Changes In Vegetation Productivity Research Articles

Effect of seasonal variation on feeding and food preference of olive baboons (Papio anubis) in a protected Guinean savannah of West Africa

Abstract This study investigates the effects of seasonal changes in vegetation productivity on olive baboon feeding behavior in a protected Guinea savannah (Kainji Lake National Park). Over two consecutive years (2017 and 2018), observations were conducted both during the wet and dry seasons using a scan sampling method. Results revealed that olive baboons consumed 34 plant species belonging to 20 families, with 28 species in the wet season and 12 in the dry season. A total of 922 feeding events were recorded in the wet season and 621 in the dry season, indicating significant seasonal variation. Fruits were the preferred food item, especially in the dry season, followed by animal matter, seeds, leaves, and subterranean food. Interestingly, baboons also consumed tree bark regardless of season. In addition, their consumption of fruits (in both seasons) and seeds (in the dry season) highlights their ecological role in seed dispersal and plant regeneration within the park. To sustain baboon (and all non-human primates) conservation efforts within the park, it’s important to maintain a high diversity and abundance of native fruit trees throughout the year. This study highlights the importance of understanding how seasonal changes in vegetation affect olive baboon feeding behavior for effective park management and biodiversity conservation.

Spatiotemporal Evolution and Impact Mechanisms of Gross Primary Productivity in Tropics

Gross primary productivity (GPP), representing organic carbon fixation through photosynthesis, is crucial for developing science-based strategies for sustainable development. Given that the tropical region harbors nearly half of all species, it plays a pivotal role in safeguarding the global environment against climate change and preserving global biodiversity. Thus, investigating changes in vegetation productivity within this region holds substantial practical importance for estimating global vegetation productivity. In this study, we employed an enhanced P model to estimate vegetation GPP in the tropical region from 2001 to 2020, based on which we quantified the spatiotemporal changes and associated mechanisms. The results reveal that the annual mean GPP in the tropical region ranged from 2603.9 to 2757.1 g·cm−2 a−1, demonstrating an overall apparent increasing trend. Inland areas were mainly influenced by precipitation, while coastal areas were primarily influenced by temperature. Land cover changes, especially conversion to cropland, significantly influence GPP, with deciduous—evergreen forest transitions causing notable decreases. Climate change emerges as the dominant factor affecting GPP, as indicated by the contribution rate analysis. This research interprets the spatiotemporal pattern and mechanisms of GPP in the tropics, offering valuable insights for sustainable ecosystem management.

Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia

Australia, characterized by extensive and heterogeneous terrestrial ecosystems, plays a critical role in the global carbon cycle and in efforts to mitigate climate change. Prior research has quantified vegetation productivity and carbon balance within the Australian context over preceding decades. Nonetheless, the responses of vegetation and carbon dynamics to the evolving phenomena of climate change and escalating concentrations of atmospheric carbon dioxide remain ambiguous within the Australian landscape. Here, we used LPJ-GUESS model to assess the impacts of climate change on Gross Primary Productivity (GPP) and Net Biome Productivity (NBP) of carbon for the state of New South Wales (NSW) in southeastern Australia. LPJ-GUESS simulations were driven by an ensemble of 27 global climate models under different emission scenarios. We investigated the change of GPP for different vegetation types and whether NSW ecosystems will be a net sink or source of carbon under climate change. We found that LPJ-GUESS successfully simulated GPP for the period 2003–2021, demonstrating a comparative performance with GPP derived from upscaled eddy covariance fluxes (R2 = 0.58, nRMSE = 14.2 %). The simulated NBP showed a larger interannual variation compared with flux data and other inversion products but could capture the timing of rainfall-driven carbon sink and source variations in 2015–2020. GPP would increase by 10.3–19.5 % under a medium emission scenario and 19.7–46.8 % under a high emission scenario. The mean probability of NSW acting as a carbon sink in the future showed a small decrease with a large uncertainty with >8 of the 27 climate models indicating an increased potential for carbon sink. These findings emphasize the significance of emission scenarios in shaping future carbon dynamics but also highlight considerable uncertainties stemming from different climate projections. Our study represents a baseline for understanding natural ecosystem dynamics and their key role in governing land carbon uptake and storage in Australia.

