An Outcome-Oriented, Social-Ecological Framework for Assessing Protected Area Effectiveness

Both the number and the extent of protected areas have grown considerably in recent years, but evaluations of their effectiveness remain partial and are hard to compare across cases. To overcome this situation, first, we suggest reserving the term effectiveness solely for assessing protected area outcomes, to clearly distinguish this from management assessments (e.g., sound planning). Second, we propose a multidimensional conceptual framework, rooted in social–ecological theory, to assess effectiveness along three complementary dimensions: ecological outcomes (e.g., biodiversity), social outcomes (e.g., well-being), and social–ecological interactions (e.g., reduced human pressures). Effectiveness indicators can subsequently be evaluated against contextual and management elements (e.g., design and planning) to shed light on management performance (e.g., cost-effectiveness). We summarize steps to operationalize our framework to foster more holistic effectiveness assessments while improving comparability across protected areas. All of this can ensure that protected areas make real contributions toward conservation and sustainability goals.Peer Reviewe

Effects of different matrix representations and connectivity measures on habitat network assessments

Assessing landscape connectivity is important to understand the ecology of landscapes and to evaluate alternative conservation strategies. The question is though, how to quantify connectivity appropriately, especially when the information available about the suitability of the matrix surrounding habitat is limited. Our goal here was to investigate the effects of matrix representation on assessments of the connectivity among habitat patches and of the relative importance of individual patches for the connectivity within a habitat network. We evaluated a set of 50 × 50 km^2 test areas in the Carpathian Mountains and considered three different matrix representations (binary, categorical and continuous) using two types of connections among habitat patches (shortest lines and least-cost paths). We compared connections, and the importance of patches, based on (1) isolation, (2) incidence-functional, and (3) graph measures. Our results showed that matrix representation can greatly affect assessments of connections (i.e., connection length, effective distance, and spatial location), but not patch prioritization. Although patch importance was not much affected by matrix representation, it was influenced by the connectivity measure and its parameterization. We found the biggest differences in the case of the integral index of connectivity and equally weighted patches, but no consistent pattern in response to changing dispersal distance. Connectivity assessments in more fragmented landscapes were more sensitive to the selection of matrix representation. Although we recommend using continuous matrix representation whenever possible, our results indicated that simpler matrix representations can be also used as a proxy to delineate those patches that are important for overall connectivity, but not to identify connections among habitat patches

Resource pulses and human–wildlife conflicts

Pulsed resources have prominent effects on community and ecosystem dynamics; however, there is little research on how resource pulses affect human–wildlife interactions. Tree masting is a common type of pulsed resource that represents a crucial food for many species and has important bottom-up effects in food webs. In anthropogenic landscapes, years of food shortage after mast years can have negative outcomes for both people and wildlife, for instance when an increased use of anthropogenic foods by animals exacerbates human–wildlife conflicts. Here, we used novel remote sensing indicators of forest productivity and phenology, together with weather cues and ground measures of mast production, to assess whether years of masting and crop failures lead to changes in human–wildlife conflict occurrence. We used a unique 14-year dataset including the production of European beech Fagus sylvatica seeds and brown bear Ursus arctos damage in the northeastern Carpathians as our model system. Linking these data in a panel regression framework, we found that temporal fluctuations in damage occurrence were sensitive to the year-to-year variation in beechnut production. Specifically, the number of damages during bear hyperphagia (i.e., September to December, when bears need to accumulate fat reserves prior to hibernation) was significantly higher in years with low beechnut production than in normal or mast years. Furthermore, we provide evidence that beech masting and failure can be predicted through a combination of remote-sensing, weather, and field indicators of forest productivity and phenology. We demonstrate how pulsed resources, such as tree masting, can percolate through food webs to amplify human–wildlife conflict in human-dominated landscapes. Given the recent range expansion of large carnivores and herbivores in many regions, including Europe, predicting years of natural food shortage can provide a pathway to proactive damage prevention, and thus to foster coexistence between wildlife and people.Peer Reviewe

