Integrating functional connectivity and fire management for better conservation outcomes

Globally, the mean abundance of terrestrial animals has fallen by 50% since 1970, and populations face ongoing threats associated with habitat loss, fragmentation, climate change, and disturbance. Climate change can influence the quality of remaining habitat directly and indirectly by precipitating increases in the extent, frequency, and severity of natural disturbances, such as fire. Species face the combined threats of habitat clearance, changing climates, and altered disturbance regimes, each of which may interact and have cascading impacts on animal populations. Typically, conservation agencies are limited in their capacity to mitigate rates of habitat clearance, habitat fragmentation, or climate change, yet fire management is increasingly used worldwide to reduce wildfire risk and achieve conservation outcomes. A popular approach to ecological fire management involves the creation of fire mosaics to promote animal diversity. However, this strategy has 2 fundamental limitations: the effect of fire on animal movement within or among habitat patches is not considered and the implications of the current fire regime for long-term population persistence are overlooked. Spatial and temporal patterns in fire history can influence animal movement, which is essential to the survival of individual animals, maintenance of genetic diversity, and persistence of populations, species, and ecosystems. We argue that there is rich potential for fire managers to manipulate animal movement patterns; enhance functional connectivity, gene flow, and genetic diversity; and increase the capacity of populations to persist under shifting environmental conditions. Recent methodological advances, such as spatiotemporal connectivity modeling, spatially explicit individual-based simulation, and fire-regime modeling can be integrated to achieve better outcomes for biodiversity in human-modified, fire-prone landscapes. Article impact statement: Land managers may conserve populations by using fire to sustain or enhance functional connectivity.     

Scale dependency in effectiveness,isolation, and social‐ecological spillover of protected areas

Protected areas are considered vital for the conservation of biodiversity. Given their central role in many conservation strategies, it is important to know whether they adequately protect biodiversity within their boundaries; whether they are becoming more isolated from other natural areas over time; and whether they play a role in facilitating or reducing land‐cover change in their surroundings. We used matching methods and national and local analyses of land‐cover change to evaluate the combined effectiveness (i.e., avoided natural‐cover loss), isolation (i.e., changes in adjacent areas), and spillover effects (i.e., impacts on adjacent areas) of 19 national parks in South Africa from 2000 to 2009. All parks had either similar or lower rates of natural‐cover loss than matched control samples. On a national level, mean net loss of natural cover and mean net gain of cultivation cover decreased with distance from park boundary, but there was considerable variation in trends around individual parks, providing evidence for both increased isolation and buffering of protected areas. Fourteen parks had significant positive spillover and reduced natural‐cover loss in their surroundings, whereas five parks experienced elevated levels of natural‐cover loss. Conclusions about social‐ecological spillover effects from protected areas depended heavily on the measures of land‐cover change used and the scale at which the results were aggregated. Our findings emphasize the need for high‐resolution data when assessing spatially explicit phenomena such as land‐cover change and challenge the usefulness of large‐scale (coarse grain, broad extent) studies for understanding social‐ecological dynamics around protected areas.     

The consequences of poaching and anthropogenic change for forest elephants

Poaching has devastated forest elephant populations (Loxodonta cyclotis), and their habitat is dramatically changing. The long‐term effects of poaching and other anthropogenic threats have been well studied in savannah elephants (Loxodonta africana), but the impacts of these changes for Central Africa's forest elephants have not been discussed. We examined potential repercussions of these threats and the related consequences for forest elephants in Central Africa by summarizing the lessons learned from savannah elephants and small forest elephant populations in West Africa. Forest elephant social organization is less known than the social organization of savannah elephants, but the close evolutionary history of these species suggests that they will respond to anthropogenic threats in broadly similar ways. The loss of older, experienced individuals in an elephant population disrupts ecological, social, and population parameters. Severe reduction of elephant abundance within Central Africa's forests can alter plant communities and ecosystem functions. Poaching, habitat alterations, and human population increase are probably compressing forest elephants into protected areas and increasing human–elephant conflict, which negatively affects their conservation. We encourage conservationists to look beyond documenting forest elephant population decline and address the causes of these declines when developing conversation strategies. We suggest assessing the effectiveness of the existing protected‐area networks for landscape connectivity in light of current industrial and infrastructure development. Longitudinal assessments of the effects of landscape changes on forest elephant sociality and behavior are also needed. Finally, lessons learned from West African elephant population loss and habitat fragmentation should be used to inform strategies for land‐use planning and managing human–elephant interactions.     

Using spatially explicit,time-dependent analysis to understand how social factors influence conservation outcomes

Conservation across human-dominated landscapes requires an understanding of the social and ecological factors driving outcomes. Studies that link conservation outcomes to social and ecological factors have examined temporally static patterns. However, there may be different social and ecological processes driving increases and decreases in conservation outcomes that can only be revealed through temporal analyses. Through a case study of the invasion of Falcataria moluccana in Hawaii, we examined the association of social factors with increases and decreases in invader distributions over time and space. Over 7 years, rates of invader decrease varied substantially (66–100%) relative to social factors, such as building value, whether land was privately or publically owned, and primary residence by a homeowner, whereas rates of increase varied only slightly (<0.1–3.6%) relative to such factors. These findings suggest that links between social factors and invasion in the study system may be driven more by landowners controlling existing invasive species, rather than by landowners preventing the spread of invasive species. We suggest that spatially explicit, time-dependent analyses provide a more nuanced understanding of the way social factors influence conservation outcomes. Such an understanding can help managers develop outreach programs and policies targeted at different types of landowners in human-dominated landscapes.     