Tropical vegetation productivity and atmospheric methane over the last 40,000 years from model simulations and stalagmites in Sulawesi, Indonesia

AbstractRecent research has shown the potential of speleothem δ13C to record a range of environmental processes. Here, we report on 230Th-dated stalagmite δ13C records for southwest Sulawesi, Indonesia, over the last 40,000 yr to investigate the relationship between tropical vegetation productivity and atmospheric methane concentrations. We demonstrate that the Sulawesi stalagmite δ13C record is driven by changes in vegetation productivity and soil respiration and explore the link between soil respiration and tropical methane emissions using HadCM3 and the Sheffield Dynamic Global Vegetation Model. The model indicates that changes in soil respiration are primarily driven by changes in temperature and CO2, in line with our interpretation of stalagmite δ13C. In turn, modelled methane emissions are driven by soil respiration, providing a mechanism that links methane to stalagmite δ13C. This relationship is particularly strong during the last glaciation, indicating a key role for the tropics in controlling atmospheric methane when emissions from high-latitude boreal wetlands were suppressed. With further investigation, the link between δ13C in stalagmites and tropical methane could provide a low-latitude proxy complementary to polar ice core records to improve our understanding of the glacial–interglacial methane budget.

Monitoring spatiotemporal dynamics of large herbivores across an African rangeland using hierarchical multi‐species distance sampling

AbstractA relative lack of standardised long‐term monitoring data often limits the ability of African conservancies to quantify their efficacy to protect wildlife. In this study, we combined eight 2‐km long transects surveyed monthly between October 2017 and March 2020 (total 240 transects sampled) with a hierarchical multi‐species and multi‐season distance sampling modelling framework to: (1) estimate monthly density of an ensemble of 10 different large herbivores and (2) understand how species respond to changes in vegetation productivity and time across the Naboisho Conservancy in the Greater Mara Ecosystem, Kenya. We documented a total of 55,298 individuals from 6830 animal groups. The median coefficient of variation for all density estimates was 27.67%. On average, number of groups was higher at intermediate levels of vegetation productivity. We found that in general, populations of large herbivores remained stable in the conservancy during the study period, except for wildebeest which decreased in density. We showed that multi‐species monitoring frameworks can be used to understand how species abundance changes across space and time, providing indications as to how they are responding to environmental dynamics or management prescriptions—both of which are valuable tools for under‐resourced wildlife conservancies.

Response of Aboveground Net Primary Production, Species and Phylogenetic Diversity to Warming and Increased Precipitation in an Alpine Meadow.

The uncertain responses of aboveground net primary productivity (ANPP) and plant diversity to climate warming and increased precipitation will limit our ability to predict changes in vegetation productivity and plant diversity under future climate change and further constrain our ability to protect biodiversity and ecosystems. A long-term experiment was conducted to explore the responses of ANPP, plant species, phylogenetic α-diversity, and community composition to warming and increased precipitation in an alpine meadow of the Northern Tibet from 2014 to 2019. Coverage, height, and species name were obtained by conventional community investigation methods, and ANPP was obtained using observed height and coverage. Open-top chambers with two different heights were used to simulate low- and high-level climate warming. The low- and high-level increased precipitation treatments were achieved by using two kinds of surface area funnel devices. The high-level warming reduced sedge ANPP (ANPPsedge) by 62.81%, species richness (SR) by 21.05%, Shannon by 13.06%, and phylogenetic diversity (PD) by 14.48%, but increased forb ANPP (ANPPforb) by 56.65% and mean nearest taxon distance (MNTD) by 33.88%. Species richness, Shannon, and PD of the high-level warming were 19.64%, 9.67%, and 14.66% lower than those of the low-level warming, respectively. The high-level warming-induced dissimilarity magnitudes of species and phylogenetic composition were greater than those caused by low-level warming. The low- rather than high-level increased precipitation altered species and phylogenetic composition. There were significant inter-annual variations of ANPP, plant species, phylogenetic α-diversity and community composition. Therefore, climate warming and increased precipitation had non-linear effects on ANPP and plant diversity, which were due to non-linear changes in temperature, water availability, and/or soil nutrition caused by warming and increased precipitation. The inter-annual variations of ANPP and plant diversity were stronger than the effects of warming and especially increased precipitation on ANPP and plant diversity. In terms of plant diversity conservation and related policy formulation, we should pay more attention to regions with greater warming, at least for the northern Tibet grasslands. Besides paying attention to the responses of ANPP and plant diversity to climate change, the large inter-annual changes of ANPP and plant diversity should be given great attention because the large inter-annual variation indicates the low temporal stability of ANPP and plant diversity and thus produces great uncertainty for the development of animal husbandry.