Agents of Forest Disturbance in the Argentine Dry Chaco

Forest degradation in the tropics is a widespread, yet poorly understood phenomenon. This is particularly true for tropical and subtropical dry forests, where a variety of disturbances, both natural and anthropogenic, affect forest canopies. Addressing forest degradation thus requires a spatially-explicit understanding of the causes of disturbances. Here, we apply an approach for attributing agents of forest disturbance across large areas of tropical dry forests, based on the Landsat image time series. Focusing on the 489,000 km2 Argentine Dry Chaco, we derived metrics on the spectral characteristics and shape of disturbance patches. We then used these metrics in a random forests classification framework to estimate the area of logging, fire, partial clearing, riparian changes and drought. Our results highlight that partial clearing was the most widespread type of forest disturbance from 1990–to 2017, extending over 5520 km2 (±407 km2), followed by fire (4562 ± 388 km2) and logging (3891 ± 341 km2). Our analyses also reveal marked trends over time, with partial clearing generally becoming more prevalent, whereas fires declined. Comparing the spatial patterns of different disturbance types against accessibility indicators showed that fire and logging prevalence was higher closer to fields, while smallholder homesteads were associated with less burning. Roads were, surprisingly, not associated with clear trends in disturbance prevalence. To our knowledge, this is the first attribution of disturbance agents in tropical dry forests based on satellite-based indicators. While our study reveals remaining uncertainties in this attribution process, our framework has considerable potential for monitoring tropical dry forest disturbances at scale. Tropical dry forests in South America, Africa and Southeast Asia are some of the fastest disappearing ecosystems on the planet, and more robust monitoring of forest degradation in these regions is urgently needed.Peer Reviewe

Mapping cropland-use intensity across Europe using MODIS NDVI time series

Global agricultural production will likely need to increase in the future due to population growth, changing diets, and the rising importance of bioenergy. Intensifying already existing cropland is often considered more sustainable than converting more natural areas. Unfortunately, our understanding of cropping patterns and intensity is weak, especially at broad geographic scales. We characterized and mapped cropping systems in Europe, a region containing diverse cropping systems, using four indicators: (a) cropping frequency (number of cropped years), (b) multi-cropping (number of harvests per year), (c) fallow cycles, and (d) crop duration ratio (actual time under crops) based on the MODIS Normalized Difference Vegetation Index (NDVI) time series from 2000 to 2012. Second, we used these cropping indicators and self-organizing maps to identify typical cropping systems. The resulting six clusters correspond well with other indicators of agricultural intensity (e.g., nitrogen input, yields) and reveal substantial differences in cropping intensity across Europe. Cropping intensity was highest in Germany, Poland, and the eastern European Black Earth regions, characterized by high cropping frequency, multi-cropping and a high crop duration ratio. Contrarily, we found lowest cropping intensity in eastern Europe outside the Black Earth region, characterized by longer fallow cycles. Our approach highlights how satellite image time series can help to characterize spatial patterns in cropping intensity—information that is rarely surveyed on the ground and commonly not included in agricultural statistics: our clustering approach also shows a way forward to reduce complexity when measuring multiple indicators. The four cropping indicators we used could become part of continental-scale agricultural monitoring in order to identify target regions for sustainable intensification, where trade-offs between intensification and the environmental should be explored.Peer Reviewe

Large carnivore range expansion in Iberia in relation to different scenarios of permeability of human‐dominated landscapes

Aim Large carnivores are currently recolonizing parts of their historical ranges in Europe after centuries of persecution and habitat loss. Understanding the mechanisms driving these recolonizations is important for proactive conservation planning. Using the brown bear (Ursus arctos) and the Iberian lynx (Lynx pardinus) as examples, we explore where and when large carnivores are likely to expand into human-dominated landscapes and how varying levels of resistance due to human pressure might impact this recolonization process. Location Iberian Peninsula. Methods We used ensembles of species distribution models to relate species occurrence data to climate, topography and satellite-based land-cover predictors at a 10 km spatial resolution. Resulting predictions of suitable habitat areas were fed into a dispersal model to simulate range expansion over the 10 time-steps for different human pressure scenarios. Finally, we overlaid predictions with protected areas to highlight areas that are likely key for future connectivity, but where human pressures might hamper dispersal. Results We found widespread suitable habitat for both species (bear: 30,000 km2, lynx: 170,000 km2), yet human pressure limits potential range expansions. For brown bears, core habitats between the Cantabrian and Pyrenean populations remained unconnected despite suitable habitat in between. For lynx, we predicted higher range expansion potential, although high human pressures in southern coastal Spain negatively affected expansion potential. Main conclusions Our results highlight that the recolonization potential of brown bears and lynx in the Iberian Peninsula is likely more constrained by lower permeability of landscapes due to human pressure than by habitat availability, a situation likely emblematic for large carnivores in many parts of the world. More generally, our approach provides a simple tool for conservation planners and managers to identify where range expansion is likely to occur and where proactively managing to allow large carnivores to safely disperse through human-dominated landscapes can contribute to viable large carnivore populations.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Peer Reviewe

Towards Causal Inference for Spatio-Temporal Data: Conflict and Forest Loss in Colombia