Enhancing synergies between action on ocean acidification and the post-2020 global biodiversity framework

Ocean acidification is a substantial emergent threat to marine biodiversity and the goods and services it provides. Although efforts to address ocean acidification have been taken under the Convention on Biological Diversity (CBD), a far greater potential to do so exists by finding synergies between biodiversity conservation efforts and ocean acidification action. The ongoing process to develop a post-2020 global biodiversity framework offers an opportunity to ensure that opportunities for addressing ocean acidification are capitalized on and not overlooked. I argue that to achieve this, the following are needed: a technical integration of ocean acidification across the targets to be included in the post-2020 framework and a reframing of the issue as a biodiversity problem so as to highlight the synergies between existing biodiversity work and action needed to address ocean acidification. Given that the post-2020 framework is intended to establish the global biodiversity agenda for the coming decades, integration of ocean acidification will set a precedent for the other biodiversity-related conventions and encourage greater uptake of the issue across the wider international community. My approach is of direct relevance to those participating in the negotiations, both from a CBD Party perspective and the perspective of those advocating for a strong outcome to protect marine biodiversity and marine socioecological systems. My discussion of framing is relevant to those working beyond the CBD within other biodiversity-related conventions in which goals to address ocean acidification are sorely lacking.     

How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.     

Wildlife impacts and vulnerable livelihoods in a transfrontier conservation landscape

Interactions between humans and wildlife resulting in negative impacts are among the most pressing conservation challenges globally. In regions of smallholder livestock and crop production, interactions with wildlife can compromise human well-being and motivate negative sentiment and retaliation toward wildlife, undermining conservation goals. Although impacts may be unavoidable when human and wildlife land use overlap, scant large-scale human data exist quantifying the direct costs of wildlife to livelihoods. In a landscape of global importance for wildlife conservation in southern Africa, we quantified costs for people living with wildlife through a fundamental measure of human well-being, food security, and we tested whether existing livelihood strategies buffer certain households against crop depredation by wildlife, predominantly elephants. To do this, we estimated Bayesian multilevel statistical models based on multicounty household data (n = 711) and interpreted model results in the context of spatial data from participatory land-use mapping. Reported crop depredation by wildlife was widespread. Over half of the sample households were affected and household food security was reduced significantly (odds ratio 0.37 [0.22, 0.63]). The most food insecure households relied on gathered food sources and welfare programs. In the event of crop depredation by wildlife, these 2 livelihood sources buffered or reduced harmful effects of depredation. The presence of buffering strategies suggests a targeted compensation strategy could benefit the region's most vulnerable people. Such strategies should be combined with dynamic and spatially explicit land-use planning that may reduce the frequency of negative human–wildlife impacts. Quantifying and mitigating the human costs from wildlife are necessary steps in working toward human–wildlife coexistence.     

Antagonistic effect of natural habitat conversion on community adjustment to climate warming in nonbreeding waterbirds

Although the impacts of climate and land-use changes on biodiversity have been widely documented, their joint effects remain poorly understood. We evaluated how nonbreeding waterbird communities adjust to climate warming along a gradient of land-use change. Using midwinter waterbird counts (132 species) at 164 major nonbreeding sites in 22 Mediterranean countries, we assessed the changes in species composition from 1991 to 2010, relative to thermal niche position and breadth, in response to regional and local winter temperature anomalies and conversion of natural habitats. We observed a low-level, nonsignificant community adjustment to the temperature increase where natural habitat conversion occurred. At the sites affected by natural habitat conversion, the relative increase of warm-dwelling species in response to climate warming was 6 times lower and the relative species decline was 3 times higher than in the sites without natural habitat conversion. We found no evidence of community adjustment to climate warming when natural habitat conversion was >5% over 15 years. This strong negative effect suggests an antagonistic interaction between climate warming and habitat change. These results underline the importance of habitat conservation in community adjustment to climate warming.     

Examining the relationship between local extinction risk and position in range

Over half of globally threatened animal species have experienced rapid geographic range loss. Identifying the parts of species’ distributions most vulnerable to local extinction would benefit conservation planning. However, previous studies give little consensus on whether ranges decline to the core or edge. We built on previous work by using empirical data to examine the position of recent local extinctions within species’ geographic ranges, address range position as a continuum, and explore the influence of environmental factors. We aggregated point‐locality data for 125 Galliform species from across the Palearctic and Indo‐Malaya into equal‐area half‐degree grid cells and used a multispecies dynamic Bayesian occupancy model to estimate rates of local extinctions. Our model provides a novel approach to identify loss of populations from within species ranges. We investigated the relationship between extinction rates and distance from range edge by examining whether patterns were consistent across biogeographic realm and different categories of land use. In the Palearctic, local extinctions occurred closer to the range edge than range core in both unconverted and human‐dominated landscapes. In Indo‐Malaya, no pattern was found for unconverted landscapes, but in human‐dominated landscapes extinctions tended to occur closer to the core than the edge. Our results suggest that local and regional factors override general spatial patterns of recent local extinction within species’ ranges and highlight the difficulty of predicting the parts of a species’ distribution most vulnerable to threat.