Anthropocene trajectories of high alpine vegetation on Mont-Blanc nunataks

ABSTRACT Climate warming causes dramatic glacier retreat and intense vegetation changes in alpine regions. High-elevation nunataks, that is bedrock islands protruding from glaciers with uppermost flowering plants, are no exception. Yet the consequences of climate change on nunatak vegetation remain relatively unexplored. Here, we report findings from a re-visit of historical plant surveys carried out on six nunataks situated between 2180 m a.s.l. and 3509 m a.s.l. amidst the glaciers of the Mont-Blanc range (France). We compared vegetation surveys conducted in 2020 to those made 150 years before, and performed remote sensing analyses to depict changes in vegetation productivity during recent decades. We report an increase in plant species richness for the lowest and least isolated nunataks, which contributed to a strong signal of vegetation greening over the last 35 years. This trend was due to the upward migration of competitive species, but also due to species colonization from neighboring high alpine areas into recently unglaciated microsites. We also highlight striking ecological trajectories that have been little discussed so far, such as stable vegetation composition in the highest and most isolated nunataks, an increase of plant species associated with non-permanent snow-cover and water run-off, an increase of graminoids at lower elevations, and of phanerophytes at higher elevations. We argue that high alpine vegetation changes are not driven by the sole upward migration of lowland competitive species, and that careful monitoring of ongoing ecological changes over broad elevation gradients is necessary to better understand the rapid transformation of high alpine landscapes.

Short-Term Effects of Tunnel Construction on Soil Organic Carbon and Enzyme Activity in Shrublands in Eastern Tibet Plateau

Soil is the largest carbon pool, and our understanding of soil organic carbon (SOC) has been enhanced due to its role in mitigating climate change. However, fundamental uncertainty remains about the quantitative importance of tunnel excavation, one of the most common practices for road construction in mountainous areas, on the SOC dynamics. Therefore, the short-term effects of tunnel construction on SOC and its fraction, soil microbial carbon, and soil enzyme activity within 0–20 cm in two shrublands (dominated by Quercus aquifolioides and mixed with Q. aquifolioides, Rhododendron phaeochrysum and Betula platyphylla, respectively) in Eastern Tibet Plateau were investigated. The results showed that, regardless of vegetation type, SOC, dissolved organic carbon, and easily oxidizable carbon were 27.14 ± 2.87, 6.70 ± 0.74, and 0.29 ± 0.10 g kg−1 for tunnel-affected area of Q. aquifolioides and 47.96 ± 17.89, 11.19 ± 2.92, and 0.24 ± 0.04 g kg−1 for the mixture of Q. aquifolioides, R. phaeochrysum, and B. platyphylla, respectively. The values were not significantly different from those of tunnel unaffected areas (p > 0.05). Similarly, soil enzymes (except cellulase) were not significantly different between tunnel-affected and unaffected areas (p > 0.05), indicating that tunnel construction had a minor impact on the SOC fractions and soil enzymes in the early stage. The unchanged SOC and enzyme activities may be associated with no changes in vegetation production and soil water content in tunnel-affected areas. However, vegetation type had a significant impact on SOC and its fractions and soil enzymes (p < 0.05), demonstrating the importance of vegetation control on the SOC fraction and soil enzymes. This study would be one of the earliest studies to explore the effects of tunnel construction on soil carbon dynamics based on field experiment, which could provide a new concept on environmental sustainability during tunnel construction. However, a long-term study is encouraged to detect the effects of tunnel construction SOC and soil enzymes in the future.