In many data scientific problems, we are interested not only in modeling the behaviour of a system that is passively observed, but also in inferring how the system reacts to changes in the data generating mechanism. Given knowledge of the underlying causal structure, such behaviour can be estimated from purely observational data. To do so, one typically assumes that the causal structure of the data generating mechanism can be fully specified. Furthermore, many methods assume that data are generated as independent replications from that mechanism. Both of these assumptions are usually hard to justify in practice: datasets often have complex dependence structures, as is the case for spatio-temporal data, and the full causal structure between all involved variables is hardly known. Here, we present causal models that are adapted to the characteristics of spatio-temporal data, and which allow us to define and quantify causal effects despite incomplete causal background knowledge. We further introduce a simple approach for estimating causal effects, and a non-parametric hypothesis test for these effects being zero. The proposed methods do not rely on any distributional assumptions on the data, and allow for arbitrarily many latent confounders, given that these confounders do not vary across time (or, alternatively, they do not vary across space). Our theoretical findings are supported by simulations and code is available online. This work has been motivated by the following real-world question: how has the Colombian conflict influenced tropical forest loss? There is evidence for both enhancing and reducing impacts, but most literature analyzing this problem is not using formal causal methodology. When applying our method to data from 2000 to 2018, we find a reducing but insignificant causal effect of conflict on forest loss. Regionally, both enhancing and reducing effects can be identified.Comment: 29 pages, 8 figure

Differences in production, carbon stocks and biodiversity outcomes of land tenure regimes in the Argentine Dry Chaco

Rising global demand for agricultural products results in agricultural expansion and intensification, with substantial environmental trade-offs. The South American Dry Chaco contains some of the fastest expanding agricultural frontiers worldwide, and includes diverse forms of land management, mainly associated with different land tenure regimes; which in turn are segregated along environmental gradients (mostly rainfall). Yet, how these regimes impact the environment and how trade-offs between production and environmental outcomes varies remains poorly understood. Here, we assessed how biodiversity, biomass stocks, and agricultural production, measured in meat-equivalents, differ among land tenure regimes in the Dry Chaco. We calculated a land-use outcome index (LUO) that combines indices comparing actual vs. potential values of 'preservation of biodiversity' (PI), 'standing biomass' (BI) and 'meat production' (MI). We found land-use outcomes to vary substantially among land-tenure regimes. Protected areas showed a biodiversity index of 0.75, similar to that of large and medium-sized farms (0.72 in both farming systems), and higher than in the other tenure regimes. Biomass index was similar among land tenure regimes, whereas we found the highest median meat production index on indigenous lands (MI = 0.35). Land-use outcomes, however, varied more across different environmental conditions than across land tenure regimes. Our results suggest that in the Argentine Dry Chaco, there is no single land tenure regime that better minimizes the trade-offs between production and environmental outcomes. A useful approach to manage these trade-offs would be to develop geographically explicit guidelines for land-use zoning, identifying the land tenure regimes more appropriate for each zone.Environmental Conservation Found of the Argentina Galicia BankEinstein Stiftung Berlin 10.13039/501100006188The German Federal Ministry of Education and ScienceGerman Research FoundationArgentina National Agency of Science and Technological ResearchRufford Foundation 10.13039/100007463Consejo Nacional de Investigaciones Científicas y Técnicas 10.13039/501100002923Peer Reviewe

Changing patterns of conflict between humans, carnivores and crop-raiding prey as large carnivores recolonize human-dominated landscapes

Large carnivores are making remarkable comebacks in Europe, but how this affects human-wildlife conflict remains unclear. Rebounding carnivore populations lead to increasing livestock depredation, which in turn leads to greater economic losses for farmers. However, returning carnivores could also influence the behavior of wild ungulates, which are themselves responsible for major crop damage and associated economic losses. Here, we exploit the natural experiment of a rebounding wolf population in the Italian Apennines to study how this affected both types of human-wildlife conflic. We used large datasets of wolf occurrences (n = 351), livestock depredation events (n = 165), and crop damage events by wild boar (n = 3442) to independently model the determinants of livestock depredation and crop damage distribution in relation to wolf habitat suitability over a ten-year period of increasing wolf numbers. These analyses yielded two major insights. First, livestock depredations were mainly related to insufficient prevention measures (e.g. lacking fencing) rather than landscape context, providing a clear pathway to conflict mitigation. Second, crop damage decreased in areas of higher wolf habitat suitability and became more likely in areas of lower wolf habitat suitability, closer to settlements. This suggests increasing predation pressure forces wild boars to avoid the most suitable wolf habitat, leading to a redistribution of crop damage in the landscape. More generally, our study highlights complex human-wildlife interactions as large carnivores recover in human-dominated landscapes, suggesting that multiple, co-occurring conflicts need to be assessed jointly and adaptively in order to foster coexistence between humans and wildlife