trend Model Components and Machine Learning Algorithms

Forest disturbances reduce the extent of natural habitats, biodiversity, and carbon sequestered in forests. With the implementation of the international framework Reduce Emissions from Deforestation and forest Degradation (REDD+), it is important to improve the accuracy in the estimation of the extent of forest disturbances. Time series analyses, such as Breaks for Additive Season and Trend (BFAST), have been frequently used to map tropical forest disturbances with promising results. Previous studies suggest that in addition to magnitude of change, disturbance accuracy could be enhanced by using other components of BFAST that describe additional aspects of the model, such as its goodness-of-fit, NDVI seasonal variation, temporal trend, historical length of observations and data quality, as well as by using separate thresholds for distinct forest types. The objective of this study is to determine if the BFAST algorithm can benefit from using these model components in a supervised scheme to improve the accuracy to detect forest disturbance. A random forests and support vector machines algorithms were trained and verified using 238 points in three different datasets: all-forest, tropical dry forest, and temperate forest. The results show that the highest accuracy was achieved by the support vector machines algorithm using the all-forest dataset. Although the increase in accuracy of the latter model vs. a magnitude threshold model is small, i.e., 0.14% for sample-based accuracy and 0.71% for area-weighted accuracy, the standard error of the estimated total disturbed forest area was 4352.59 ha smaller, while the annual disturbance rate was also smaller by 1262.2 ha year−1. The implemented approach can be useful to obtain more precise estimates in forest disturbance, as well as its associated carbon emissions.

Creating past habitat maps to quantify local extirpation of Australian threatened birds

Habitat loss is driving the extirpation of fauna across Earth. Many species are now absent from vast areas where they once occurred in inhabited continents, yet we do not have a good understanding of the extent to which different species have been locally extirpated, nor the degree to which range contractions and habitat loss has contributed to this local extirpation. Here, for the first time, we use a combination of scientific literature, historical sources, spatial data, and expert elicitation to map the past extent of potential habitats, and changes thereto, of 72 of Australia’s most imperiled terrestrial birds. By comparing the area of potential habitat within the past and current ranges of these taxa, we quantify the extent over which each of Australia’s threatened terrestrial birds have likely been extirpated and assess the amount and configuration of potential habitat that remains. Our results show that since 1750 (before European colonization), at least one extant taxon of threatened bird has disappeared from over 530 million hectares (69%) of Australia, through both range contractions and loss of potentially suitable habitat (noting these are not mutually exclusive phenomena). Ten taxa (14%) have likely been extirpated from >99% of their past potential habitat. For 56 taxa (78%), remaining habitat within their current potential habitats has become fragmented. This research paints a sobering picture of the extent of local extirpation of threatened birds from much of Australia over a 250 years time period. By mapping and quantifying this loss, these findings will help refine scientific understanding about the impact of habitat removal and other pervasive threats that are driving this observed extirpation.

A spatially explicit analytical framework to assess wildfire risks on brown bear habitat and corridors in conservation areas

BackgroundHumans have altered fire regimes across ecosystems due to climate change, land use change, and increasing ignition. Unprecedented shifts in fire regimes affect animals and contribute to habitat displacement, reduced movement, and increased mortality risk. Mitigating these effects require the identification of habitats that are susceptible to wildfires. We designed an analytical framework that incorporates fire risk mapping with species distribution modeling to identify key habitats of Ursus arctos with high probability of fire in Iran. We applied the random forest algorithm for fire risk mapping. We also modeled brown bear habitats and predicted connectivity between them using species distribution models and connectivity analysis, respectively. Finally, the fire risk map, critical habitats, and corridors were overlaid to spatially identify habitats and corridors that are at high risk of fire.ResultsWe identified 17 critical habitats with 5245 km2 of corridors connecting them, 40.06% and 11.34% of which are covered by conservation areas, respectively. Our analysis showed that 35.65% of key habitats and 23.56% of corridors are at high risk of fire.ConclusionsSince bears habitat in this semi-arid landscape rely on forests at higher altitudes, it is likely that shifting fire regimes due to changing climate and land use modifications reduce the extent of habitats in the future. While it is not well known how fire affects bears, identifying its key habitat where wildfires are likely to occur is the first step to manage potential impacts from increasing wildfires on this species.

Quantifying the Intra-Habitat Variation of Seagrass Beds with Unoccupied Aerial Vehicles (UAVs)

Accurate knowledge of the spatial extent of seagrass habitats is essential for monitoring and management purposes given their ecological and economic significance. Extent data are typically presented in binary (presence/absence) or arbitrary, semi-quantitative density bands derived from low-resolution satellite imagery, which cannot resolve fine-scale features and intra-habitat variability. Recent advances in consumer-grade unoccupied aerial vehicles (UAVs) have advanced our ability to survey large areas at higher resolution and at lower cost. This has improved the accessibility of mapping technologies to developing coastal nations, where a large proportion of the world’s seagrass habitats are found. Here, we present the application of UAV-gathered imagery to determine seagrass habitat extent and percent of canopy cover. Four contrasting sites were surveyed in the Turneffe Atoll Marine Reserve, Belize, and seagrass canopy cover was ground truthed from in situ quadrats. Orthomosaic images were created for each site from the UAV-gathered imagery. Three modelling techniques were tested to extrapolate the findings from quadrats to spatial information, producing binary (random forest) and canopy cover (random forest regression and beta regression) habitat maps. The most robust model (random forest regression) had an average absolute error of 6.8–11.9% (SE of 8.2–14), building upon previous attempts at mapping seagrass density from satellite imagery, which achieved errors between 15–20% approximately. The resulting maps exhibited great intra-habitat heterogeneity and different levels of patchiness, which were attributed to site energetics and, possibly, species composition. The extra information in the canopy cover maps provides greater detail and information for key management decisions and provides the basis for future spatial studies and monitoring programmes.