Quantifying the contributions of climate factors and human activities to variations of net primary productivity in China from 2000 to 2020

Net primary productivity (NPP) plays a vital role in the globe carbon cycle. Quantitative assessment of the effects of climate changes and human activities on net primary productivity dynamics is vital for understanding the driving mechanisms of vegetation change and sustainable development of ecosystems. This study investigates the contributions of climatic factors and human activities to vegetation productivity changes in China from 2000 to 2020 based on the residual trend analysis (RESTREND) method. The results showed that the annual average net primary productivity in China was 325.11 g C/m2/year from 2000 to 2020 and net primary productivity showed a significantly increasing trend (p<0.05) at a rate of 2.32 g C/m2/year. Net primary productivity increased significantly (p<0.05) across 40.90% of China over the study period, while only 1.79% showed a significantly declining trend (p<0.05). The contributions of climatic factors and human activities to net primary productivity increase were 1.169 g C/m2/year and 1.142 g C/m2/year, respectively. Climate factors contributed positively mainly in Sichuan Basin, the Loess Plateau, the Mongolian Plateau, and Northeast China Plain. Positive contributions of human activities to net primary productivity mainly occurred in the Loess Plateau, Central China, and the Greater Khingan Mountains. The effects of climatic factors and human activities on net primary productivity changes varied among sub-regions. In Tropical Monsoon Climate Region and Subtropical Monsoon Climate Region, human activities had greater impacts on net primary productivity increase than climate factors, while climate factors were the dominant factor for net primary productivity recovery in other sub-regions. In addition, during 2000–2020, net primary productivity was dominated by both climate factors and human activities in 49.84% of China, while areas dominated solely by climate factors and human activities accounted for 13.67% and 10.92%, respectively. Compared to changed land cover types, the total net primary productivity as well as the increase of total net primary productivity in China was mostly contributed by unchanged land cover types, which contributed more than 90%.

PInc-PanTher estimates of Arctic permafrost soil carbon under the GeoMIP G6solar and G6sulfur experiments

Abstract. Circum-Arctic permafrost stores large amounts of frozen carbon that must be maintained to avoid catastrophic climate change. Solar geoengineering has the potential to cool the Arctic surface by increasing planetary albedo but could also reduce tundra productivity. Here, we improve the data-constrained PInc-PanTher model of permafrost carbon storage by including estimates of plant productivity and rhizosphere priming on soil carbon. Six earth system models are used to drive the model, running G6solar (solar dimming) and G6sulfur (stratospheric sulfate aerosols) experiments, which reduce radiative forcing from SSP5-8.5 (no mitigation) to SSP2-4.5 (substantive mitigation) levels. By 2100, simulations indicate a loss of 9.2 ± 0.4 million km2 (mean ± standard error) of permafrost area and 81 ± 8 Pg of soil carbon under the SSP5-8.5 scenario. In comparison, under SSP2-4.5, G6solar, and G6sulfur, permafrost area loss would be mitigated by approximately 39 %, 37 %, and 34 % and soil carbon loss by 42 %, 54 %, and 47 %, respectively, relative to SSP5-8.5. Uncertainties in permafrost soil C loss estimates arise mainly from changes in vegetation productivity. Increased carbon flux from vegetation to soil raises soil C storage, while the priming effects of root exudates lowers it, with a net mitigating effect on soil C loss. Despite model differences, the protective effects of G6solar and G6sulfur on permafrost area and soil C storage are consistent and significant for all ESMs. G6 experiments mitigate ∼ 1/3 of permafrost area loss and halve carbon loss for SSP5-8.5, averting USD 0–70 trillion (mean of USD 20 trillion) in economic losses through reduced permafrost emissions.

