Tracking changes in total biomass production or land productivity is an essential part of monitoring land transformations and long-term alterations of the health and productive capacity of land that are typically associated with land degradation. Persistent declines in land productivity impact many terrestrial ecosystem services that form the basis for sustainable livelihoods of human communities. Protected areas (PAs) are key to globally conserve biodiversity and ecosystem services that are critical for human well-being, and cover about 15% of the land worldwide. Here we globally assess the trends in land productivity in PAs of at least 10 km 2 and in their unprotected surroundings (10 km buffers) from 1999 to 2013. We quantify the percentage of the protected and unprotected land that shows stable, increasing or decreasing trends in land productivity, quantified as long-term (15 year) changes in above-ground biomass derived from satellite-based observations with a spatial resolution of 1 km. We find that 44% of the land in PAs globally has retained the productivity at stable levels from 1999 to 2013, compared to 42% of stable productivity in the unprotected land around PAs. Persistent increases in productivity are more common in the unprotected lands around PAs (32%) than within PAs (18%) globally, while about 14% of the protected land and 12% of the unprotected land around PAs has experienced declines in land productivity. Oceania has the highest percentage of land with stable productivity in PAs (57%), whereas Europe has the lowest percentage (38%) and also the largest share of protected land with increasing land productivity (32%). We discuss the observed differences between PAs and unprotected lands, and between different parts of the world, in relation to different types and levels of human activities and their impact on land productivity. Our assessment of land productivity dynamics helps to characterise the state, pressures and changes in and around protected areas globally. Further research may focus on more detailed analyses to disentangle the relative contribution of specific drivers (from climate change to land use change) and their interaction with land productivity dynamics and potential land degradation in different regions of the world.

The Integrated system for Natural Capital Accounting (INCA) was developed and supported by the European Commission to test and implement the System of integrated Environmental and Economic Accounting -Ecosystem Accounting (SEEA EA). Through the compilation of nine Ecosystem Services (ES) accounts, INCA can make available to any interested ecosystem accountant a number of lessons learned. Amongst the conceptual lessons learned, we can mention: (i) for accounting purposes, ES should be clustered according to the existence (or not) of a sustainability threshold; (ii) the assessment of ES flow results from the interaction of an ES potential and an ES demand; (iii) the ES demand can be spatially identified, but for an overarching environmental target, this is not possible; ES potential and ES demand could mis-match; (iv) because the

12Tracking changes in total biomass production or land productivity is an essential part of 13 monitoring land transformations and long-term alterations of the health and productive 14 capacity of land that are typically associated with land degradation. Persistent declines in land 15 productivity impact many terrestrial ecosystem services that form the basis for sustainable 16 livelihoods of human communities. Protected areas (PAs) are a key strategy in global efforts to 17 conserve biodiversity and ecosystem services that are critical for human well-being, and cover 18 about 15% of the land worldwide. Here we globally assess the trends in land productivity in PAs 19 of at least 10 km 2 and in their unprotected surroundings (10 km buffers) from 1999 to 2013. We 20 quantify the percentage of the protected and unprotected land that shows stable, increasing or 21 decreasing trends in land productivity, quantified as long-term (15 year) changes in above-22 ground biomass derived from satellite-based observations with a spatial resolution of 1 km. We 23 find that 44% of the land in PAs globally has retained the productivity at stable levels from 1999 24 to 2013, compared to 42% of stable productivity in the unprotected land around PAs. Persistent 25 increases in productivity are more common in the unprotected lands around PAs (32%) than 26within PAs (18%) globally, which may be related to more active management and vegetation 27cover changes in some of these unprotected lands. About 14% of the protected land and 12% of 28 the unprotected land around PAs has experienced declines in land productivity from 1999 to 29 2013 globally. Oceania has the highest percentage of land with stable productivity in PAs (57%) 30followed by Asia (52%). Europe is the continent with the lowest percentage of land with stable 31 productivity levels in PAs (38%) and with the largest share of protected land with increasing land 32 productivity (32%), which may be related to the high population density and share of agricultural 33 land within PAs as well as to rural land abandonment processes in many regions of Europe. In 34 conclusion, we provide a relevant indicator and assessment of land productivity dynamics that 35 contributes to characterise the state, pressures and changes in and around protected areas 36globally. Further research may focus on more detailed analyses to disentangle the relative 37 contribution of specific drivers (from climate change to land use change) and their interaction 38 with land productivity dynamics and potential land degradation in different regions of the world. 39

The agricultural industry in Africa has recently been impacted by rainfall variability and long-term changes in amount and distribution. Reliable rainfall forecasts on a daily timescale are vital for in-season decision-making. This study evaluated the relative prediction abilities of the European Centre for Medium-Range Weather Forecasts (ECMWF-S5) and the NOAA Climate Prediction System (CFS) gridded rainfall models across Africa and three sub-regions from2012–2022. The results indicate that the performance of both models declines with increasing lead times and improves with aggregated or coarser temporal resolutions. Besides, the ECMWF-S5 data represents observed daily rainfall better than the CFS data at all lead times, particularly in West Africa. On dekadal timescales, ECMWF-S5 outperformed CFS in all sub-regions, confirming its superiority. Both models are great at capturing rainfall at low elevations than at high elevations. CFS tends to overestimate low- and high-intensity rainfall events, while the ECMWF-S5slightly underestimates low-intensity rainfall events and accurately captures high-intensity events over Africa. Overall, the accuracy of these models in forecasting rainfall patterns in Africa varies according to the lead time, region, intensity of rainfall, and elevation. As a result, it is vital to use effective bias-correction approaches on these models to increase their accuracy and dependability for use in several sectors. This study emphasized the potential and shortcomings of the CFS and ECMWF-S5 models for climate impact studies, particularly in West Africa and regions with low elevations.