Drylands contribute disproportionately to observed global productivity increases

Drylands cover about 40% of the terrestrial surface and are sensitive to climate change, but their relative contributions to global vegetation greening and productivity increase in recent decades are still poorly known. Here, by integrating satellite data and biosphere modeling, we showed that drylands contributed more to global gross primary productivity (GPP) increase (65% ± 16%) than to Earth greening (33% ± 15%) observed during 1982–2015. The enhanced productivity per unit leaf area, i.e., light-use efficiency (LUE), was the mechanism behind this pattern. We also found that LUE was more sensitive to soil moisture than to atmospheric vapor pressure deficit (VPD) in drylands, while the opposite was observed (i.e., LUE was more sensitive to VPD) in humid areas. Our findings suggest the importance of using different moisture stress metrics in projecting the vegetation productivity changes of dry versus humid regions and highlight the prominent role of drylands as key controllers of the global carbon cycle.

Vegetation productivity of the Lake Poyang Wetland in the post Three Gorges Dam era

三峡运行以来,气候变化与人类活动共同驱动了鄱阳湖水文情势的急剧变化,并对其湿地植被产生了显著影响,但当前研究尚未系统量化鄱阳湖湿地植被在此条件下的演变规律与趋势。因此,本研究以增强型植被指数EVI(enhanced vegetation index)的时段最高值作为表征湿地植被生产力的代用指标,定量揭示了后三峡工程时代鄱阳湖湿地植被生产力的气候态特征及其变化,包括变化的量级、显著性及阶段性。结果表明:(1)2000-2020年,鄱阳湖湿地植被EVI最高值在全年及春、秋两季分别为0.37、0.30和0.33,入湖河流三角洲及碟形洼地边滩是其生产力中心;春季EVI最高值在此区域高于秋季,而在湖心区低于秋季。(2)三峡运行后的湿地植被生产力变化在全年及春、秋两季均有极大空间异质性,在湖心深泓线附近显著增加,而在入湖河流三角洲及湿地边缘下降。春季EVI增长区域面积占比极大(84.2%),而秋季增长区面积占比较小(71.2%),即有较大面积区域EVI在秋季下降(38.8%)。(3)三峡运行后,鄱阳湖湿地植被生产力中心经历了原位增长、空间扩张以及湖心向转移3个阶段,最终完成了由支流三角洲向湖心区的转移。从总体来看,鄱阳湖湿地植被生产力在全年及春、秋季均呈增长趋势,增速分别为0.0035、0.0049和0.0028 EVI/a。本研究量化了后三峡工程时代的鄱阳湖湿地植被生产力变化,为该区域进一步的综合管理提供了数据支撑。;Since the operation of the Three Gorges Dam (TGD), the superposition of human activities and climate change has dramatically changed hydrological regimes of the Lake Poyang. These changes significantly affected the structure and function of the surrounding wetland ecosystems. However, vegetation variations in the Lake Poyang Wetland under this changing condition has not yet been systematically quantified. Hence, this study took the maximum EVI (enhanced vegetation index) as a proxy index to characterize vegetation productivity of the Lake Poyang Wetland, aiming to quantitatively reveal its changes in the post TGD era. The results show that: (1) During 2000 to 2020, the regional averaged maximum EVI of the wetland was 0.37, 0.30 and 0.33 in the whole year, spring, and autumn, respectively. River deltas of the lake tributaries and the dished depressions in the wetland were generally with higher EVI values compared to other areas, thus regarding as high productivity center of the wetland. In springs, the maximum EVI in the productivity center was higher than that in autumn, whereas it was lower than that in autumn in other areas with low EVI values such as the center of the lake. (2) Changes of vegetation productivity had great spatial heterogeneity for all the periods including the whole year, springs, and autumns. The maximum EVI values increased significantly in the central of the wetland (surrounding the thalweg), while the maximum EVI values decreased in river deltas of lake tributaries and wetland edge. The areas with increasing EVI values in spring accounted for about 84.2% of the whole wetland, while the area with increasing EVI in autumn accounted merely 71.2% of the wetland. That is, there was still a large proportion of the wetland with decreasing EVI in autumn (38.8%). (3) After TGD, the high productivity center of the wetland experienced three stages: in-situ growth, spatial expansion and towards lake center transfer, thus moved from river deltas to lake center areas. Overall, the maximum EVIs of the wetland showed an increasing trend, with a rate of 0.0035, 0.0049, and 0.0028 EVI/year for the annual, spring and autumn, respectively. The findings systematically quantified vegetation productivity changes of the Lake Poyang Wetland in the post TGD era. It also provided a scientific basis for proposing water resource management strategies to maintain the stability of wetland ecosystem.

Increasing Impact of Precipitation on Alpine-Grassland Productivity over Last Two Decades on the Tibetan Plateau

Understanding the importance of temperature and precipitation on plant productivity is beneficial, to reveal the potential impact of climate change on vegetation growth. Although some studies have quantified the response of vegetation productivity to climate change at local, regional, and global scales, changes in climatic constraints on vegetation productivity over time are not well understood. This study combines the normalized difference vegetation index (NDVI) and the net primary production (NPP) modeled by CASA during the plant-growing season, to quantify the interplay of climatic (growing-season temperature and precipitation, GST and GSP) constraints on alpine-grassland productivity on the Tibetan Plateau, as well as the temporal dynamics of these constraints. The results showed that (1) 42.2% and 36.3% of grassland NDVI and NPP on the Tibetan Plateau increased significantly from 2000 to 2019. GSP controlled grassland growth in dryland regions, while humid grasslands were controlled by the GST. (2) The response strength of the NDVI and NPP to precipitation (partial correlation coefficient RNDVI-GSP and RNPP-GSP) increased substantially between 2000 and 2019. Especially, the RNDVI-GSP and RNPP-GSP increased from 0.14 and 0.01 in the first 10year period (2000–2009) to 0.83 and 0.78 in the second 10-year period (2010–2019), respectively. As a result, the controlling factor for alpine-grassland productivity variations shifted from temperature during 2000–2009 to precipitation during 2010–2019. (3) The increase in precipitation constraints was mainly distributed in dryland regions of the plateau. This study highlights that the climatic constraints on alpine-grassland productivity might change under ongoing climate change, which helps the understanding of the ecological responses and helps predict how vegetation productivity changes in the future.

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

Satellite observations document trends consistent with a boreal forest biome shift.

The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground‐based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.

UAV reveals substantial but heterogeneous effects of herbivores on Arctic vegetation

Understanding how herbivores shape plant biomass and distribution is a core challenge in ecology. Yet, the lack of suitable remote sensing technology limits our knowledge of temporal and spatial impacts of mammal herbivores in the Earth system. The regular interannual density fluctuations of voles and lemmings are exceptional with their large reduction of plant biomass in Arctic landscapes during peak years (12–24%) as previously shown at large spatial scales using satellites. This provides evidence that herbivores are important drivers of observed global changes in vegetation productivity. Here, we use a novel approach with repeated unmanned aerial vehicle (UAV) flights, to map vegetation impact by rodents, indicating that many important aspects of vegetation dynamics otherwise hidden by the coarse resolution of satellite images, including plant–herbivore interactions, can be revealed using UAVs. We quantify areas impacted by rodents at four complex Arctic landscapes with very high spatial resolution UAV imagery to get a new perspective on how herbivores shape Arctic ecosystems. The area impacted by voles and lemmings is indeed substantial, larger at higher altitude tundra environments, varies between habitats depending on local snow cover and plant community composition, and is heterogeneous even within habitats at submeter scales. Coupling this with spectral reflectance of vegetation (NDVI), we can show that the impact on central ecosystem properties like GPP and biomass is stronger than currently accounted for in Arctic ecosystems. As an emerging technology, UAVs will allow us to better disentangle important information on how herbivores maintain spatial heterogeneity, function and diversity in natural ecosystems.

Vegetation phenology dynamics as an indicator of energy and productivity functions in semi-arid savannah protected areas: a case study of Gonarezhou National Park in south-eastern Zimbabwe

Spatial and temporal patterns of vegetation productivity in semi-arid savanna national parks are influenced by differences in land cover and changes in time series trends. The main purpose of this paper is to analyse patterns of vegetation productivity metrics of base value, peak value, amplitude, and small and large integrals in Gonarezhou National Park (GNP) in south-eastern Zimbabwe from 1981 to 2015. Three sample sites comprising shrublands, deciduous broadleaved forested woodlands and mixed cover (shrublands, broadleaved deciduous forested woodlands and grasslands) were selected to show existing patterns of vegetation productivity for GNP. We used remotely sensed Normalised Difference Vegetation Index (NDVI) data which was further processed in the TIMESAT 3.3 program to derive productivity metrics. We then tested differences in land cover using analysis of variance and changes in time-series trends using Mann–Kendall and Theil–Sen’s tests. We note significant differences in land cover (P < 0.01) in selected samples. There are significant downward trends in the base value in shrublands (P < 0.01) and broadleaved deciduous forested woodlands (P = 0.04). Significant upward trends in the amplitude in the shrublands (P < 0.01) and mixed cover areas (P = 0.01) were noted. However, there are no changes in vegetation productivity, as indicated by the peak value and large and small integral indices. Shrublands are becoming vulnerable in terms of energy and vegetation productivity and need constant monitoring. Long-span coarse-resolution images are important stepping stones in providing a baseline for further studies from moderate and fine-resolution imagery. Research on vegetation productivity using fine-resolution imagery is more suitable for GNP.

A Decade's Change in Vegetation Productivity and Its Response to Climate Change over Northeast China.

In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (R2) = 0.84 and the root mean square error (RMSE) = 42.73 gC/m2·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m2·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources.

High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA

The inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks—a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling approach previously developed for the state of Maryland to 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain, which includes Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In this study, we employ an updated version of the Ecosystem Demography (ED) model, an improved lidar initialization strategy, and an expanded calibration/validation approach. High resolution (90 m) wall-to-wall maps of present aboveground carbon, aboveground carbon sequestration potential, aboveground carbon sequestration potential gap (CSPG), and time to reach sequestration potential were produced over the RGGI domain where airborne lidar data were available, including 100% of eight states, 62% of Maine, 12% of New Jersey, and 0.65% of New York. For the eight states with complete data, an area of 228 552 km2, the contemporary forest aboveground carbon stock is estimated to be 1134 Tg C, and the forest aboveground CSPG is estimated to be larger at >1770 Tg C. Importantly, these estimates of the potential for added aboveground carbon sequestration in forests are spatially resolved, are further partitioned between continued growth of existing trees and new afforested/reforested areas, and include time estimates for realization. They are also assessed for sensitivity to potential changes in vegetation productivity and disturbance rate in response to climate change. The results from this study are intended as input into regional, state, and local planning efforts that consider future climate mitigation in forests along with other land-use considerations.

Biophysical controls of increased tundra productivity in the western Canadian Arctic

Rapid climate warming has widely been considered as the main driver of recent increases in Arctic tundra productivity. Field observations and remote sensing both show that tundra “greening” has been widespread, but heterogeneity in regional and landscape-scale trends suggest that additional controls are mediating the response of tundra vegetation to warming. In this study, we examined the relationship between changes in vegetation productivity in the western Canadian Arctic and biophysical variables by analyzing trends in the Enhanced Vegetation Index (EVI) obtained from nonparametric regression of annual Landsat surface reflectance composites. We used Random Forests classification and regression tree modelling to predict the trajectory and magnitude of greening from 1984 to 2016 and identify biophysical controls. More than two-thirds of our study area showed statistically significant increases in vegetation productivity, but observed changes were heterogeneous, occurring most rapidly within areas of the Southern Arctic that were: (1) dominated by dwarf and upright shrub cover types, (2) moderately sloping, and (3) located at lower elevation. These findings suggest that the response of tundra vegetation to warming is mediated by regional- and landscape-scale variation in microclimate, topography and soil moisture, and physiological differences among plant functional groups. Our work highlights the potential of the joint analysis of annual remotely sensed vegetation indices and broad-scale biophysical data to understand spatial variation in tundra vegetation change.